Optimal allocation and adaptive VAR control of PV-DG in distribution networks
Optimal allocation and adaptive VAR control of PV-DG in distribution networks
复制标题
配电网PV-DG优化配置及自适应VAR控制
DOI：
10.1016/j.apenergy.2014.10.012
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发表时间：
2015
期刊：
影响因子：
11.2
通讯作者：
Haoyong Chen
中科院分区：
文献类型：
--
作者：
Xueqian Fu;Haoyong Chen
分布式发电的发展给电网带来了新的挑战。其中，分布式电源引起的配电网电压调节问题引起了广泛的关注。分布式电源在配电网中的优化配置是另一个被广泛研究的问题。针对光伏发电机组的不可调度特性，提出了一种新的光伏分布式发电（PV-DG）优化配置方法。在PV-DG配置中引入自适应无功控制模型，以平衡含PV-DG单元的配电网中电压质量改善和网损最小化之间的权衡。最优分配问题被制定为一个机会约束随机规划（CCSP）模型，用于处理太阳能发电的随机性。提出了一种将多目标粒子群优化（MOPSO）和支持向量机（SVM）相结合的新算法来求解由一组可能解组成的Pareto前沿。Pareto解进一步评估使用加权秩和比（WRSR）的方法，以帮助决策者获得所需的解决方案。对33节点辐射状配电网的仿真结果表明，该优化配置方法能够充分考虑PV-DG的时变特性和概率分布，得到最优配置方案。
The development of distributed generation (DG) has brought new challenges to power networks. One of them that catches extensive attention is the voltage regulation problem of distribution networks caused by DG. Optimal allocation of DG in distribution networks is another well-known problem being widely investigated. This paper proposes a new method for the optimal allocation of photovoltaic distributed generation (PV-DG) considering the non-dispatchable characteristics of PV units. An adaptive reactive power control model is introduced in PV-DG allocation as to balance the trade-off between the improvement of voltage quality and the minimization of power loss in a distribution network integrated with PV-DG units. The optimal allocation problem is formulated as a chance-constrained stochastic programming (CCSP) model for dealing with the randomness of solar power energy. A novel algorithm combining the multi-objective particle swarm optimization (MOPSO) with support vector machines (SVM) is proposed to find the Pareto front consisting of a set of possible solutions. The Pareto solutions are further evaluated using the weighted rank sum ratio (WRSR) method to help the decision-maker obtain the desired solution. Simulation results on a 33-bus radial distribution system show that the optimal allocation method can fully take into account the time-variant characteristics and probability distribution of PV-DG, and obtain the best allocation scheme.
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影响因子：
11.2
作者：
M. Gómez;A. Lopez;F. Jurado
通讯作者：
M. Gómez;A. Lopez;F. Jurado
DOI：
10.4028/www.scientific.net/amr.518-523.4839
发表时间：
2012-05
期刊：
Advanced Materials Research
影响因子：
--
作者：
Ji Zhou
通讯作者：
Ji Zhou
影响因子：
--
作者：
Chen Zinian
通讯作者：
Chen Zinian
影响因子：
11.2
作者：
H. Ren;Weisheng Zhou;K. Nakagami;Weijun Gao;Qiong Wu
通讯作者：
H. Ren;Weisheng Zhou;K. Nakagami;Weijun Gao;Qiong Wu
DOI：
10.1109/appeec.2013.6837134
发表时间：
2013-12
期刊：
2013 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)
影响因子：
--
作者：
R. Cai;Haoyong Chen;Runge Lu;X. Jin;Huanghuang Liu
通讯作者：
R. Cai;Haoyong Chen;Runge Lu;X. Jin;Huanghuang Liu