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考虑设备风险和风光不确定性的园区综合能源随机优化运行

Stochastic Optimal Operation of Park-level Integrated Energy Considering Equipment Risk and Uncertainty of Wind and Solar
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摘要 综合能源系统因其能源梯级利用的高效性被广泛应用,而在运行过程中各设备的潜在故障风险与风光出力波动会成为系统供能稳定性的安全隐患。为此,首先基于设备负载率建立故障概率模型与设备风险模型。其次针对风光出力的不确定性采取蒙特卡洛采样法生成典型场景,建立考虑设备风险与风光不确定性的综合能源多目标随机优化模型,运用分段线性化、宽容分层序列法将该模型处理为混合整数模型。最后,通过算例仿真表明:所提优化模型能够兼顾运行风险与经济成本,相较于传统经济调度,在总成本仅上升了9.6%时、设备风险降低了79.3%,证明了模型的经济性与安全性。 The integrated energy system is widely used due to its high efficiency in energy cascading,and the potential failure risk of each equipment in the operation process and fluctuation of wind and solar power output become a hidden danger for the stability of system energy supply.For this reason,firstly,a failure probability model and an equipment risk model based on equipment load rate were established.Then,the Monte Carlo simulation was used to generate typical scenes according to the uncertainty of wind and solar.A multi-objective stochastic optimization model of integrated energy considering equipment risk and wind and solar uncertainty was established.The model was treated as a mixed integer model by using piecewise linearization and tolerant hierarchical sequence method.Finally,the simulation example shows that the proposed optimization model can balance the operational risk and economic cost.Compared with the traditional economic dispatch,when the total cost is increased by 9.6%,the equipment risk is decreased by 79.3%,which proves the economy and security of the model.
作者 闻天润 彭道刚 赵慧荣 张浩 WEN Tian-run;PENG Dao-gang;ZHAO Hui-rong;ZHANG Hao(School of Automatic Engineering,Shanghai University of Electric Power,Shanghai 200090,China;School of Electronics and Information Engineering,Tongji University,Shanghai 201804,China)
出处 《科学技术与工程》 北大核心 2023年第32期13861-13871,共11页 Science Technology and Engineering
基金 国家自然科学基金重大研究计划培育项目(92067105) 国家自然科学基金青年科学基金(52006131) 上海市“科技创新行动计划”地方院校能力建设专项项目(20020500500)。
关键词 园区综合能源 设备风险 风光不确定性 宽容度分层 随机优化 park-level integrated energy system equipment risk uncertainty of wind and solar tolerance stratification stochastic optimization
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