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Khastieva, D., Dimoulkas, I. & Amelin, M. (2018). Optimal Investment Planning of Bulk Energy Storage Systems. Sustainability, 10(3), Article ID 610.
Open this publication in new window or tab >>Optimal Investment Planning of Bulk Energy Storage Systems
2018 (English)In: Sustainability, ISSN 2071-1050, E-ISSN 2071-1050, Vol. 10, no 3, article id 610Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
MDPI, 2018
Keywords
energy storage, power system planning, wind power generation, stochastic processes
National Category
Energy Systems
Identifiers
urn:nbn:se:kth:diva-226803 (URN)10.3390/su10030610 (DOI)000428567100037 ()2-s2.0-85042566241 (Scopus ID)
Note

QC 20180427

Available from: 2018-04-27 Created: 2018-04-27 Last updated: 2018-04-27Bibliographically approved
Dimoulkas, I., Amelin, M. & Levihn, F. (2017). District heating system operation in power systems with high share of wind power. Journal of Modern Power Systems and Clean Energy, 5(6), 850-862
Open this publication in new window or tab >>District heating system operation in power systems with high share of wind power
2017 (English)In: 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) Published
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.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2017
Keywords
Combined heat and power (CHP), District heating systems, Flexible power system operation, Heat storage
National Category
Energy Systems
Identifiers
urn:nbn:se:kth:diva-220217 (URN)10.1007/s40565-017-0344-6 (DOI)000416327000003 ()2-s2.0-85037054066 (Scopus ID)
Note

QC 20171219

Available from: 2017-12-19 Created: 2017-12-19 Last updated: 2017-12-22Bibliographically approved
Dimoulkas, I. & Amelin, M. (2017). Monte carlo simulation of district heating system short-term operation in electricity markets. Energetika, 63(3), 93-104
Open this publication in new window or tab >>Monte carlo simulation of district heating system short-term operation in electricity markets
2017 (English)In: Energetika, ISSN 0235-7208, Vol. 63, no 3, p. 93-104Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Lithuanian Academy of Sciences Publishers, 2017
Keywords
Combined heat and power, District heating, Electricity markets, Monte Carlo simulation, Short-term operation
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-219662 (URN)10.6001/energetika.v63i3.3560 (DOI)2-s2.0-85035235835 (Scopus ID)
Note

QC 20171212

Available from: 2017-12-12 Created: 2017-12-12 Last updated: 2017-12-12Bibliographically approved
Dimoulkas, I. & Amelin, M. (2015). Probabilistic day-ahead CHP operation scheduling. In: 2015 IEEE POWER & ENERGY SOCIETY GENERAL MEETING: . Paper presented at General Meeting of the IEEE-Power-and-Energy-Society, JUL 26-30, 2015, Denver, CO. IEEE conference proceedings
Open this publication in new window or tab >>Probabilistic day-ahead CHP operation scheduling
2015 (English)In: 2015 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, IEEE conference proceedings, 2015Conference paper, Published 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.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2015
Series
IEEE Power and Energy Society General Meeting PESGM, ISSN 1944-9925
National Category
Energy Systems
Identifiers
urn:nbn:se:kth:diva-184576 (URN)10.1109/PESGM.2015.7285962 (DOI)000371397501101 ()2-s2.0-84956862139 (Scopus ID)978-1-4673-8040-9 (ISBN)
Conference
General Meeting of the IEEE-Power-and-Energy-Society, JUL 26-30, 2015, Denver, CO
Note

QC 20160404

Available from: 2016-04-04 Created: 2016-04-01 Last updated: 2017-02-01Bibliographically approved
Dimoulkas, I. & Amelin, M. (2014). CHP operation scheduling under uncertainty: Estimating the value of thermal energy storage. In: Anna Land (Ed.), Proceedings from the 14th International Symposium on District Heating and Cooling: . Paper presented at 14th International Symposium on District Heating and Cooling, Stockholm, September 6-10, 2014.
Open this publication in new window or tab >>CHP operation scheduling under uncertainty: Estimating the value of thermal energy storage
2014 (English)In: Proceedings from the 14th International Symposium on District Heating and Cooling / [ed] Anna Land, 2014Conference paper, Poster (with or without abstract) (Refereed)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering; Energy Technology
Identifiers
urn:nbn:se:kth:diva-165892 (URN)978-91-85775-24-8 (ISBN)
Conference
14th International Symposium on District Heating and Cooling, Stockholm, September 6-10, 2014
Funder
SweGRIDS - Swedish Centre for Smart Grids and Energy Storage
Note

