基于需求响应的新能源电网短期负荷优化调度

Short-Term Load Optimization Scheduling of New Energy Grid Based on Demand Response

中文关键词:需求响应  新能源电网  短期负荷  负荷预测  优化调度

keywords:demand response  new energy power grid  short-term load  load prediction  optimal scheduling

中文摘要:针对新能源大规模并网背景下因用户行为的不确定性对短期负荷优化调度构成挑战，从而影响电网综合效益的问题，提出一种基于需求响应的新能源电网短期负荷优化调度策略。首先，分析电力需求侧的需求响应任务，并依据不同任务下的负荷特性构建数学模型，以精准界定响应负荷；其次，利用深度学习技术精准地预测短期负荷变化，并结合响应负荷特性设计优化调度目标函数；最后，通过实验结果验证了所提方法不仅预测负荷的误差小，而且优化调度的效果显著。所提方法能有效降低负荷曲线的波动性，提升新能源电网的用电经济性与调度效率，为新能源并网环境下的负荷管理提供了新思路。

Abstract:In the context of large-scale grid connection of new energy，the uncertainty of user behavior brings challenges to short-term load optimal scheduling，thereby affecting the comprehensive benefits of the power grid. To address this problem，a short-term load optimal scheduling strategy for new energy power grids based on demand response is proposed. Firstly，the demand response tasks on the power demand side are analyzed，and a mathematical model is constructed according to the load characteristics under different tasks to accurately define the responsive load. Secondly，deep learning technology is used to accurately predict short-term load changes，and an optimal scheduling objective function is designed in combination with the characteristics of responsive load. Finally，experimental results verify that the proposed method not only has small load prediction error，but also has significant optimal scheduling effect.The proposed method can effectively reduce the fluctuation of the load curve，improve the economic efficiency and scheduling efficiency of the new energy power grid，and provide a new idea for load management under large-scale new energy integration.