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Smart Grid  2023 

高比例新能源背景下跨境新型电力系统多主体激励交易模型
Multi-Agent Incentive Trading Model of Cross-Border New Power System under the Background of High Proportion of New Energy

DOI: 10.12677/SG.2023.134007, PP. 71-81

Keywords: 跨境交易,电力市场,新能源消纳,粒子群算法
Cross-Border Trading
, Electricity Market, New Energy Consumption, Particle Swarm Optimization

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Abstract:

随着新能源发电技术在全球范围内的高速发展,各国电网新能源消纳压力日益凸显,利用跨境输电网络进行新能源跨境交易是提高新能源利用率的有效途径。为充分调配国家间的盈余新能源电力,本文提出了一种跨境新型电力系统多国家主体激励交易模型。本文首先考虑各国境内电力市场的出清结果及境内机组的调节能力以获得各国的跨境购售电力需求,其次,在多方共赢的约束下搭建以跨境各国总收益最大为目标的优化模型以获得最优跨境新能源交易决策,并采用粒子群算法对模型进行求解。最后,通过欧洲某跨境市场算例验证了盈余新能源跨境激励交易模型的有效性。
With the rapid development of new energy power generation technology in the world, the new en-ergy consumption pressure of national power grids has become increasingly prominent, and the use of cross-border transmission networks to carry out cross-border transactions of new energy is an effective way to improve the utilization rate of new energy. In order to fully allocate the surplus new energy power between countries, this paper proposes a new cross-border power system multi- na-tional incentive trading model. This paper first considers the clearing results of domestic electricity markets and the adjustment capacity of domestic units in order to obtain the cross-border purchase and sale of electricity demand of various countries. Secondly, under the constraint of multi-party win-win, an optimization model with the goal of maximizing the total revenue of cross- border countries is built to obtain the optimal cross-border new energy trading decision, and particle swarm optimization algorithm is adopted to solve the model. Finally, the validity of the surplus new energy cross-border incentive trading model is verified by a European cross-border market exam-ple.

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