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Research On Modeling And Optimization Of Day-ahead Electricity Transaction Among Regional Commercial Buildings In Electricity Market

Posted on:2021-04-02Degree:MasterType:Thesis
Country:ChinaCandidate:Z Y ZhangFull Text:PDF
GTID:2392330611466475Subject:Power system and its automation
Abstract/Summary:PDF Full Text Request
With the development of power market,distributed controlled resources,such as photovoltaic,energy storage and gas turbine,have developed rapidly,and more and more distributed power generation equipment has been applied to commercial buildings.Therefore,commercial buildings have the potential to generate power,and it is possible for regional commercial buildings to make up their own power demand through power trading,such as centralized power trading and decentralized power trading.Aiming at the problem of centralized power trading in regional commercial buildings,this paper develops an optimization model of power trading in regional commercial buildings based on the electric retailer.The model is divided into two layers,namely,electric retailer in the upper layer and commercial buildings in the lower layer.Under the constraints of power balance and costs of commercial buildings,the electric retailer can maximize its own benefit by publishing time-of-use pricing strategies and gathering corresponding power consumption information of commercial buildings.Commercial buildings make their own day-ahead power consumption strategies according to the time-of-use electricity price issued by the electric retailer,so as to minimize the operating cost.At the same time,in order to satisfy the privacy requirements between the electric retailer and commercial buildings,this paper also proposes a hybrid optimization algorithm based on ensemble learning and simplex method.It was verified by example results that this algorithm can reduce the operating costs of commercial buildings and improve the interest of the electric retailer.Aiming at the problem of decentralized power trading in regional commercial buildings,this paper develops a distributed power trading model for regional commercial buildings.In this model,each commercial building can not only meet its energy demand by dispatching its own distributed equipment and interacting with the distribution network,but also further reduce its operating cost by trading power with other commercial buildings nearby.Because these commercial buildings all expect to maximize benefits through the power transaction,and the optimization goals conflict with each other.Therefore,this paper employs Nash bargaining theory to design incentive mechanism to promote the power trade.Meanwhile,in order to meet the privacy requirements among commercial buildings,the distributed optimization method based on alternating direction method of multipliers was employed to solve the problem.Finally,the effectiveness of the method to reduce the operating costs of commercial buildings was verified by the simulation results.Meanwhile,in order to satisfy the demand of information interaction in the electric energy transaction of commercial buildings,this paper develops the user interaction system of commercial buildings to provide support for the electric energy transaction to a certain extent.
Keywords/Search Tags:Commercial building, Electric retailer, Ensemble learning, Centralized power trading, Decentralized power trading, Interactive system
PDF Full Text Request
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