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A Sustainability-Oriented Multiobjective Optimization Model for Siting and Sizing Distributed Generation Plants in Distribution Systems

机译:用于配电系统中分布式发电厂的可持续发展型多目标优化模型

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摘要

This paper proposes a sustainability-oriented multiobjective optimization model for siting and sizing DG plants in distribution systems. Life cycle exergy (LCE) is used as a unified indicator of the entire system’s environmental sustainability, and it is optimized as an objective function in the model. Other two objective functions include economic cost and expected power loss. Chance constraints are used to control the operation risks caused by the uncertain power loads and renewable energies. A semilinearized simulation method is proposed and combined with the Latin hypercube sampling (LHS) method to improve the efficiency of probabilistic load flow (PLF) analysis which is repeatedly performed to verify the chance constraints. A numerical study based on the modified IEEE 33-node system is performed to verify the proposed method. Numerical results show that the proposed semilinearized simulation method reduces about 93.3% of the calculation time of PLF analysis and guarantees satisfying accuracy. The results also indicate that benefits for environmental sustainability of using DG plants can be effectively reflected by the proposed model which helps the planner to make rational decision towards sustainable development of the distribution system.
机译:本文提出了一种可持续性导向的多目标优化模型,用于在分配系统中采集和施加DG工厂。生命周期驱逐(LCE)被用作整个系统环境可持续性的统一指标,并且在模型中被优化为目标函数。其他两个客观职能包括经济成本和预期的失衡。机会约束用于控制由不确定的电力负载和可再生能量引起的操作风险。提出了一种半线性化仿真方法,并结合了拉丁超立体采样(LHS)方法,以提高概率负载流量(PLF)分析的效率,以验证机会限制。执行基于修改的IEEE 33节点系统的数值研究来验证所提出的方法。数值结果表明,所提出的半解析模拟方法减少了PLF分析计算时间的约93.3%,并保证了满足准确性的保证。结果还表明,使用DG工厂的环境可持续性的益处可以有效地反映出拟议的模型,这有助于规划师对分配系统的可持续发展做出理性决策。

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