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  • 1.
    Ahlfors, Charlotta
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Weekly planning of hydropower in systems with large volumes and varying power generation: A literature review2021In: 2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings, Institute of Electrical and Electronics Engineers (IEEE) , 2021, article id 9495058Conference paper (Refereed)
    Abstract [en]

    Hydropower is the world's largest source of renewable electricity generation and hydropower plants with reservoirs provide flexibility to the power systems. Efficient planning techniques improve the flexibility of the power systems and reduce carbon emissions, which is needed in power systems exposed to a rapid change. Renewable energy sources, such as wind and solar power, are increasing in the power systems. Hydropower plants have low operating costs and are used as base power. This paper reviews hydropower planning in different time frames and specifically focuses on weekly planning, i.e. hydropower planning for 1 to 3 weeks. Main conclusions in this study are that the term weekly planning is seldom used and the definitions in earlier studies of short term, mid term and long term planning, respectively, varies. The authors propose that weekly planning should belong to mid term planning.

  • 2.
    Amelin, M.
    et al.
    KTH, Superseded Departments (pre-2005).
    Söder, L.
    KTH, Superseded Departments (pre-2005).
    On Monte Carlo simulation of electricity markets with uncertainties in precipitation and load forecasts2001In: Power Tech Proceedings, 2001 IEEE Porto, 2001, Vol. 1, p. 6-1Conference paper (Refereed)
    Abstract [en]

    Long-term planning of a power system requires that the electricity market can be simulated. One important aspect that should be simulated is that the owners of hydro power plants with reservoirs (generally referred to as dispatchable hydro power) are forced to base their scheduling on uncertain forecasts on precipitation and load. It is inevitable that this lack of perfect information has an impact on the operation costs and reliability of the system. Hence, a simulation of an electricity market should include this property of dispatchable hydro, power. This paper shows how the consequences of hydro power planning based on uncertain forecasts can be incorporated in a Monte Carlo model by using random water value errors

  • 3.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    An Evaluation of Intraday Trading and Demand Response for a Predominantly Hydro-Wind System Under Nordic Market Rules2015In: IEEE Transactions on Power Systems, ISSN 0885-8950, E-ISSN 1558-0679, Vol. 30, no 1, p. 3-12Article in journal (Refereed)
    Abstract [en]

    Many countries are planning for a large-scale expansion of wind power. This development will have a significant impact on power system operation and economics. One of the challenges is that the difficulty to forecast wind power generation will increase the need for real-time balancing. This paper presents a study of how the impact of wind power forecast errors can be reduced by changes in the market design. The study is based on the conditions in the Nordic electricity market. A characteristic of this market is that there is a large share of flexible hydro generation; hence, ramp and unit commitment constraints rarely constrain dispatch. The need for regulation during real-time is provided in a voluntary real-time balancing market, where players can be compensated for their redispatch costs. Case studies are presented which show that a shift from day-ahead to intraday trading and increased demand response can improve the performance when the share of wind power is increasing.

  • 4.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Comparison of Capacity Credit Calculation Methods for Conventional Power Plants and Wind Power2009In: IEEE Transactions on Power Systems, ISSN 0885-8950, E-ISSN 1558-0679, Vol. 24, no 2, p. 685-691Article in journal (Refereed)
    Abstract [en]

    Several methods for computing capacity credit values of power plants have been presented over the years. This paper uses an empirical approach to investigate and compare different properties of four typical capacity credit definitions. It is shown that the choice of definition indeed can have a significant impact on the results. Concerning three of the analyzed methods, it is found that important factors that influence the capacity credit are the overall generation adequacy and the penetration factor of the power plant; this means that the same generating unit will generally have a higher capacity credit if added to a system with high loss of load probability, and the unit will have a higher capacity credit if its installed capacity is small compared to the total installed capacity of the system. The results of the fourth method only depend on the size and availability of the generating units.

  • 5.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Impact of Trading Arrangements on Imbalance Costs2009Report (Other academic)
    Abstract [en]

    Today there are plans for large wind power investments in Sweden as well asin the neighbouring countries. At the same time, there is a developmenttowards increased price sensitivity of the consumers. These two changes arepartially connected to each other, because larger volumes wind power willresult in increased price variations in the spot market as well as the real-timebalancing market, which makes it desirable with consumers who are moreactive in the electricity market.This report studies different factors of the electricity trading arrangements,which are of importance to the efficiency of an electricity market with largevolumes of wind power and increased consumption flexibility. The study isbased on a new simulation model, which calculates the price for the differentphases of the electricity trading using supply and demand curves based onthe forecasts that are available in each phase. This model has then beenapplied to a number of test systems, which although fictitious, have the samebasic characteristics as the conditions found in the Nordic electricity market.The following factors of the design of the electricity market have beenstudied:• Planning horizon. The planning horizon refers to the delay time fromwhen the players have to submit bids to the spot market until the actualdelivery hour. The consequence of shortening the planning horizon is that theforecast errors will be smaller, especially for wind power forecasts. The resultsfrom the case study show that a shorter planning horizon is beneficial toalmost all players in the electricity market. If such a change of the electricitymarket is profitable does however depend on whether the value of theimproved forecasts is larger than the administrative costs.• Pricing of wind power imbalances. In the present Nordic electricitymarket, a two-price system is used for generation and a one-price system isused for consumption. An alternative would be to consider wind power asnegative load and include wind power imbalances in the consumptionimbalance of the balance responsible players. This would result in decreasedimbalance costs for wind power producers, but the results from the case studyshow that the differences are small compared to treating wind power as othergeneration. The explanation to this is that the imbalance costs in spite of allare only a few per cent of the wind power producer’ income of sellingelectricity.• Increased consumption flexibility. This reports considers theconsequences of introducing a new form contracts, which allows the retailersto initiate load reductions for certain consumers during a limited number ofhours per year. In the case study, this kind of contracts turned out to bebeneficial to all players (including those who were not themselves balanceresponsible for any consumption). The increased consumption flexibility alsoresulted in improved reliability of supply. These advantages must of course becompared to the costs of introducing such contracts and the necessaryinfrastructure

  • 6.
    Amelin, Mikael
    KTH, Superseded Departments (pre-2005), Electrical Systems.
    On Monte Carlo simulation and analysis of electricity markets2004Doctoral thesis, monograph (Other scientific)
    Abstract [en]

    This dissertation is about how Monte Carlo simulation can be used to analyse electricity markets. There are a wide range of applications for simulation; for example, players in the electricity market can use simulation to decide whether or not an investment can be expected to be profitable, and authorities can by means of simulation find out which consequences a certain market design can be expected to have on electricity prices, environmental impact, etc.

