Risk-constrained offering strategy for a hybrid power plant consisting of wind power producer and electric vehicle aggregator

Renewable energy producers such as wind power producers (WPP) and electric vehicle (EV) aggregators are playing an increasingly important role in the electricity market as their large capacity could strategically influence the electricity price. This paper proposes a bi-level stochastic optimization...

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Vydané v:	Energy (Oxford) Ročník 177; s. 183 - 191
Hlavní autori:	Gao, Xiang, Chan, Ka Wing, Xia, Shiwei, Zhou, Bin, Lu, Xi, Xu, Da
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Oxford Elsevier Ltd 15.06.2019 Elsevier BV
Predmet:	Alternative energy sources Computer simulation Constraints Electric power generation Electric vehicle Electric vehicles Electricity electricity costs Electricity pricing energy Hybrid power plant income Integer programming Linear programming Markets Mixed integer Offering strategy Optimization Power plants prices Profits profits and margins Renewable energy risk Risk management social welfare uncertainty Volatility Wind power Wind power generation Electric vehicle Renewable energy Offering strategy Hybrid power plant
ISSN:	0360-5442, 1873-6785
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Abstract	Renewable energy producers such as wind power producers (WPP) and electric vehicle (EV) aggregators are playing an increasingly important role in the electricity market as their large capacity could strategically influence the electricity price. This paper proposes a bi-level stochastic optimization model of offering strategy for an aggregated WPP-EV hybrid power plant (HPP) as a price maker in the day-ahead (DA) market while considering the uncertainties of the energy production and spot price in the real-time (RT) market. While the HPP's profits is maximized in the upper level of the proposed model with the use of conditional-value-at-risk (CVaR) to manage the risk of expected revenues, the social welfare from the perspective of the grid is maximized in the lower level. The formulated bi-level model is first transformed into a single-level mathematical program with equilibrium constraints (MPEC) and then further transformed into a mixed integer linear programming (MILP) problem for solution. Simulation results have demonstrated the effectiveness of the proposed HPP model with strategically bidding price to increase profits and reduce volatility of profits by considering the risk-metric. •EV aggregators with both V2G and G2V services and WPPs are integrated as a HPP.•A bi-level model of offering strategy for a HPP in the DA market is proposed.•Renewable energy production and real market prices are considered as uncertainties.•EVs and elastic loads as DR sources are price makers and price takers respectively.
AbstractList	Renewable energy producers such as wind power producers (WPP) and electric vehicle (EV) aggregators are playing an increasingly important role in the electricity market as their large capacity could strategically influence the electricity price. This paper proposes a bi-level stochastic optimization model of offering strategy for an aggregated WPP-EV hybrid power plant (HPP) as a price maker in the day-ahead (DA) market while considering the uncertainties of the energy production and spot price in the real-time (RT) market. While the HPP's profits is maximized in the upper level of the proposed model with the use of conditional-value-at-risk (CVaR) to manage the risk of expected revenues, the social welfare from the perspective of the grid is maximized in the lower level. The formulated bi-level model is first transformed into a single-level mathematical program with equilibrium constraints (MPEC) and then further transformed into a mixed integer linear programming (MILP) problem for solution. Simulation results have demonstrated the effectiveness of the proposed HPP model with strategically bidding price to increase profits and reduce volatility of profits by considering the risk-metric. Renewable energy producers such as wind power producers (WPP) and electric vehicle (EV) aggregators are playing an increasingly important role in the electricity market as their large capacity could strategically influence the electricity price. This paper proposes a bi-level stochastic optimization model of offering strategy for an aggregated WPP-EV hybrid power plant (HPP) as a price maker in the day-ahead (DA) market while considering the uncertainties of the energy production and spot price in the real-time (RT) market. While the HPP's profits is maximized in the upper level of the proposed model with the use of conditional-value-at-risk (CVaR) to manage the risk of expected revenues, the social welfare from the perspective of the grid is maximized in the lower level. The formulated bi-level model is first transformed into a single-level mathematical program with equilibrium constraints (MPEC) and then further transformed into a mixed integer linear programming (MILP) problem for solution. Simulation results have demonstrated the effectiveness of the proposed HPP model with strategically bidding price to increase profits and reduce volatility of profits by considering the risk-metric. •EV aggregators with both V2G and G2V services and WPPs are integrated as a HPP.•A bi-level model of offering strategy for a HPP in the DA market is proposed.•Renewable energy production and real market prices are considered as uncertainties.•EVs and elastic loads as DR sources are price makers and price takers respectively.
Author	Zhou, Bin Xia, Shiwei Xu, Da Lu, Xi Gao, Xiang Chan, Ka Wing
Author_xml	– sequence: 1 givenname: Xiang surname: Gao fullname: Gao, Xiang organization: Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong – sequence: 2 givenname: Ka Wing orcidid: 0000-0001-7462-0753 surname: Chan fullname: Chan, Ka Wing email: eekwchan@polyu.edu.hk organization: Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong – sequence: 3 givenname: Shiwei orcidid: 0000-0003-1272-210X surname: Xia fullname: Xia, Shiwei organization: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, 102206, China – sequence: 4 givenname: Bin orcidid: 0000-0002-1376-4531 surname: Zhou fullname: Zhou, Bin email: binzhou@hnu.edu.cn organization: Hunan Key Laboratory of Intelligent Information Analysis and Integrated Optimization for Energy Internet, Hunan University, Changsha, 410082, China – sequence: 5 givenname: Xi orcidid: 0000-0003-3297-5198 surname: Lu fullname: Lu, Xi organization: Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong – sequence: 6 givenname: Da surname: Xu fullname: Xu, Da organization: Hunan Key Laboratory of Intelligent Information Analysis and Integrated Optimization for Energy Internet, Hunan University, Changsha, 410082, China
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Snippet	Renewable energy producers such as wind power producers (WPP) and electric vehicle (EV) aggregators are playing an increasingly important role in the...
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SubjectTerms	Alternative energy sources Computer simulation Constraints Electric power generation Electric vehicle Electric vehicles Electricity electricity costs Electricity pricing energy Hybrid power plant income Integer programming Linear programming Markets Mixed integer Offering strategy Optimization Power plants prices Profits profits and margins Renewable energy risk Risk management social welfare uncertainty Volatility Wind power Wind power generation
Title	Risk-constrained offering strategy for a hybrid power plant consisting of wind power producer and electric vehicle aggregator
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