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A planning method for siting and sizing of distributed generation based on chance-constrained programming

机译:基于机会约束规划的分布式发电选址与规模规划方法

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With the increasing of the new energy's permeability in the regional power network, the inherent characteristics of new energy output bring new challenges to the power network planning. In order to solve the problem that the traditional distribution network planning is too conservative for the new energy planning, a planning method for siting and sizing of distributed generation (DG) based on Chance-constrained programming is proposed in this paper. The method provides an approach to calculate the new energy's maximum installation capability and the optimal installation site for regional power network Basing on the analysis of stochastic models of wind power, solar output and load, the planning model has the objective function of maximizing renewable energy utilization with the considering of several constraint conditions such as node voltage constraint and branch transmission power constraint. The particle swarm optimization (PSO) algorithm and Monte-Carlo simulation method is used to solve the optimization problem. Taking a regional power network as an example, Power System Analysis Software Package (PSASP) is used to carry out transient and steady stability verification for the extreme scenario, and contingency plans for the accidents which is not satisfied with the verification requirement must be worked out to ensure the safe and stable operation of the network.
机译:随着区域电网中新能源渗透率的提高,新能源输出的内在特征给电网规划提出了新的挑战。为了解决传统的配网规划对新能源规划过于保守的问题,提出了一种基于机会约束规划的分布式发电选址与选型规划方法。该方法在分析风能,太阳能输出和负荷的随机模型的基础上,提供了一种计算区域电网新能源最大安装量和最佳安装地点的方法,该规划模型具有最大化可再生能源利用的目标功能。考虑了一些约束条件,例如节点电压约束和分支传输功率约束。用粒子群算法(PSO)和蒙特卡罗仿真方法解决了优化问题。以区域电网为例,使用电力系统分析软件包(PSASP)对极端情况进行瞬态和稳定稳定性验证,必须制定出不满足验证要求的事故应急计划。确保网络安全稳定运行。

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