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作 者:王宝石 吕东声 王铎 WANG Baoshi;LÜDongsheng;WANG Duo(College of Electric Power,Shenyang Institute of Engineering,Shenyang,Liaoning 110136,China;Electric Power Dispatching and Control Center of State Grid Liaoning Electric Power Co.,Ltd.,Shenyang,Liaoning 110006,China)
机构地区:[1]沈阳工程学院电力学院,辽宁沈阳110136 [2]国网辽宁省电力有限公司电力调度控制中心,辽宁沈阳110006
出 处:《东北电力技术》2024年第5期6-11,15,共7页Northeast Electric Power Technology
摘 要:随着能源互联网建设的推进,多种能源间灵活互动,用能需求不断多元化,可再生能源消纳比例越来越高,导致能源供需系统的不稳定性增强,系统平衡难度增加。为满足多元化用能需求和实现高比例可再生能源的消纳,提出计及不确定性的新能源小镇灵活性资源容量双层优化配置方法。结合采用比例选择法生成源荷双侧的联合概率乘积的场景,利用削减技术选取最大概率的场景作为典型日基础数据输入,规划层以年投资、运维成本最低为目标,规划地源热泵、储能和储热等灵活性资源的容量;运行层以燃料、运行维护、弃光惩罚成本最低为目标,采用遗传算法求解建立在典型场景下的灵活性资源优化配置方案。通过北方某新能源小镇的仿真,验证该方法的有效性和可靠性。With the promotion of energy internet construction,flexible interaction between various energy sources,continuous diversi-fication of energy demand,the renewable energy consumption ratio is increasing.It enhances the instability of energy supply and demand system,and increases the difficulty of system balance.In order to meet the demand of diversified energy use and realize a high proportion of renewable energy consumption,it proposes a bi-level optimal configuration method for flexible resource capacity of new energy town considering uncertainty.Combined with the joint probability product scenario of the source both sides load being gen-erated by proportional selection method,it uses reducing technique to selecte the maximum probability scenario as the typical daily basic data input.The planning level aims at the lowest annual investment and operation and maintenance costs,and plans the capacity of flexible resources such as ground source heat pump,energy storage and heat storage.The operation layer aims at the lowest cost of fuel,operation and maintenance,light abandonment penalty,and uses genetic algorithm to solve the flexible resource optimization configuration scheme established in typical scenarios.Through a simulation example of a new energy town in the north,it verifies the effectiveness and reliability of the proposed method.
分 类 号:TM73[电气工程—电力系统及自动化]
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