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Shinde, P., Gamberi, G. & Amelin, M. (2023). A Multi-agent Model for Cross-border Trading in the Continuous Intraday Electricity Market. Energy Reports, 9, 6227-6240
Open this publication in new window or tab >>A Multi-agent Model for Cross-border Trading in the Continuous Intraday Electricity Market
2023 (English)In: Energy Reports, E-ISSN 2352-4847, Vol. 9, p. 6227-6240Article in journal (Refereed) Published
Abstract [en]

The increasing importance of cross-border trade has brought the topic of allocating cross-border transmission capacity under the limelight. In this paper, we focus on two different transmission capacity calculation methods, namely, Available Transfer Capacity and Flow-based Capacity allocation, in the continuous intraday electricity market. The effect of these two methods is studied on the continuous intraday electricity market through an agent-based model comprising various types of trading agents. It also models market operator agent and transmission system operator agent inspired by the Single Intraday Coupling project in Europe. The price-volume decisions for the orders posted by the market participants are determined by two different strategies where one of them adapts to changing market conditions and new information while the other is naive. The model accounts for ramping constraints which enables the analysis of the trading behavior and interaction of agents across multiple delivery products simultaneously. A switch parameter is availed in the trading timeline for the thermal and storage agents to change from a less conservative approach of ignoring the ramping and charging/discharging rate constraints respectively to considering them. An interplay between different switch parameters and cross-border transmission capacity calculation methods is studied.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
Continuous intraday electricity market, Cross-border intraday trading, Flow-based market coupling, Agent-based model
National Category
Energy Systems
Identifiers
urn:nbn:se:kth:diva-331186 (URN)10.1016/j.egyr.2023.05.070 (DOI)001013791000001 ()2-s2.0-85161019287 (Scopus ID)
Note

Not duplicate with DiVA 1690946

QC 20230706

Available from: 2023-07-06 Created: 2023-07-06 Last updated: 2023-07-06Bibliographically approved
Skalyga, M., Amelin, M., Wu, Q. & Söder, L. (2023). Distributionally robust day-ahead combined heat and power plants scheduling with Wasserstein Metric. Energy, 269, Article ID 126793.
Open this publication in new window or tab >>Distributionally robust day-ahead combined heat and power plants scheduling with Wasserstein Metric
2023 (English)In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 269, article id 126793Article in journal (Refereed) Published
Abstract [en]

Combined heat and power (CHP) plants are main generation units in district heating systems that produce both heat and electric power simultaneously. Moreover, CHP plants can participate in electricity markets, selling and buying the extra power when profitable. However, operational decisions have to be made with unknown electricity prices. The distribution of unknown electricity prices is also not known exactly and uncertain in practice. Therefore, the need of tools to schedule CHP units' production under distributional uncertainty is necessary for CHP producers. On top of that, a heating network could serve as a heat storage and an additional source of flexibility for CHP plants. In this paper, a distributionally robust short-term operational model of CHP plants in the day-ahead electricity market is developed. The model accounts for the heating network and considers temperature dynamics in the pipes. The problem is formulated in a data-driven manner, where the production decisions explicitly depend on the historical data for the uncertain day-ahead electricity prices. A case study is performed, and the resulting profit of the CHP producer is analyzed. The proposed operational strategy shows high reliability in the out-of-sample performance and a profit gain of the CHP producer, who is aware of the temperature dynamics in the heating network.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
Stochastic programming, Combined heat and power, District heating, Distributionally robust optimization, Electricity markets
National Category
Energy Systems
Identifiers
urn:nbn:se:kth:diva-326451 (URN)10.1016/j.energy.2023.126793 (DOI)000963159700001 ()2-s2.0-85147214520 (Scopus ID)
Note

