A bottom-up approach for demand response aggregators’ participation in electricity markets

•This paper proposes a bottom-up DR approach for DR aggregators.•The proposed DR model considers technical constraints of customers.•The proposed DR model considers the uncertainty of customers.•A stochastic problem is formulated for trading DR in various markets.•The results indicate the usefulness...

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Veröffentlicht in:Electric power systems research 2017-02, Vol.143, p.121-129
Hauptverfasser: Mahmoudi, Nadali, Heydarian-Forushani, Ehsan, Shafie-khah, Miadreza, Saha, Tapan K., Golshan, M.E.H., Siano, Pierluigi
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container_end_page 129
container_issue
container_start_page 121
container_title Electric power systems research
container_volume 143
creator Mahmoudi, Nadali
Heydarian-Forushani, Ehsan
Shafie-khah, Miadreza
Saha, Tapan K.
Golshan, M.E.H.
Siano, Pierluigi
description •This paper proposes a bottom-up DR approach for DR aggregators.•The proposed DR model considers technical constraints of customers.•The proposed DR model considers the uncertainty of customers.•A stochastic problem is formulated for trading DR in various markets.•The results indicate the usefulness and significance of the proposed bottom-up DR. This paper proposes a bottom-up model for demand response (DR) aggregators in electricity markets. This model enables a DR aggregator to consider the technical constraints of customers in developing an optimal trading strategy in the wholesale electricity market. In the bottom level, DR options, called load shifting, load curtailment and load recovery are comprehensively modelled in a stochastic programming approach. Each DR program is mathematically formulated in such a way that practically models the constraints of customers. Further, the proposed model considers the customers’ behaviour in participating in the given DR program through a scenario-based participation factor. On the other hand, the upper level proposes trading the DR outcome in day-ahead and balancing markets with uncertain prices, as well as in forward contracts with a predefined price. The overall bottom-up problem is formulated as a stochastic profit maximization model for the DR aggregator, in which the risk is taken into account using the Conditional Value-at-Risk (CVaR) measure. The feasibility of the given strategy is assessed on a case of the Nordic market.
doi_str_mv 10.1016/j.epsr.2016.08.038
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This paper proposes a bottom-up model for demand response (DR) aggregators in electricity markets. This model enables a DR aggregator to consider the technical constraints of customers in developing an optimal trading strategy in the wholesale electricity market. In the bottom level, DR options, called load shifting, load curtailment and load recovery are comprehensively modelled in a stochastic programming approach. Each DR program is mathematically formulated in such a way that practically models the constraints of customers. Further, the proposed model considers the customers’ behaviour in participating in the given DR program through a scenario-based participation factor. On the other hand, the upper level proposes trading the DR outcome in day-ahead and balancing markets with uncertain prices, as well as in forward contracts with a predefined price. The overall bottom-up problem is formulated as a stochastic profit maximization model for the DR aggregator, in which the risk is taken into account using the Conditional Value-at-Risk (CVaR) measure. The feasibility of the given strategy is assessed on a case of the Nordic market.</description><identifier>ISSN: 0378-7796</identifier><identifier>EISSN: 1873-2046</identifier><identifier>DOI: 10.1016/j.epsr.2016.08.038</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Bottom-up DR model ; Constraint modelling ; Consumer behavior ; Customer-driven DR ; Customers ; Customers’ behaviour ; DR aggregator ; Economic conditions ; Electrical loads ; Electricity ; Electricity consumption ; Electricity markets ; Feasibility studies ; Markets ; Mathematical models ; Optimization ; Power supply ; Pricing ; Stochastic models ; Stochastic programming</subject><ispartof>Electric power systems research, 2017-02, Vol.143, p.121-129</ispartof><rights>2016 Elsevier B.V.</rights><rights>Copyright Elsevier Science Ltd. 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This paper proposes a bottom-up model for demand response (DR) aggregators in electricity markets. This model enables a DR aggregator to consider the technical constraints of customers in developing an optimal trading strategy in the wholesale electricity market. In the bottom level, DR options, called load shifting, load curtailment and load recovery are comprehensively modelled in a stochastic programming approach. Each DR program is mathematically formulated in such a way that practically models the constraints of customers. Further, the proposed model considers the customers’ behaviour in participating in the given DR program through a scenario-based participation factor. On the other hand, the upper level proposes trading the DR outcome in day-ahead and balancing markets with uncertain prices, as well as in forward contracts with a predefined price. The overall bottom-up problem is formulated as a stochastic profit maximization model for the DR aggregator, in which the risk is taken into account using the Conditional Value-at-Risk (CVaR) measure. 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This paper proposes a bottom-up model for demand response (DR) aggregators in electricity markets. This model enables a DR aggregator to consider the technical constraints of customers in developing an optimal trading strategy in the wholesale electricity market. In the bottom level, DR options, called load shifting, load curtailment and load recovery are comprehensively modelled in a stochastic programming approach. Each DR program is mathematically formulated in such a way that practically models the constraints of customers. Further, the proposed model considers the customers’ behaviour in participating in the given DR program through a scenario-based participation factor. On the other hand, the upper level proposes trading the DR outcome in day-ahead and balancing markets with uncertain prices, as well as in forward contracts with a predefined price. 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subjects Bottom-up DR model
Constraint modelling
Consumer behavior
Customer-driven DR
Customers
Customers’ behaviour
DR aggregator
Economic conditions
Electrical loads
Electricity
Electricity consumption
Electricity markets
Feasibility studies
Markets
Mathematical models
Optimization
Power supply
Pricing
Stochastic models
Stochastic programming
title A bottom-up approach for demand response aggregators’ participation in electricity markets
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