Non-Cooperative Game in Block Bidding Markets Considering Demand Response
Autor: | Gangfeng Yan, Jian Hou, Ningxuan Guo, Yinan Wang |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
Non-cooperative game
Supply Control and Optimization Optimization problem Renewable Energy Sustainability and the Environment Computer science lcsh:T Stochastic game block bidding market Energy Engineering and Power Technology distributed iteration Bidding lcsh:Technology Profit (economics) Microeconomics Demand response demand response non-cooperative game supply function Electrical and Electronic Engineering Engineering (miscellaneous) Demand load Energy (miscellaneous) |
Zdroj: | Energies; Volume 13; Issue 13; Pages: 3322 Energies, Vol 13, Iss 3322, p 3322 (2020) |
ISSN: | 1996-1073 |
DOI: | 10.3390/en13133322 |
Popis: | With the reform of electricity markets, demand response (DR) plays an important role in providing flexibility to the markets. Block bidding market is a new market mode, which is based on the concept of “the same quality, the same price”. The mechanism has great effects in reducing start-stop related costs. In this paper, we propose a double-sided non-cooperative game model in block bidding markets with a DR program. The model combines the advantages of block bidding and the simplicity of hourly bidding. In the model, one side is the non-cooperative game of supply-side power firms, and we propose a novel supply function bidding model based on block duration and load capacity to maximize each firm’s profit. The other side is the demand-side different types of customers, and we propose a DR model that combines hourly-various prices with the block bidding mechanism to maximize each customer’s payoff. The overall market optimization problem is solved by a distributed iterative algorithm, which has great convergence performance. We verify the proposed model on real data, and the results show that the demand load curve becomes flattened with DR, and the total generation costs decrease while the social welfare is significantly improved. |
Databáze: | OpenAIRE |
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