QC 20230503

Available from: 2023-05-03 Created: 2023-05-03 Last updated: 2023-05-03Bibliographically approved
Dires, F. G., Amelin, M. & Bekele, G. (2023). Inflow Scenario Generation for the Ethiopian Hydropower System. Water, 15(3), Article ID 500.
Open this publication in new window or tab >>Inflow Scenario Generation for the Ethiopian Hydropower System
2023 (English)In: Water, E-ISSN 2073-4441, Vol. 15, no 3, article id 500Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
MDPI AG, 2023
Keywords
inflow scenarios, synthetic historical inflow series, time series analysis, stochastic process, scenario generation, hydropower, planning model
National Category
Water Engineering
Identifiers
urn:nbn:se:kth:diva-324709 (URN)10.3390/w15030500 (DOI)000929743300001 ()2-s2.0-85147799931 (Scopus ID)
Note

QC 20230314

Available from: 2023-03-14 Created: 2023-03-14 Last updated: 2023-08-28Bibliographically approved
Dires, F. G., Amelin, M. & Bekele, G. (2023). Long-Term Hydropower Planning for Ethiopia: A Rolling Horizon Stochastic Programming Approach with Uncertain Inflow. Energies, 16(21), Article ID 7399.
Open this publication in new window or tab >>Long-Term Hydropower Planning for Ethiopia: A Rolling Horizon Stochastic Programming Approach with Uncertain Inflow
2023 (English)In: Energies, E-ISSN 1996-1073, Vol. 16, no 21, article id 7399Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
MDPI AG, 2023
Keywords
hydropower, planning model, risk-averse model, rolling horizon, stochastic model, uncertain inflow
National Category
Economics
Identifiers
urn:nbn:se:kth:diva-340111 (URN)10.3390/en16217399 (DOI)001100379800001 ()2-s2.0-85176420233 (Scopus ID)
Note

QC 20231128

Available from: 2023-11-28 Created: 2023-11-28 Last updated: 2024-02-29Bibliographically approved
Shinde, P., Kouveliotis Lysikatos, I., Amelin, M. & Song, M. (2022). A Modified Progressive Hedging Approach for Multistage Intraday Trade of EV Aggregators. In: : . Paper presented at Power Systems Computation Conference 2022, Porto, Portugal from 27th of June to the 1st of July 2022. Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>A Modified Progressive Hedging Approach for Multistage Intraday Trade of EV Aggregators
2022 (English)Conference paper, Published paper (Refereed)
Abstract [en]

The growing prominence of electric vehicle (EV) aggregators in the modern power system is drawing more attention towards modeling their behavior in the short-term electricity markets. The demand-side flexibility offered by the EVs can be leveraged to reduce their charging costs. In this paper, the participation of an EV aggregator in the intraday and balancing market is modeled as a multistage stochastic programming problem. The computational complexity introduced by the peculiarities of the intraday market is solved by a  progressive hedging algorithm (PHA), a scenario-based decomposition technique. A randomized scenario sampling approach is implemented to accelerate the PHA which is further improved with a parallel randomized PHA. Finally, an asynchronous version of the parallel randomized PHA is leveraged to speed up the multistage model of EV aggregator trading. We compare the computation time of the modified versions of the PHA algorithm with the conventional PHA for the proposed EV aggregator model. Furthermore, we also show the value of EV aggregator trading in the intraday and balancing markets by comparing its cost to baseline models. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022
Keywords
Intraday electricity market, randomized progressive hedging, multistage stochastic programming
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-313292 (URN)
Conference
Power Systems Computation Conference 2022, Porto, Portugal from 27th of June to the 1st of July 2022
Funder
Swedish Energy Agency
Note

QC 20220629

Available from: 2022-06-02 Created: 2022-06-02 Last updated: 2022-06-29Bibliographically approved
Shinde, P., Kouveliotis Lysikatos, I., Amelin, M. & Song, M. (2022). A Modified Progressive Hedging Approach for Multistage Intraday Trade of EV aggregators. Electric power systems research, 212, Article ID 108518.
Open this publication in new window or tab >>A Modified Progressive Hedging Approach for Multistage Intraday Trade of EV aggregators
2022 (English)In: Electric power systems research, ISSN 0378-7796, E-ISSN 1873-2046, Vol. 212, article id 108518Article in journal (Refereed) Published
Abstract [en]

