基于优惠信息引导用户侧参与的购售电互动优化决策模型  

Optimization decision model for electricity purchase and sales interaction based on preferential information guiding user side participation

作　　者：丁胜 肖楚鹏 邵雪松 周超 李文庆 DING Sheng;XIAO Chupeng;SHAO Xuesong;ZHOU Chao;LI Wenqing(NARI Group Corporation(State Grid Electric Power Research Institute),Nanjing 210000,China;Wuhan Energy Effieiency Evaluation Company,State Grid Electric Power Science Research Institute Wuhan 430074,China;Marketing Service Center,State Grid Jiangsu Electric Power Co.,Ltd.,Nanjing 210019,China)

机构地区：[1]南瑞集团有限公司国网电力科学研究院有限公司,南京210000 [2]国网电力科学研究院武汉能效测评有限公司,武汉430074 [3]国网江苏省电力有限公司营销服务中心,南京210019

出　　处：《电力需求侧管理》2024年第4期68-73,共6页Power Demand Side Management

基　　金：国家电网有限公司科技项目(5400-202118391A-0-0-00)。

摘　　要：现有的需求侧参与柔性互动的引导方法未充分考虑优惠信息等社会信息对用户用电负荷的影响,其引导机制实际作用与期望结果偏差较大。针对这一问题,采用Attention-LSTM模型预测多种社会因素作用下用户用电负荷调整量,为引导方法所需的用户负荷调整量提供依据。以分时电价和优惠券套餐作为优惠信息为例,提出考虑社会因素影响的优惠信息引导方法,引导用户合理用电,从而减少售电商购电成本。在此基础上,基于售电商多级市场购电模型,考虑优惠信息影响建立了以售电商收益最大化为目标的售电商多级市场购售电优化决策模型,来验证所提引导方法的可行性和有效性。采用粒子群算法和CPLEX求解,获得最优引导策略与售电商购电策略。基于澳大利亚数据的算例分析表明,所提基于优惠信息引导用户用电的售电商购售电优化决策模型能够有效引导用户主动参与互动。Existing guidance method of demand-side participating in flexible interaction do not fully consider the influence of social infor-mation such as preferential information on load,resulting in a large deviation between the actual role of the guiding cues and the expected results.In view of such situation,the Attention-LSTM model is used to forecast the load adjustment under the effect of social information,such as guiding cues.Coupon guidance method could be determined with this model.Take time of use tariff and coupon as an example,coupon guidance method considering the influence of preferential information is proposed,to guide consumers to change their electricity consumption behaviors for less cost of purchasing electricity.And on this basis,a decision-making model of purchase-sale strategy consid-ering the influence of preferential information in multi-level electricity market is established,to maximize the revenue of electricity retail-ers and verify the feasibility and effectiveness of the proposed guidance method,which is solved by particle swarm optimization algorithm and CPLEX,to obtain the optimal guidance strategy and purchase strategy of electricity retailers.An example based on Australian data shows that the electricity purchasing and selling optimization model of electricity ratailers base on coupons guiding can effectively guide customers to actively participate in the interaction.

关 键 词：引导信息 优惠券引导策略 柔性互动 优惠信息 

分 类 号：F426.61[经济管理—产业经济] TM73[电气工程—电力系统及自动化]