A decentralized stochastic bidding strategy for aggregators of prosumers in electricity reserve markets
Recent years have seen an increasing interest in demand response as a means to provide flexibility and support the penetration of renewable resources in the power system. Aggregators play a key role, in this regard, by enabling the participation of small-scale distributed energy resources and loads...
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| Veröffentlicht in: | Journal of cleaner production Jg. 389; S. 135962 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Elsevier Ltd
20.02.2023
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| ISSN: | 0959-6526, 1879-1786 |
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| Abstract | Recent years have seen an increasing interest in demand response as a means to provide flexibility and support the penetration of renewable resources in the power system. Aggregators play a key role, in this regard, by enabling the participation of small-scale distributed energy resources and loads connected at the distribution network into local and central markets.
This paper proposes an optimal strategy to support aggregators of a large number of small prosumers to participate in the tertiary reserve procurement market. In particular, a two-stage decentralized approach is proposed in which, first, prosumers individually optimize their flexible appliances schedule according to their own requirements and preferences, without sharing any information with the aggregator. At the aggregator level, a trading strategy is proposed for participation in the reserve market aiming at maximizing the aggregator’s profit under the pay-as-bid pricing scheme, while only requiring a linear programming formulation ensuring the efficiency of the trading problem. In the developed approach, a scenario-based stochastic programming method is introduced to capture the uncertainties of market prices, weather conditions, loads, and user behavior.
To demonstrate the applicability of the proposed method, using real data, simulations on 2500 small prosumers in a realistic setting are carried out. The proposed linear and decentralized method can be executed within a few minutes, enabling its applicability for aggregators with a large number of customers. |
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| AbstractList | Recent years have seen an increasing interest in demand response as a means to provide flexibility and support the penetration of renewable resources in the power system. Aggregators play a key role, in this regard, by enabling the participation of small-scale distributed energy resources and loads connected at the distribution network into local and central markets. This paper proposes an optimal strategy to support aggregators of a large number of small prosumers to participate in the tertiary reserve procurement market. In particular, a two-stage decentralized approach is proposed in which, first, prosumers individually optimize their flexible appliances schedule according to their own requirements and preferences, without sharing any information with the aggregator. At the aggregator level, a trading strategy is proposed for participation in the reserve market aiming at maximizing the aggregator’s profit under the pay-as-bid pricing scheme, while only requiring a linear programming formulation ensuring the efficiency of the trading problem. In the developed approach, a scenario-based stochastic programming method is introduced to capture the uncertainties of market prices, weather conditions, loads, and user behavior. To demonstrate the applicability of the proposed method, using real data, simulations on 2500 small prosumers in a realistic setting are carried out. The proposed linear and decentralized method can be executed within a few minutes, enabling its applicability for aggregators with a large number of customers. Recent years have seen an increasing interest in demand response as a means to provide flexibility and support the penetration of renewable resources in the power system. Aggregators play a key role, in this regard, by enabling the participation of small-scale distributed energy resources and loads connected at the distribution network into local and central markets. This paper proposes an optimal strategy to support aggregators of a large number of small prosumers to participate in the tertiary reserve procurement market. In particular, a two-stage decentralized approach is proposed in which, first, prosumers individually optimize their flexible appliances schedule according to their own requirements and preferences, without sharing any information with the aggregator. At the aggregator level, a trading strategy is proposed for participation in the reserve market aiming at maximizing the aggregator’s profit under the pay-as-bid pricing scheme, while only requiring a linear programming formulation ensuring the efficiency of the trading problem. In the developed approach, a scenario-based stochastic programming method is introduced to capture the uncertainties of market prices, weather conditions, loads, and user behavior. To demonstrate the applicability of the proposed method, using real data, simulations on 2500 small prosumers in a realistic setting are carried out. The proposed linear and decentralized method can be executed within a few minutes, enabling its applicability for aggregators with a large number of customers. |
| ArticleNumber | 135962 |
| Author | Sanjab, Anibal Manna, Carlo |
| Author_xml | – sequence: 1 givenname: Carlo orcidid: 0000-0001-8815-1628 surname: Manna fullname: Manna, Carlo email: carlo.manna@vito.be – sequence: 2 givenname: Anibal orcidid: 0000-0002-6846-9441 surname: Sanjab fullname: Sanjab, Anibal |
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| Keywords | Aggregators Flexibility Electricity markets Reserve procurement Stochastic programming |
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