QC 20150507

Available from: 2015-04-30 Created: 2015-04-30 Last updated: 2017-02-01Bibliographically approved
Dimoulkas, I. & Amelin, M. (2014). Constructing Bidding Curves for a CHP Producer in Day-ahead Electricity Markets. In: ENERGYCON 2014 - IEEE International Energy Conference: . Paper presented at 2014 IEEE International Energy Conference, ENERGYCON 2014; Dubrovnik; Croatia; 13 May 2014 through 16 May 2014 (pp. 487-494). IEEE Computer Society
Open this publication in new window or tab >>Constructing Bidding Curves for a CHP Producer in Day-ahead Electricity Markets
2014 (English)In: ENERGYCON 2014 - IEEE International Energy Conference, IEEE Computer Society, 2014, p. 487-494Conference paper, Published 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.

Place, publisher, year, edition, pages
IEEE Computer Society, 2014
Series
IEEE International Energy Conference, ISSN 2164-4322
Keywords
Combined Heat and Power, CHP, bidding curves, stochastic programming, operation planning
National Category
Energy Systems Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-157236 (URN)10.1109/ENERGYCON.2014.6850471 (DOI)000343646400075 ()2-s2.0-84905025278 (Scopus ID)978-1-4799-2449-3 (ISBN)
Conference
2014 IEEE International Energy Conference, ENERGYCON 2014; Dubrovnik; Croatia; 13 May 2014 through 16 May 2014
Note

QC 20141208

Available from: 2014-12-08 Created: 2014-12-08 Last updated: 2017-02-01Bibliographically approved
Gonzalez, J. L., Dimoulkas, I. & Amelin, M. (2014). Operation Planning of a CSP Plant in the Spanish Day-ahead Electricity Market. In: : . Paper presented at ¨11th International Conference on the European Energy Market, EEM 2014; Krakow; Poland; 28 May 2014 through 30 May 2014.
Open this publication in new window or tab >>Operation Planning of a CSP Plant in the Spanish Day-ahead Electricity Market
2014 (English)Conference paper, Published 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.

Series
International Conference on the European Energy Market, ISSN 2165-4077
Keywords
Concentrated solar power, CSP, operation planning, spot market, backup boiler
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-158334 (URN)10.1109/EEM.2014.6861303 (DOI)000345229900101 ()2-s2.0-84905693956 (Scopus ID)978-1-4799-6095-8 (ISBN)978-147996094-1 (ISBN)
Conference
¨11th International Conference on the European Energy Market, EEM 2014; Krakow; Poland; 28 May 2014 through 30 May 2014
Note

QC 20150126

Available from: 2015-01-26 Created: 2015-01-07 Last updated: 2016-12-02Bibliographically approved
Moiseeva, E., Hesamzadeh, M. R. & Dimoulkas, I. (2014). Tacit Collusion with Imperfect Information: Ex-Ante Detection. In: : . Paper presented at IEEE PES General Meeting, JUL 27-31, 2014, National Harbor, MD. IEEE conference proceedings
Open this publication in new window or tab >>Tacit Collusion with Imperfect Information: Ex-Ante Detection
2014 (English)Conference paper, Published paper (Refereed)
Abstract [en]

The liberalization of electricity markets had a significant impact on the whole process of optimal dispatch. The positive effect of competition is partly canceled out by profit-maximizing behavior of market participants. Strategic generators can exercise market power or collude tacitly with other participants to ensure higher electricity price and therefore higher profits. In this paper we study the generators' possibility to come to a tacit collusion by distributed computations. Due to the strategic nature of market interactions, the information corresponding to the power production by generating companies is often fully confidential outside the generating unit. Such information includes the data about planned and emergency outages, capacity constraints, ramping rates specific to the units, probability of failures, etc. Under certain assumptions the constraint set of a generating unit can be represented as a convex set. Using a novel multi-agent distributed constrained optimization algorithm we show how market participants with confidential constraint sets can reach the collusion on the production share, while maximizing their own profit. We compare this outcome to the outcome of Nash equilibrium over specified time horizon and conclude, if both generators find it profitable to collude. This modeling is important for early detection and prevention of tacit collusion.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2014
National Category
Energy Systems
Identifiers
urn:nbn:se:kth:diva-164505 (URN)10.1109/PESGM.2014.6939785 (DOI)000349551504112 ()2-s2.0-84930989330 (Scopus ID)978-1-4799-6415-4 (ISBN)
Conference
IEEE PES General Meeting, JUL 27-31, 2014, National Harbor, MD
Note

QC 20150417

Available from: 2015-04-17 Created: 2015-04-17 Last updated: 2017-04-05Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-4490-9278

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