    In the first part of the dissertation, the focus is which electricity market models are suitable for Monte Carlo simulation. The starting point is a definition of an ideal electricity market. Such an electricity market is partly practical from a mathematical point of view (it is simple to formulate and does not require too complex calculations) and partly it is a representation of the best possible resource utilisation. The definition of the ideal electricity market is followed by analysis how the reality differs from the ideal model, what consequences the differences have on the rules of the electricity market and the strategies of the players, as well as how non-ideal properties can be included in a mathematical model. Particularly, questions about environmental impact, forecast uncertainty and grid costs are studied.

    The second part of the dissertation treats the Monte Carlo technique itself. To reduce the number of samples necessary to obtain accurate results, variance reduction techniques can be used. Here, six different variance reduction techniques are studied and possible applications are pointed out. The conclusions of these studies are turned into a method for efficient simulation of basic electricity markets. The method is applied to some test systems and the results show that the chosen variance reduction techniques can produce equal or better results using 99% fewer samples compared to when the same system is simulated without any variance reduction technique. More complex electricity market models cannot directly be simulated using the same method. However, in the dissertation it is shown that there are parallels and that the results from simulation of basic electricity markets can form a foundation for future simulation methods.

    Keywords: Electricity market, Monte Carlo simulation, variance reduction techniques, operation cost, reliability.

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  • 7.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Simulation of Trading Arrangements Impact on Wind Power Imbalance Costs2008In: 2008 10TH INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS, NEW YORK: IEEE , 2008, p. 25-31Conference paper (Refereed)
    Abstract [en]

    Uncertain wind power forecasts is a disadvantage in an electricity market where the majority of the trading is performed several hours before the actual delivery. This paper presents a model which can be used to study how changes in the trading arrangement-in particular changing the delay time between closure of the spot market and the delivery period or changing the imbalance pricing system-would affect different players in the electricity market. The model can be used in Monte Carlo simulation, which is demonstrated for an example system.

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  • 8.
    Amelin, Mikael
    KTH, Superseded Departments (pre-2005), Electric Power Systems.
    Small-scale Renewable Energy Sources for Rural Electrification. Possibilities and Limitations1998Report (Other academic)
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  • 9.
    Amelin, Mikael
    KTH, Superseded Departments (pre-2005), Signals, Sensors and Systems.
    The value of transmission capability between countries and regions2000Licentiate thesis, monograph (Other scientific)
  • 10.
    Amelin, Mikael
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Englund, Calle
    Fagerberg, Andreas
    Balansering av vindkraft och vattenkraft i norra Sverige2009Report (Other academic)
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  • 11.
    Amelin, Mikael
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Hersoug, Ellef
    Options for Rural Electrification in Developing Countries. A Case Study in Kasulu, Tanzania.1997Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
  • 12.
    Amelin, Mikael
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Knazkins, Valerijs
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Estimation of maximum power consumption in the grid area of Fortum, Stockholm2005Conference paper (Refereed)
  • 13.
    Amelin, Mikael
    et al.
    KTH, Superseded Departments (pre-2005).
    Söder, Lennart
    KTH, Superseded Departments (pre-2005).
    A fast multi-area economic hydro-thermal power system model1999In: NAPS, 1999Conference paper (Refereed)
  • 14.
    Amelin, Mikael
    et al.
    KTH, Superseded Departments (pre-2005).
    Söder, Lennart
    KTH, Superseded Departments (pre-2005).
    Cost estimations for power sources in rural electrification schemes1999In: ICEET, 1999, p. 98-105Conference paper (Refereed)
  • 15.
    Amelin, Mikael
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Taking Credit: The Impact of Wind Power on Supply Adequacy-Experience from the Swedish Market2010In: IEEE POWER ENERGY MAG, ISSN 1540-7977, Vol. 8, no 5, p. 47-52Article in journal (Refereed)
    Abstract [en]

    This article presents some general concepts about capacity credit values, which are illustrated by theoretical examples as well as practical experience from the Swedish electricity market. The capacity credit of a wind generating unit (or a block of generating units) represents the contribution of the unit to the supply adequacy of the system. The capacity credit of a power plant is an abstract quantity based on probability calculations and requires knowledge of the probability distributions for available generation capacity and load. To secure the reliability of supply, the Swedish system operator was given the responsibility to purchase annual contracts for a "power reserve".

  • 16.
    Amelin, Mikael
    et al.
    KTH, Superseded Departments (pre-2005).
    Söder, Lennart
    KTH, Superseded Departments (pre-2005).
    The Strata Tree: A Useful Tool for Simulation of Electricity Markets2002In: PMAPS 2002, Naples, Italy, 2002Conference paper (Refereed)
  • 17. Bakkabulindi, G.
    et al.
    Hesamzadeh, Mohammad Reza
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Da Silva, I. P.
    Models for conductor size selection in Single Wire Earth Return distribution networks2013In: IEEE AFRICON 2013, IEEE conference proceedings, 2013, p. 6757773-Conference paper (Refereed)
    Abstract [en]

    The use of the ground as the current return path often presents planning and operational challenges in power distribution networks. This study presents optimization-based models for the optimal selection of conductor sizes in Single Wire Earth Return (SWER) power distribution networks. By using mixed integer non-linear programming (MINLP), models are developed for both branch-wise and primary-lateral feeder selections from a discrete set of overhead conductor sizes. The models are based on a mathematical formulation of the SWER line, where the objective function is to minimize fixed and variable costs subject to constraints specific to SWER power flow. Load growth over different time periods is considered. The practical application is tested using a case study extracted from an existing SWER distribution line in Namibia. The results were consistent for different network operating scenarios.

