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Research On Trading Strategies Of Energy Storage Use Right In The Electricity Market

Posted on:2022-09-15Degree:MasterType:Thesis
Country:ChinaCandidate:Y R XiaFull Text:PDF
GTID:2492306569473104Subject:Power system and its automation
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With the development of renewable energy,the demand of power grid for energy storage is increasing,but the high investment cost limits the large-scale application of energy storage.Shared energy storage can make full use of social capital and meet the differentiated needs of multiple types of subscribers at the same time.It has received extensive attention,but still faces many challenges.This paper introduces the concept of energy storage use right in the electricity market.The problems of basic clearing and pricing,the problems of bidding and clearing under the optimal offering and the problems of the joint clearing with the day-ahead energy market are studied to discuss the trading strategies of the energy storage use right.The main contents are as follows:(1)Discrete power capacity right and continuous energy capacity right are proposed as trading products to meet the different needs of different subscribers for energy storage.Based on the basic characteristics of the proposed trading products,combined with the physical constraints of energy storage and the bidding constraints of subscribers,the clearing model aiming at social welfare maximization is established.It ensures the physical feasibility under the condition of realizing the optimal sharing of energy storage.Based on the principle of optimality,the pricing rules of energy storage use right are designed,which can meet the optimality conditions of maximizing the market interests of each energy storage subscriber.According to the strong duality theorem and the analysis of complementary conditions,it can ensure the non-negative interest of each market participant and avoid the loss of their interests even under the worst conditions.(2)On the basis of the proposed clearing and pricing rules,this paper further considers the optimal bidding strategies of subscribers,and models the systematic trading strategies which integrate bidding,clearing and pricing as a bi-level programming problem.The upperlevel determines the bidding strategy according to the maximum profit of subscribers,and the lower-level completes the market clearing according to the maximum social welfare.Then,according to the Karush-Kuhn-Tucker optimality conditions,the lower-level problem is replaced equivalently,so that the bi-level programming problem is transformed into a single level mathematical programming problem with equilibrium constraints.To solve effectively,the original problem is transformed into a mixed integer linear programming problem by using binary expansion and Fortune-Amat transformation.Finally,case studies are given to verify the effectiveness of the proposed method under different transaction products,energy storage subscribers and energy storage parameters.(3)Based on the single transaction of the energy storage use right,this paper further analyzes the joint clearing problem between energy storage use right and the day-ahead energy market.A joint clearing strategy is proposed to solve the problem of how to obtain and use shared energy storage.In order to realize the global sharing of energy storage in the system and describe the profit seeking situation of users,the network characteristics and game behavior of energy storage right transaction are comprehensively considered.Then,according to the principle of optimality,the implicit function relationship between the two markets is established,and the clearing problem of the two markets is transformed into an equilibrium problem with equilibrium constraints.On the basis of linearization process,the meaningful equilibrium of the maximum social welfare is selected effectively.Finally,through different test systems,the effectiveness of the proposed method is verified from many aspects.
Keywords/Search Tags:shared energy storage, use right, pricing rules, bidding strategies of subscribers, joint clearing
PDF Full Text Request
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