The growing prominence of electric vehicle (EV) aggregators in the modern power system is drawing more attention towards modeling their behavior in the short-term electricity markets. The demand-side flexibility offered by the EVs can be leveraged to reduce their charging costs. In this paper, the participation of an EV aggregator in the intraday and balancing market is modeled as a multistage stochastic programming problem. The computational complexity introduced by the peculiarities of the intraday market is solved by a progressive hedging algorithm (PHA), a scenario-based decomposition technique. A randomized scenario sampling approach is implemented to accelerate the PHA which is further improved with a parallel randomized PHA. Finally, an asynchronous version of the parallel randomized PHA is leveraged to speed up the multistage model of EV aggregator trading. We compare the computation time of the modified versions of the PHA algorithm with the conventional PHA for the proposed EV aggregator model. Furthermore, we also show the value of EV aggregator trading in the intraday and balancing markets by comparing its cost to baseline models.

Place, publisher, year, edition, pages
Elsevier BV, 2022
Keywords
Intraday electricity market, Randomized progressive hedging, Multistage stochastic programming
National Category
Work Sciences
Identifiers
urn:nbn:se:kth:diva-320301 (URN)10.1016/j.epsr.2022.108518 (DOI)000856623900030 ()2-s2.0-85134810085 (Scopus ID)
Note

QC 20221024

Available from: 2022-10-24 Created: 2022-10-24 Last updated: 2022-12-23Bibliographically approved
Shinde, P., Gamberi, G. & Amelin, M. (2022). A Multi-Agent Model for Cross-Border Trading in the Continuous Intraday Electricity Market.
Open this publication in new window or tab >>A Multi-Agent Model for Cross-Border Trading in the Continuous Intraday Electricity Market
2022 (English)In: Article in journal (Other academic) Submitted
Abstract [en]

The increasing importance of cross-border trade has brought the topic of allocating cross-border transmission capacity under the limelight. In this paper, we focus on two different transmission capacity calculation methods, namely, Available Transfer Capacity and Flow-based Capacity allocation, in the continuous intraday electricity market. The effect of these two methods is studied on the continuous intraday electricity market through an agent-based model. The model comprises market participants, including renewable producers, consumers, storage, and thermal power producers. The market operator agent is responsible for managing the shared order book and clearing orders while the transmission system operator agent calculates and updates the cross-border transmission capacities in the continuous intraday electricity market. The price-volume decisions for the orders posted by the market participants are determined by two different strategies where one of them adapts to changing market conditions and new information while the other is naive. The model accounts for ramping constraints which enables the analysis of the trading behavior and interaction of agents across multiple delivery products simultaneously. A switch parameter is availed in the trading timeline for the thermal and storage agents to change from a less conservative approach of ignoring the ramping and charging/discharging rate constraints respectively to considering them. An interplay between different switch parameters and cross-border transmission capacity calculation methods is studied.

Place, publisher, year, edition, pages
Elsevier, 2022
Keywords
Continuous intraday electricity market, cross-border intraday trading, flow-based market coupling, agent-based model
National Category
Engineering and Technology
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-316678 (URN)
Note

QC 20220830

Preprint, submitted to Journal of Applied Energy

Available from: 2022-08-28 Created: 2022-08-28 Last updated: 2022-12-23Bibliographically approved
Shinde, P., Bharambe, N. & Amelin, M. (2022). Agent-Based Model to Simulate Multiple Delivery Products in Continuous Intraday Electricity Market. In: Proceedings IEEE Power and Energy Society General Meeting 2022: . Paper presented at IEEE Power and Energy Society General Meeting 2022, 17-21 July 2022, Denver, Colorado. IEEE Computer Society
Open this publication in new window or tab >>Agent-Based Model to Simulate Multiple Delivery Products in Continuous Intraday Electricity Market
2022 (English)In: Proceedings IEEE Power and Energy Society General Meeting 2022, IEEE Computer Society , 2022Conference paper, Published paper (Refereed)
Abstract [en]

The increasing variable renewable energy sourcesin the power system have led to rise in the trading volumesin the electricity markets. In this paper, we extend an existingopen source agent-based model for simulating the behavior andinteractions of the renewable, consumer, thermal, and marketoperator agents in the continuous intraday (CID) electricitymarket by introducing the energy storage agents. Furthermore,the limitation of the earlier model to account for the CID tradeof a single delivery product is relaxed by extending the modelto consider the simultaneous trading of all the possible deliveryproducts in a day. A realistic trading behavior is enabled byan user-defined parameter for the thermal and storage agentsto choose the switching point in the trading timeline when thestrategy of the trading agent navigates from increasing theirprofits by trading in the CID market to avoiding any imbalancesby considering their physical constraints. Comparative casestudies are performed to demonstrate the evolution of the tradingbehavior of the agents throughout the trading horizons formultiple delivery products with different switching instances.