  • 18.
    Bakkabulindi, Geofrey
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Hesamzadeh, Mohammad R.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Da Silva, I.P.
    Makerere University, Faculty of Technology.
    Planning Algorithm for Single Wire Earth Return Distribution Networks2012In: Power and Energy Society General Meeting, 2012 IEEE, 2012, p. 1-7Conference paper (Refereed)
    Abstract [en]

    Power flow in earth return distribution systems typically depends on geographical location and specific earth properties. The planning of such systems has to take into account different operational and safety constraints from conventional distribution systems. This work presents the mathematical modeling and planning of Single Wire Earth Return (SWER) power distribution networks. The SWER load flow is modeled and formulated as an optimization problem. Then by using a heuristic iterative procedure, a planning algorithm is developed for the SWER system. The developed procedure includes optimal feeder routing and overhead conductor selection for both primary and lateral feeders with load growth over several time periods. A 30 node test network extracted from a rural area in Uganda is used to test the algorithm's practical application to give reasonable and consistent results. The model presented can be used in planning SWER networks for areas which have previously not been electrified as well as determining suitable upgrades for existing SWER distribution feeders. The algorithm's mathematical modeling and simulations were done using the General Algebraic Modeling System (GAMS).

  • 19.
    Bakkabulindi, Geofrey
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Hesamzadeh, Mohammad R.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Da Silva, I.P.
    Lugujjo, E.
    A Heuristic Model for Planning of Single Wire Earth Return Power Distribution Networks2011In: Proceedings of the IASTED International Conference on Power and Energy Systems and Applications, PESA 2011, 2011, p. 215-222Conference paper (Refereed)
    Abstract [en]

    The planning of distribution networks with earth return is highly dependent on the ground's electrical properties. This study incorporates a load flow algorithm for Single Wire Earth Return (SWER) networks into the planning of such systems. The earth's variable conductive properties are modelled into the load flow algorithm and the model considers load growth over different time periods. It includes optimal conductor selection for the SWER system and can also be used to forecast when an initially selected conductor will need to be upgraded. The planning procedure is based on indices derived through an iterative heuristic process that aims to minimise losses and investment costs subject to load flow constraints. A case study in Uganda is used to test the model's practical application.

  • 20. Bompard, E.
    et al.
    Correia, P.
    Gross, G.
    Amelin, M.
    KTH, Superseded Departments (pre-2005).
    A Comparative Analysis of Congestion Management Schemes under a Unified Framework2002In: IEEE Power Engineering Review, ISSN 0272-1724, E-ISSN 1558-1705, Vol. 22, p. 59-60Article in journal (Refereed)
    Abstract [en]

    The restructuring of the electricity industry has spawned the introduction of new independent grid operators or IGOs, typically called transmission system operators (TSO), independent system operator (ISO) or regional transmission organizations (RTO), in various parts of the world. An important task of an IGO is congestion management (CM) and pricing. This activity has significant economic implications on every market participant in the IGO’s region. The paper briefly reviews the congestion management schemes and the associated pricing mechanism used by the IGO’s in five representative schemes. These were selected to Illustrate the various CM approaches in use: England and Wales, Norway, Sweden, PJM and Califomia. We develop a unified framework for the mathematical representation of the market dispatch and redispatch problems that the IGO must solve in CM in these various jurisdictions. We use this unified framework to develop meaningful metrics to compare the various CM approaches so as to assess their efficiency and the effectiveness of the market signals provided to the market participants. We compare, using a small test system, side by side, the performance of these schemes.

  • 21. Bompard, E.
    et al.
    Correia, P.
    Gross, G.
    Amelin, Mikael
    KTH, Superseded Departments (pre-2005).
    Congestion-management schemes: A comparative analysis under a unified framework2003In: IEEE Transactions on Power Systems, ISSN 0885-8950, E-ISSN 1558-0679, Vol. 18, no 1, p. 346-352Article in journal (Refereed)
    Abstract [en]

    The restructuring of the electricity industry has spawned the introduction of new independent grid operators (IGOs), typically called transmission system operators (TSOs); independent system operator (ISOs); or regional transmission organizations (RTOs), in various parts of the world. An important task of an IGO is congestion management (CM) and pricing. This activity has significant economic implications on every. market participant in the IGO's region. The paper briefly reviews the CM schemes and the associated pricing mechanism used by the IGOs in five representative schemes. These were selected to illustrate the various CM approaches in use: England and Wales, Norway, Sweden, PJM, and California. We develop a unified framework for the mathematical representation of the market dispatch and redispatch problems that the IGO must solve in CM in these various jurisdictions. We use this unified framework to develop meaningful metrics to compare the various CM approaches so as to assess their efficiency and the effectiveness of the market signals provided to the market participants. We compare, using a small test system, side by side, the performance of these schemes.

