摘要
严重自然灾害事件会给电力系统运行安全带来巨大风险,需要研究提高电力系统应对自然灾害事故能力的措施与方法,这也是弹性电力系统建设的重要内容。增强电力系统弹性的最基本措施是加强系统结构,发展计及自然灾害的输电系统规划方法,以适当平衡支路建设成本与风险损失是值得研究的重要课题。在此背景下,通过综合考虑投资与运行经济性、常规运行情况下的系统可靠性和发生自然灾害情况下的系统风险等因素,发展了输电系统规划的混合整数非线性规划模型。构建了计及风电与负荷波动以及发生自然灾害情形下的2类场景集,分别用于对候选规划方案进行安全校验和风险评估。之后,在分层优化架构下采用粒子群优化算法求解所构造的优化模型。最后,用经典的18节点系统说明了所提方法的基本特征。
Severe natural disasters may result in significant risks to the secure operation of a power system concerned.Hence,it is necessary to study the measures and methods for enhancing the capability of the power system to cope with natural disasters,and this is an important part in building a resilient power system. A fundamental measure of upgrading the resilience of a power system is to strengthen its structure,therefore it is an important research issue to develop transmission system planning methods with natural disasters as well as reasonable compromise between investment costs and risk losses well taken into account. Given this background,a mixed integer nonlinear programming model for transmission system planning is developed to comprehensively evaluate the economics of network investment and system operation,the reliability under normal system operation and the suffered risk under natural disasters. Two sets of representative scenarios are then generated to respectively describe the situations with fluctuant wind power outputs and random load variances as well as the ones with natural disasters,and are respectively employed to check security constraints and evaluate the risk concerned. The well-established particle swarm optimization algorithm is next employed to solve the presented optimization model under the hierarchical optimization framework. Finally,a typical 18-node sample power system is served for demonstrating the essential features of the developed method.
出处
《电力建设》
北大核心
2017年第4期26-33,共8页
Electric Power Construction
基金
国家自然科学基金项目(51477151)
广东电网有限责任公司科技项目(GDKJQQ20153001)~~
关键词
输电系统规划
自然灾害风险
场景分析
预想事故场景筛选
分层优化
transmission system planning
natural disaster risk
scenario analysis
contingency scenario screening
hierarchical optimization