Place, publisher, year, edition, pages
IEEE Computer Society, 2022
Keywords
Agent-based modeling, Continuous Intraday Electricity market, Energy storage
National Category
Energy Systems
Identifiers
urn:nbn:se:kth:diva-311458 (URN)2-s2.0-85141482568 (Scopus ID)
Conference
IEEE Power and Energy Society General Meeting 2022, 17-21 July 2022, Denver, Colorado
Note

QC 20220428

Available from: 2022-04-28 Created: 2022-04-28 Last updated: 2023-06-14Bibliographically approved
Shinde, P., Kouveliotis Lysikatos, I. & Amelin, M. (2022). Cross-border Trading Model for a Risk-averse VPP in the Continuous Intraday Electricity Market. In: : . Paper presented at 18th European Energy Market Conference, Ljubljana, Slovenia, 13-15 September 2022. Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Cross-border Trading Model for a Risk-averse VPP in the Continuous Intraday Electricity Market
2022 (English)Conference paper, Published paper (Refereed)
Abstract [en]

The surge in intermittent renewable energy sources has led to larger volumes traded in the short-term electricity markets. As a result, the problem of optimally trading in the cross-border continuous intraday (CID) electricity market has come under the limelight. In this paper, we propose a multistage stochastic programming model to determine the participation of a virtual power plant (VPP), comprising wind power, hydropower, and thermal power portfolio, in a cross-border CID market. The VPP determines the order volumes to be submitted at the market price by assessing the available orders in other bidding areas. We also present an order clearing model that accounts for the cross-border transmission capacities along with the liquidity in the CID market. The risk-averse behavior of the VPP is captured by the nested conditional value at risk (CVaR) formulation. In order to demonstrate the functionality of the proposed model, several case studies are performed by constructing data models based on historical trading data obtained from the Nord Pool.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022
Keywords
cross-border continuous intraday electricity market, multistage stochastic programming, virtual power plants, risk-averse
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-316677 (URN)10.1109/EEM54602.2022.9921175 (DOI)2-s2.0-85141158234 (Scopus ID)
Conference
18th European Energy Market Conference, Ljubljana, Slovenia, 13-15 September 2022
Funder
Swedish Energy Agency
Note

QC 20220830

Available from: 2022-08-27 Created: 2022-08-27 Last updated: 2023-06-13Bibliographically approved
Khodadadi, A., Söder, L. & Amelin, M. (2022). Flexible Stochastic Bilevel Scheduling Strategy in Hydropower Dominated Energy Markets. In: Proceedings of the 11th International Conference on Innovative Smart Grid Technologies - Asia, ISGT-Asia 2022: . Paper presented at 11th International Conference on Innovative Smart Grid Technologies - Asia, ISGT-Asia 2022, Singapore, Singapore, Nov 1 2022 - Nov 5 2022 (pp. 245-249). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Flexible Stochastic Bilevel Scheduling Strategy in Hydropower Dominated Energy Markets
2022 (English)In: 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, Published 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.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022
Keywords
Bilevel optimization, Hydropower, Nordic electricity market, Optimal planning and operation
National Category
Energy Systems
Identifiers
urn:nbn:se:kth:diva-333442 (URN)10.1109/ISGTAsia54193.2022.10003497 (DOI)2-s2.0-85146849532 (Scopus ID)
Conference
11th International Conference on Innovative Smart Grid Technologies - Asia, ISGT-Asia 2022, Singapore, Singapore, Nov 1 2022 - Nov 5 2022
Note

Part of ISBN 9798350399660

QC 20230802

Available from: 2023-08-02 Created: 2023-08-02 Last updated: 2023-08-02Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0001-6000-9363

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