  • 22.
    Dimoulkas, Ilias
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    CHP operation scheduling under uncertainty: Estimating the value of thermal energy storage2014In: Proceedings from the 14th International Symposium on District Heating and Cooling / [ed] Anna Land, 2014Conference paper (Refereed)
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  • 23.
    Dimoulkas, Ilias
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Constructing Bidding Curves for a CHP Producer in Day-ahead Electricity Markets2014In: ENERGYCON 2014 - IEEE International Energy Conference, IEEE Computer Society, 2014, p. 487-494Conference paper (Refereed)
    Abstract [en]

    The operation of Combined Heat and Power (CHP) systems in liberalized electricity markets depends both on uncertain electricity prices and uncertain heat demand. In the future, uncertainty is going to increase due to the increased intermittent power induced by renewable energy sources. Therefore, the need for improved planning and bidding tools is highly important for CHP producers. This paper applies an optimal bidding model under the uncertainties of day-ahead market prices and the heat demand. The problem is formulated in a stochastic programming framework where future scenarios of the random variables are considered in order to handle the uncertainties. A case study is performed and conclusions are derived about the CHP operation and the need for heat storage.

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  • 24.
    Dimoulkas, Ilias
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Monte carlo simulation of district heating system short-term operation in electricity markets2017In: Energetika, ISSN 0235-7208, Vol. 63, no 3, p. 93-104Article in journal (Refereed)
    Abstract [en]

    Energy generation in district heating (DH) systems is usually done in combined heat and power (CHP) units which can efficiently produce both useful heat and electric power. There can also exist heat only boilers, electric heaters, heat pumps and heat storage tanks. The coupling of heat and power generation in the CHP units and the possibility to store heat for later use makes the short-term operation scheduling of such systems quite challenging. Furthermore, big DH systems produce power that is sold in the electricity markets. This makes the operation scheduling problem even more complex as the uncertainty of the electricity prices in the markets should be considered. To make optimal decisions under uncertainty, various mathematical optimization tools were developed, such as stochastic programming and robust optimization. In this paper, an approach based on a Monte Carlo simulation is followed. Initially, a model of DH system short-term operation and power trading is mathematically formulated. Then, this model is used to run a Monte Carlo simulation for a case study system where the values of stochastic parameters are simulated using autoregressive models. Results demonstrate that simulation is fast, taking 300-400 runs to converge. A comparison of two system configurations shows that the use of heat storage increases the daily expected profit by 11%. Finally, the electricity price volatility in this case study is such that mainly two CHP units are operating for most of the time.

  • 25.
    Dimoulkas, Ilias
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Probabilistic day-ahead CHP operation scheduling2015In: 2015 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, IEEE conference proceedings, 2015Conference paper (Refereed)
    Abstract [en]

    The production scheduling of combined heat and power plants is a challenging task. The need for simultaneous production of heat and power in combination with the technical constraints results in a problem with high complexity. Furthermore, the operation in the electricity markets environment means that every decision is made with unknown electricity prices for the produced electric energy. In order to compensate the increased risk of operating under such uncertain conditions, tools like stochastic programming have been developed. In this paper, the short-term operation scheduling model of a CHP system in the day-ahead electricity market is mathematically described and solved. The problem is formulated in a stochastic programming framework where the uncertain parameters of day-ahead electricity prices and the heat demand are incorporated into the problem in the form of scenarios. A case study is also performed with a CHP system operating in a district heating network and the value of heat storage capacity is estimated.

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  • 26.
    Dimoulkas, Ilias
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Use of temperature scenariosl medium and long-term probabilistic heat demand forecasting in district heating2018In: Euroheat and Power (English Edition), ISSN 1613-0200, Vol. 15, no 4, p. 10-16Article in journal (Refereed)
  • 27.
    Dimoulkas, Ilias
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Hesamzadeh, Mohammad Reza
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Forecasting Balancing Market Prices Using Hidden Markov Models2016In: 2016 13TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET (EEM), IEEE conference proceedings, 2016Conference paper (Refereed)
    Abstract [en]

    This paper presents a Hidden Markov Model (HMM) based method to predict the prices and trading volumes in the electricity balancing markets. The HMM are quite powerful in modelling stochastic processes where the underlying dynamics are not apparent. The proposed method provides both one hour and 12-36 hour ahead forecasts. The first is mostly useful to wind/solar producers in order to compensate their production imbalances while the second is important when submitting the offers to the day ahead markets. The results are compared to the ones from Markov-autoregressive model.

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  • 28.
    Dimoulkas, Ilias
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Levihn, Fabian
    KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.).
    District heating system operation in power systems with high share of wind power2017In: Journal of Modern Power Systems and Clean Energy, ISSN 2196-5625, E-ISSN 2196-5420, Vol. 5, no 6, p. 850-862Article in journal (Refereed)
    Abstract [en]

    The integration of continuously varying and not easily predictable wind power generation is affecting the stability of the power system and leads to increasing demand for balancing services. In this study, a short-term operation model of a district heating system is proposed to optimally schedule the production of both heat and power in a system with high wind power penetration. The application of the model in a case study system shows the increased flexibility offered by the coordination of power generation, consumption and heat storage units which are available in district heating systems.

  • 29.
    Dimoulkas, Ilias
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Herre, Lars
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Khastieva, Dina
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Nycander, Elis
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Mazidi, P.
    A hybrid model based on symbolic regression and neural networks for electricity load forecasting2018In: International Conference on the European Energy Market, EEM, IEEE Computer Society, 2018, article id 8469901Conference paper (Refereed)
    Abstract [en]

    This paper proposes a hybrid model for electricity load forecasting. Symbolic regression is initially used to automatically create a regression model of the load. Then the explanatory variables and their transformations that have been selected in the model are used as input in an artificial neural network that is trained to predict the electricity load at the output. Therefore symbolic regression operates as a feature selection-creation method and forecasting is done by the artificial neural network. The proposed hybrid model has been successfully used in an electricity load forecasting competition.

