基于NNC法的含电解铝系统多目标优化  

Multi-objective optimization of electrolytic aluminum system based on NNC method

作　　者：刘昕明 王海云[1] LIU Xinming;WANG Haiyun(Engineering Research Center of Education Ministry for Renewable Energy Power Generation and Grid Conmection,Collage of Electrical Engineering,Xinjiang University,Urumqi 830017,China)

机构地区：[1]新疆大学电气工程学院可再生能源发电与并网控制教育部工程研究中心,新疆乌鲁木齐830017

出　　处：《现代电子技术》2024年第14期122-128,共7页Modern Electronics Technique

基　　金：新疆维吾尔自治区重点研发计划基金项目(2022B01020-3)。

摘　　要：随着高比例可再生能源并网,电力系统运行面临调峰压力大、风电消纳难等问题。为此,基于电解铝负荷的响应容量大、调节速度快等特点,提出一种基于规格化平面约束法(NNC)的含电解铝系统多目标优化方法。首先,将需求侧具有调节特性的电解铝负荷与火电厂相结合,建立含电解铝电力系统的多目标优化模型,以系统运行总成本最小、弃风电量最小为目标函数,联合储能系统对系统进行整体优化调度;其次,采用NNC法处理多目标模型,获取均匀分布Pareto前沿解;最后,选用逼近理想解法(TOPSIS),在Pareto前沿解中得到全局最优解。算例分析结果表明,所提方法可有效提高可再生能源的消纳量,具有良好的经济性。With a high proportion of renewable energy connected to the grid,the power system faces challenges such as significant peak load pressure and difficulties in accommodating wind power.Therefore,a multi-objective optimization method for electrolysis aluminum system based on the NNC(normalized normal constraint)method is proposed based on the characterics that electrolysis aluminum has a large response capacity and fast adjustment speed.The demand-side electrolysis aluminum load with regulatory characteristics is integrated with thermal power plants to establish a multi-objective optimization model for power systems with electrolysis aluminum.The objective functions are set to minimize the total operating cost and minimize the discarded wind power,and the energy storage system is jointly optimized for the overall system scheduling.The NNC method is employed to handle the multi-objective model and obtain a uniformly distributed Pareto front solution.The technique for order preference by similarity to ideal solution(TOPSIS)is selected to obtain the globally optimal solution within the Pareto front.The case analysis results show that this method can effectively improve renewable energy integration,and has good economic performance.

关 键 词：规格化平面约束法 电解铝负荷 需求响应 多目标优化 新能源消纳 逼近理想解法 储能系统 

分 类 号：TN86-34[电子电信—信息与通信工程] TM73[电气工程—电力系统及自动化]