Optimal Siting and Sizing of Distributed Generators in Distribution Systems Considering Uncertainties
Optimal Siting and Sizing of Distributed Generators in Distribution Systems Considering Uncertainties
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DOI：
10.1109/tpwrd.2011.2165972
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发表时间：
2011-09
影响因子：
4.4
通讯作者：
Zhipeng Liu;F. Wen;G. Ledwich
中科院分区：
文献类型：
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作者：
Zhipeng Liu;F. Wen;G. Ledwich
插电式电动汽车(PEV)由于其随机充放电时间表而产生的输出功率的不确定性、风力发电机组因风速的随机性而导致的输出功率的不确定性、太阳能发电电源由于光照强度的随机性、燃油价格的波动以及未来负荷增长的不确定性等不确定性会导致在配电网规划中确定分布式发电机(DGs)的最优选址和规模时存在一定的风险。在此背景下，在机会约束规划(CCP)的框架下，提出了一种新的方法来处理分布式电源最优选址和规模中的不确定性。首先，以分布式电源的投资成本、运行成本、维护成本、网损成本和容量充足性成本最小为目标，以安全约束为约束条件，以分布式电源的选址和规模为优化变量，建立了分布式电源的优化数学模型。然后，采用基于蒙特卡罗模拟嵌入遗传算法的方法对所建立的CCP模型进行求解。最后，利用IEEE 37节点测试馈线验证了所提出模型和方法的可行性和有效性，测试结果表明，该模型和方法可以显著改善用户的电压分布和供电可靠性，大幅降低网损。
Some uncertainties, such as the uncertain output power of a plug-in electric vehicle (PEV) due to its stochastic charging and discharging schedule, that of a wind generation unit due to the stochastic wind speed, and that of a solar generating source due to the stochastic illumination intensity, volatile fuel prices, and future uncertain load growth could lead to some risks in determining the optimal siting and sizing of distributed generators (DGs) in distribution system planning. Given this background, under the chance constrained programming (CCP) framework, a new method is presented to handle these uncertainties in the optimal siting and sizing of DGs. First, a mathematical model of CCP is developed with the minimization of the DGs' investment cost, operating cost, maintenance cost, network loss cost, as well as the capacity adequacy cost as the objective, security limitations as constraints, and the siting and sizing of DGs as optimization variables. Then, a Monte Carlo simulation-embedded genetic-algorithm-based approach is employed to solve the developed CCP model. Finally, the IEEE 37-node test feeder is used to verify the feasibility and effectiveness of the developed model and method, and the test results have demonstrated that the voltage profile and power-supply reliability for customers can be significantly improved and the network loss substantially reduced.