  • 30.
    Dimoulkas, Ilias
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Khastieva, Dina
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Constructing Offering Curves for a CSP Producer in Day-ahead Electricity Markets2016In: 6th Solar Integration Workshop: International workshop on integration of solar power into power systems / [ed] Uta Betancourt / Thomas Ackermann, 2016, p. 424-431Conference paper (Refereed)
    Abstract [en]

    In many countries, the installation and operation of concentrated solar power plants has been promoted with high feed-in tariffs and other incentives. However, as this technology is becoming more mature and the installation costs are being reduced, the incentives are minimized or totally abolished. Under these new economic conditions, there is an increased need for operation planning and power trading tools that will help the operators of such systems to make optimal decisions under the various uncertainties they face. This paper provides a model that can be used to derive the offering curves of a CSP producer in the day-ahead (spot) market. The model can also be used for the hourly short-term operation planning of the system. In order to tackle with the uncertainties of electricity prices and solar irradiance, the stochastic programming framework is used and a risk measure is incorporated into the model. A case study is conducted to show the applicability of the model.

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  • 31. Dires, F. G.
    et al.
    Amelin, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Bekele, G.
    Deterministic Hydropower Simulation Model for Ethiopia2021In: 2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings, Institute of Electrical and Electronics Engineers (IEEE) , 2021, article id 9494862Conference paper (Refereed)
    Abstract [en]

    This paper presents a long-term deterministic linear simulation model for the Ethiopian hydropower system, intending to utilize the water stored in the rainy season throughout the year with minimum load shedding. Two cases are simulated and compared to historical data. The base case represents current load levels, and the second case represents a load level increase. The results show that the Ethiopian hydropower system has a great deal of flexibility to be operated in a more efficient way to minimize load shedding. The results also show that the system can support a 50% load increase with minimum load shedding, mostly when the load demand exceeds the total generating capacity. The contribution of this paper is to apply a standard hydropower model for Ethiopia to estimate the potential of the Ethiopian hydropower system to avoid or minimize load shedding with improved generation and operation planning. 

  • 32.
    Dires, Firehiwot Girma
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems. Addis Ababa Inst Technol, Sch Elect & Comp Engn, Addis Ababa 385, Ethiopia..
    Amelin, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Bekele, Getachew
    Addis Ababa Inst Technol, Sch Elect & Comp Engn, Addis Ababa 385, Ethiopia..
    Inflow Scenario Generation for the Ethiopian Hydropower System2023In: Water, E-ISSN 2073-4441, Vol. 15, no 3, article id 500Article in journal (Refereed)
    Abstract [en]

    In a hydropower system, inflow is an uncertain stochastic process that depends on the meteorology of the reservoir's location. To properly utilize the stored water in reservoirs, it is necessary to have a good forecast or a historical inflow record. In the absence of these two pieces of information, which is the case in Ethiopia and most African countries, the derivation of the synthetic historical inflow series with the appropriate time resolution will be a solution. This paper presents a method of developing synthetic historical inflow time series and techniques to identify the stochastic process that mimics the behavior of the time series and generates inflow scenarios. The methodology was applied to the Ethiopian power system. The time series were analyzed using statistical methods, and the stochastic process that mimics the inflow patterns in Ethiopia was identified. The Monte Carlo simulation was used to generate sample realizations of random scenarios from the identified stochastic process. Then, three cases of inflow scenarios were tested in a deterministic simulation model of the Ethiopian hydropower system and compared with the actual operation. The results show that the generated inflow scenarios give a realistic output of generation scheduling and reasonable reservoir content based on the actual operation.

  • 33.
    Dires, Firehiwot Girma
    et al.
    School of Electrical and Computer Engineering, Addis Ababa Institute of Technology, 385, Addis Ababa, Ethiopi.
    Amelin, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Bekele, Getachew
    School of Electrical and Computer Engineering, Addis Ababa Institute of Technology, 385, Addis Ababa, Ethiopia.
    Long-Term Hydropower Planning for Ethiopia: A Rolling Horizon Stochastic Programming Approach with Uncertain Inflow2023In: Energies, E-ISSN 1996-1073, Vol. 16, no 21, article id 7399Article in journal (Refereed)
    Abstract [en]

    All long-term hydropower planning problems require a forecast of the inflow during the planning period. However, it is challenging to accurately forecast inflows for a year or more. Therefore, it is common to use stochastic models considering the uncertainties of the inflow. This paper compares deterministic and stochastic models in a weekly rolling horizon framework considering inflow uncertainty. The stochastic model is tested in both a risk-neutral and a risk-averse version. The rolling horizon framework helps make periodic decisions and update the information in each rolling week, which minimizes the errors in prolonged forecasts. The models aim to utilize the water stored in the rainy season throughout the year with minimum load shedding while storing as much water as possible at the end of the planning horizon. The Conditional Value at Risk ((Formula presented.)) risk measure is used to develop the risk-averse stochastic model. Three different risk measures are investigated to choose the risk measure that yields the best outcome in the risk-averse problem, and the two best measures are compared to a deterministic and risk-neutral model in a weekly rolling horizon framework. The results show that the risk-neutral and best risk-averse models perform almost equally and are better than the deterministic model. Hence, using a stochastic model would be an improvement to the actual planning performed in the Ethiopian and other African countries’ power systems.

  • 34. Estanqueiro, A.
    et al.
    Ardal, A. R.
    O'Dwyer, C.
    Flynn, D.
    Huertas-Hernando, D.
    Lew, D.
    Gomez-Lazaro, E.
    Ela, E.
    Revuelta, J.
    Kiviluoma, J.
    Rodrigues, L.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Holtinen, H.
    Energy storage for wind integration: Hydropower and other contributions2012In: Power and Energy Society General Meeting, 2012 IEEE, IEEE , 2012, p. 6344652-Conference paper (Refereed)
    Abstract [en]

    The amount of wind power and other timevariable non-dispatchable renewable energy sources (RES) is rapidly increasing in the world. A few power systems are already facing very high penetrations from variable renewables which can surpass the systems' consumption during no-load periods, requiring the energy excess to be curtailed, exported or stored. The limitations of electric energy storage naturally lead to the selection of the well-known form of storing potential energy in reservoirs of reversible hydropower stations, although other technologies such as heat storage are also being used successfully. This paper reviews the storage technologies that are available and may be used on a power system scale and compares their advantages and disadvantages for the integration of fast-growing renewables, such as wind power, with a special focus on the role of pumped hydro storage.

