Optimal allocation of wind turbine in multi carrier energy networks improving loss and voltage profile

S. Pazouki, Amin Mohsenzadeh, M. Haghifam, Mohammad Ebrahim Talebian
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引用次数: 4

Abstract

Smart grid enables Distributed Energy Resources (DERs); wind, energy storage and demand response through advanced technologies. Combined Heat and Power (CHP) is great example of the technologies which allows coupling of independent energy networks together. Energy Hub (EH) has been originated as a new approach to optimal planning and operation of combined networks in recent years. Wind turbine as an important of distributed generation in the world as beenh integrated to electricity network over two past decades. Optimal placement of wind turbine in multi carrier energy network in presence of CHP as another distributed produce source originates novel challenge which is considered in this paper. A multi objective function is formulated to solve the optimization problem with considering multi carrier energy network operation costs, loss and voltage profile. Simulation carries out a 33 bus radial distribution network which is supplied with CHP in some buses. CPLEX solver of GAMS and Genetic Algorithm of MATLAB is employed to solve the problem. Simulation results reveal optimal allocation of wind turbine in multi carrier energy networks in presence of CHP. Results demonstrate that optimal placement of wind turbine in the systems improves operation costs till 8% and loss power till 5%. It also enhances voltage profile till 0.5%.
风电机组在多载波电网中的优化配置,改善损耗和电压分布
智能电网实现分布式能源(DERs);风能,能源储存和需求响应通过先进的技术。热电联产(CHP)是将独立的能源网络耦合在一起的技术的一个很好的例子。能源枢纽(EH)是近年来提出的一种新的联合电网优化规划和运行方法。风力发电作为一种重要的分布式发电方式,在过去的二十年里逐渐融入到电网中。在热电联产作为另一分布式发电源的情况下,风电机组在多载波能源网络中的优化配置提出了新的挑战,本文对此进行了研究。建立了考虑多载波能量网络运行成本、损耗和电压分布的多目标函数来求解优化问题。仿真研究了在部分母线上采用热电联产的33母线径向配电网。采用GAMS的CPLEX求解器和MATLAB的遗传算法对该问题进行求解。仿真结果揭示了存在热电联产的多载波能源网络中风电机组的最优配置。结果表明,风电机组优化配置可使系统运行成本提高8%,损耗功率提高5%。它还将电压剖面提高到0.5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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