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作 者:王功臣[1] 邓长虹[1] 夏沛[1] 梁宁[1] 张达[1] 周沁[1]
机构地区:[1]武汉大学电气工程学院,湖北省武汉市430072
出 处:《电力系统自动化》2017年第11期55-60,共6页Automation of Electric Power Systems
基 金:国家科技支撑计划资助项目(2013BAA02B02)~~
摘 要:提出一种包含调整机组优化选取策略的滚动优化调度方法。根据负荷及风电超短期预测信息,首先考虑等效负荷(负荷+风电)预测偏差和机组调节容量匹配、机组爬坡量和等效负荷波动量匹配,以及减少外送断面越限原则进行调节机组优化选取。在此基础上,以机组调整成本及弃风量最小为目标,建立优化模型并采用改进粒子群优化算法求解。实际算例表明,考虑机组优化选取的滚动优化调度实现了超短期时间尺度上对负荷及风电预测偏差的自动跟踪调节,提高了发电计划的准确性,同时有效降低了综合发电成本和外送断面功率越限的风险,提高了电网运行的经济性和安全性。A rolling optimization dispatching method is proposed including the optimal selection strategy of units to be adjusted. According to ultra-short-term predictive information of load and wind power, the units to be adjusted are optimized and selected first by considering the matching between the prediction deviation of equivalent load (load and wind) and units' regulation capacity, the matching between the units' climbing amount and the fluctuation quantity of equivalent load, as well as the principle of reducing risks of the interface power off limits. On this basis, with minimum unit adjustment cost and abandoned wind power as the objective, an optimizing mathematical model is developed and solved by the improved particle swarm optimization (PSO) algorithm. A practical example shows that the rolling optimization dispatching method considering the optimal selection strategy of units can realize automatic tracking and regulation according to the prediction deviation of load and wind power on an ultra-short-term time scale, while improving the accuracy of generation schedule and reducing the comprehensive generating costs and the risks of the interface power getting off-limits to enhance the economy and security of power grid.
关 键 词:风电 滚动优化调度 机组优化选取 粒子群优化算法
分 类 号:TM73[电气工程—电力系统及自动化]
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