  • 35.
    Fester, Christian
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Kouveliotis Lysikatos, Iasonas
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Marin, Manuel
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Open-Source Modelling and Simulation of a District Heating and Electricity Energy System2022In: 1st International Workshop on Open Source Modelling and Simulation of Energy Systems, OSMSES 2022 - Proceedings, Institute of Electrical and Electronics Engineers (IEEE) , 2022Conference paper (Refereed)
    Abstract [en]

    Open multi-energy system models are becoming increasingly more important for transitioning into a sustainable energy system. Open-source energy modelling tools like SpineOpt can provide such a transparent and flexible framework for performing complex and realistic case studies. In this paper, a short-term electricity and heat dispatch model with different types of Combined Heat and Power units and Power-to-Heat systems is implemented and simulated, using SpineOpt. The model’s performance and efficacy is evaluated against the commercial equation-based optimisation library GUROBIPY with good results. The model and the data are made openly available.

  • 36.
    Gonzalez, Jose Luis
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Dimoulkas, Ilias
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Operation Planning of a CSP Plant in the Spanish Day-ahead Electricity Market2014Conference paper (Refereed)
    Abstract [en]

    This paper addresses the short-term operation planning of a concentrated solar power (CSP) plant equipped with a backup fuel boiler and operating in the Spanish day-ahead electricity market. The problem is formulated as a mixed-integer linear programming model. Forecasted values of electricity prices and direct sun irradiation are considered. The main concern in the problem is to set an optimal use of the backup system in order to increase power generation and maximize the profits. Interaction between the solar and fuel heated systems is considered through heat balance constraints while parameters referring to the boiler are independent from the rest of the system allowing various types of boilers to be tested. A realistic case study provides results of a CSP plant operating a) without boiler, b) with a natural gas boiler and c) with a biomass boiler. Results demonstrate the advantages of the proposed model.

  • 37.
    Hamon, Camille
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Shayesteh, Ebrahim
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Two partitioning methods for multi-area studies in large power systems2015In: International Transactions on Electrical Energy Systems, E-ISSN 2050-7038, Vol. 25, no 4, p. 648-660Article in journal (Refereed)
    Abstract [en]

    Multi-area studies are an important tool for today's and future power systems. In this paper, a two-step algorithm for creating multi-area models is presented that, first, identifies areas, and, second, computes reduced models of these areas. For the first step, two new methods to identify areas in power systems have been developed. The first method is based upon spectral partitioning, whereas the second one is formulated as a linear optimization problem. The methods are compared in terms of computation time on the IEEE 118 bus system, and the first method clearly stands out in this comparison. The first method is then applied to the IEEE 300 bus system and to a model of the Polish power system with 2746 buses to study how it scales in large power systems. Even in the latter case, it runs in less than 30s. For the second step, existing equivalencing methods can be used. As an example, radial, equivalent, and independent equivalents are used to model the areas identified by the partitioning methods. The partitioning and equivalencing methods have been tested on the IEEE 118 bus system by running 1000 regular and optimal power flows. Comparisons with the original IEEE 118 bus system in terms of flows, costs and losses are carried out.

  • 38.
    Hesamzadeh, Mohammad
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    A generation expansion planning model of a strategic electricity generating firm2011In: Power and Energy Society General Meeting, 2011 IEEE, IEEE , 2011, p. 1-7Conference paper (Refereed)
    Abstract [en]

    This paper derives a mathematical structure for investment decisions of a profit-maximising and strategic producer in liberalised electricity markets. The paper assumes a Cournot producer in an energy market with nodal pricing regime. The Cournot producer is assumed to have revenue from selling energy to the pool. The investment problem of the strategic producer is modelled through a leader-follower game in applied mathematics. The leader is the strategic producer seeking the optimal mix of its investment technologies and the follower is a stochastic estimator. The stochastic estimator forecasts the reactions of other producers in the market in response to the investment decisions of the producer in question. The stochastic estimator takes the investment decisions of the producer and it calculates the stochastic prices. The mathematical structure is a stochastic linear bilevel programming problem. This problem is reformulated as a stochastic MILP problem which can be solved using the commercially available software packages. Finally, the developed mathematical structure is applied to a six-node example system to highlight the strengths of the whole approach.

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  • 39.
    Hesamzadeh, Mohammad
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Assessment of the market power cost in liberalised electricity markets using SMPI, PMPI, and NMPI indicators2011In: Energy Market (EEM), 2011 8th International Conference on the European, 2011, p. 844-848Conference paper (Refereed)
    Abstract [en]

    Market power analysis is one of the major issues facing regulators of wholesale electricity markets. The exercise of market power both distorts wholesale price signals and reduces the efficiency of the operation of and investment in the wholesale electricity market. This paper deals with a systematic way for quantifying and visualising market power. The paper first proposes three indicators termed the System Market Power Indicator, SMPI, the Producer Market Power Indicator, PMPI, and the Nodal Market Power Indicator, NMPI. The game theory in applied mathematics and the concept of social welfare in microeconomics are used in formulating of these indicators. The SMPI finds the total cost of exercising market power by generating companies. The contribution of a specific generating company in system market power is calculated using the PMPI. The NMPI finds the contribution of each power system node in the total market power cost. Then after, a colour contour map is used to visualise the exercise of market power and its associated cost. The proposed market power indicators are applied to the modified Garver’s example system to show the promising performance of these indicators.

  • 40.
    Hesamzadeh, Mohammad
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Modelling market power cost in the assessment of transmission investment policies2011In: PowerTech, 2011 IEEE Trondheim, 2011, p. 1-6Conference paper (Refereed)
    Abstract [en]

    This paper develops a mathematical tool for modelling market power cost in transmission expansion planning decisions. The mathematical modelling is based on the game theory in applied mathematics and the concept of social welfare in microeconomics. We assume the generating companies as Cournot players and the Transmission System Operators as a regulated social transmission planner. To tackle the multiple Nash equilibria problem, the concept of worst-Nash equilibrium is defined and mathematically formulated. The developed mathematical structure is a mixed-integer linear programming problem. This closed form mathematical structure can be solved efficiently using the available computational packages.

  • 41.
    Hesamzadeh, Mohammad R.
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Rahman, A K M Zami-Ur
    KTH, School of Information and Communication Technology (ICT), Electronic Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    The Probabilistic TC-PSI for Studying Market Power2011Conference paper (Refereed)
    Abstract [en]

    It is widely recognized that wholesale electricity markets tend to be prone to the exercise of market power. The exercise of market power has antisocial impacts in the liberalised electricity markets. It results in inefficient short-term dispatch outcomes, and affects the efficiency of longer-term generation investment decisions. And thus, it results in power price rises and substantial wealth transfers between electricity customers and generators. Electricity market regulators around the world tend to be interested in mechanisms for predicting marker power ex ante and detecting and controlling the exercise of market power ex post. The common indices of ex ante market power indicators however, mostly disregard transmission constraints, variation of wind farms' capacities, and dynamics of electric power systems. This paper carries out a probabilistic study of market power using an index termed Probabilistic Transmission-Constrained Pivotal Supplier Indicator (Probabilistic TC-PSI). Two probabilistic approaches (a) Monte Carlo Method (MCM), and (b) Two-Point Estimation Method (T-PEM) are employed in the probabilistic study and then compared.

  • 42.
    Khastieva, Dina
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Short-term planning of hydro-thermal system with high wind energy penetration and energy storage2016In: IEEE Power and Energy Society General Meeting, IEEE, 2016Conference paper (Refereed)
    Abstract [en]

    Wind based electricity generation is considered as one of the solutions for emission reduction. However, variability and uncertainty of wind speeds create challenges for balancing in the power systems and in many cases require improvements in ramping capabilities of the system along with additional reserved generation capacity. Ramping capability as well as generation reserves could be provided by different technologies such as thermal and hydro generation and different types of energy storage. The last option is considered to be a possible solution for power systems with large wind generation. This paper provides a model for short-term planning of the hydro-thermal power system with high wind energy penetration and presence of a large scale energy storage unit. The model is used to compare the effect of different generation mix and energy storage presence on the operation of the power system and balancing cost in particular.

  • 43.
    Khastieva, Dina
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Dimoulkas, Ilias
    KTH.
    Amelin, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Optimal Investment Planning of Bulk Energy Storage Systems2018In: Sustainability, E-ISSN 2071-1050, Vol. 10, no 3, article id 610Article in journal (Refereed)
    Abstract [en]

    Many countries have the ambition to increase the share of renewable sources in electricity generation. However, continuously varying renewable sources, such as wind power or solar energy, require that the power system can manage the variability and uncertainty of the power generation. One solution to increase flexibility of the system is to use various forms of energy storage, which can provide flexibility to the system at different time ranges and smooth the effect of variability of the renewable generation. In this paper, we investigate three questions connected to investment planning of energy storage systems. First, how the existing flexibility in the system will affect the need for energy storage investments. Second, how presence of energy storage will affect renewable generation expansion and affect electricity prices. Third, who should be responsible for energy storage investments planning. This paper proposes to assess these questions through two different mathematical models. The first model is designed for centralized investment planning and the second model deals with a decentralized investment approach where a single independent profit maximizing utility is responsible for energy storage investments. The models have been applied in various case studies with different generation mixes and flexibility levels. The results show that energy storage system is beneficial for power system operation. However, additional regulation should be considered to achieve optimal investment and allocation of energy storage.

  • 44.
    Khastieva, Dina
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Hesamzadeh, Mohammad Reza
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Vogelsang, I.
    Rosellón, J.
    Amelin, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Value of energy storage for transmission investments2019In: Energy Strategy Reviews, ISSN 2211-467X, E-ISSN 2211-4688, Vol. 24, p. 94-110Article in journal (Refereed)
    Abstract [en]

    This paper investigates joint investment planning of transmission lines and energy storage. Energy storage can be seen as a complement to transmission infrastructure and can be used for transmission deferral. On the other hand, under certain conditions, when the expected profit of both sectors depends on congestion in the system, transmission and energy storage can be seen as competitors. The transmission sector is in this study assumed to be a natural monopoly and operation and planning of transmission lines is performed by an independent company whereas the energy storage owner company operates and invests under competitive market rules. Three main questions are addressed in this paper. First of all, will additional energy storage capacity contribute to the growth of social welfare? Second, how will incentive regulation of the transmission network affect the need for energy storage? Third, how will the choice of incentive regulation affect the value of energy storage. This paper first provides an overview of incentive regulation which can be applied to transmission investments. Then case studies based on a 6-node power system network and the IEEE 118-node system are proposed in order to answer the aforementioned questions. The results of the case studies show that energy storage investments complement transmission expansion and contribute to higher social welfare values. The benefits from energy storage investments are significantly higher under two investigated incentive regulations as compared to the case without incentive regulation. Thus, the transmission investment planning process should consider energy storage options.

  • 45.
    Khodadadi, Abolfazl
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Herre, Lars
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Shinde, Priyanka
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Eriksson, Robert
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Nordic Balancing Markets: Overview of Market Rules2020In: International Conference on the European Energy Market, EEM, IEEE Computer Society , 2020Conference paper (Refereed)
    Abstract [en]

    System operators have the option to trade balancing reserves among countries and operators. In order to trade balancing reserves with other system operators the markets should be harmonized. While the spot and intraday markets are already harmonized within the Nordics, the balancing markets still display differences. The differences can be subtle, yet they may play a significant role for the planning, operation, modelling and control of the power system. In this paper, we conduct a thorough literature review on Nordic balancing markets and summarize the market rules and requirements. This review can help operators and modellers to better represent the Nordic power system.

  • 46.
    Khodadadi, Abolfazl
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Flexible Stochastic Bilevel Scheduling Strategy in Hydropower Dominated Energy Markets2022In: Proceedings of the 11th International Conference on Innovative Smart Grid Technologies - Asia, ISGT-Asia 2022, Institute of Electrical and Electronics Engineers (IEEE) , 2022, p. 245-249Conference paper (Refereed)
    Abstract [en]

    This paper presents an electricity market that in-cludes day-ahead energy and manual frequency replacement reserve (mFRR) markets and consists of cascaded hydropower plants (HPs) offering their aggregated capacity to these markets. The proposed model is a two-stage bilevel offering strategy to show the hierarchical decision-making process in the European electricity market. The upper-level describes the day-ahead profit maximization optimization considering the opportunity cost of saving water which is controlled through the real-time dispatch in the operation day and mFRR capacity requirements imposed from TSO. In the lower-level, the mFRR energy market with their corresponding active-time duration is modeled to control the real-time discharge of water and upward or downward offering strategies. The new approach provides the flexibility for the planning and operational stages to define their own objective functions, maximize their profits and conserve the proper interaction between them through linking variables.

  • 47.
    Khodadadi, Abolfazl
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Stochastic adaptive robust approach for day-ahead energy market bidding strategies in hydro dominated sequential electricity markets2022In: Sustainable Energy, Grids and Networks, E-ISSN 2352-4677, Vol. 32, article id 100827Article in journal (Refereed)
    Abstract [en]

    This paper presents a novel methodological approach for the optimal day-ahead energy market bidding behavior of a cascaded hydropower plants (HPPs) portfolio in the sequential electricity markets. The understudy markets are day-ahead energy market and manual frequency restoration reserve (mFRR) markets in both capacity and energy setups. The introduction of the mFRR capacity market ensures transmission system operators (TSOs) about the availability of energy bids in the real-time market, which acts as binding constraints in the mFRR energy markets. As a determining factor, the active-time duration of mFRR energy bids is uncertain at the time of day-ahead bidding, which is modeled as the intervals in our robust optimization, while the electricity prices are considered as the scenarios in the stochastic optimization. Hence, we have proposed a novel stochastic adaptive robust optimization to address the bidding problem in the face of uncertainties accurately. The results show a considerable improvement compared to the conventional fully-stochastic approach in the case study of Swedish cascaded hydropower plants.

  • 48. Kiviluoma, Juha
    et al.
    Pallonetto, Fabiano
    Marin, Manuel
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Savolainen, Pekka T.
    Soininen, Antti
    Vennström, Per
    Rinne, Erkka
    Huang, Jiangyi
    Kouveliotis Lysikatos, Iasonas
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Ihlemann, Maren
    Delarue, Erik
    O’Dwyer, Ciara
    O’Donnel, Terence
    Amelin, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Dillon, Joseph
    Spine Toolbox: A flexible open-source workflow management system with scenario and data management2022In: SoftwareX, ISSN 2352-7110, Vol. 17, p. 100967-100967, article id 100967Article in journal (Refereed)
    Abstract [en]

    The Spine Toolbox is open-source software for defining, managing, simulating and optimising energy system models. It gives the user the ability to collect, create, organise, and validate model input data, execute a model with selected data and finally archive and visualise results/output data. Spine Toolbox has been designed and developed to support the creation and execution of multivector energy integration models. It conveniently facilitates the linking of models with different scopes, or spatio-temporal resolutions, through the user interface. The models can be organised as a direct acyclic graph and efficiently executed through the embedded workflow management engine. The software helps users to import and manage data, define models and scenarios and orchestrate projects. It supports a self-contained and shareable entity-relationship data structure for storing model parameter values and the associated data. The software is developed using the latest Python environment and supports the execution of plugins. It is shipped in an installation package as a desktop application for different operating systems.

  • 49.
    Kouveliotis Lysikatos, Iasonas
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    The value of coordinating the operation of small-scale hydro2022Conference paper (Refereed)
    Abstract [en]

    Small-scale hydropower production is a comparatively small power resource, but it is valuable as it is CO2-free, renewable, and flexible.~However, small-scale hydropower owners in Sweden often operate their plants empirically and without coordinating with other plant owners of the same river system, possibly resulting in suboptimal water usage.~This paper investigates two different hydropower planning strategies for small-scale hydro in a realistic case study from historical hydrological data. Two scheduling models are formulated and compared; a coordinated scheduling model assumes centralised information sharing to calculate optimal planning results, and a successive, greedy planning process, where each power plant determines its operational schedule individually and passively, depending on the water discharged from the upstream plants.

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  • 50.
    Kouveliotis Lysikatos, Iasonas
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Marin, Manuel
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Amelin, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Exploring Multitemporal Hydro Power Models of the Nordic Power System using Spine Toolbox2020In: UPEC 2020 - 2020 55th International Universities Power Engineering Conference, Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2020, article id 9209852Conference paper (Refereed)
    Abstract [en]

    This paper presents the development and simulation of hydro power models in the open source energy modelling framework Spine. We study the market-based hourly operation of the Skellefte river in the Swedish hydro power system using the abstract representation of \textit{Spine Model}, in order to employ and demonstrate its available functionalities, focusing on the automated handling of the temporal resolution of the optimization model. The Spine temporal block is used for automating the transformation of the temporal resolution of the model in different time intervals, as well as the manipulation of various modelling parameters. After the mathematical formulation of the optimization problem and the detailed analysis of the modelling steps in Spine, various results are extracted discussing the added value of Spine.

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