摘要
考虑风电、光伏两种可再生能源发电形式出力的不确定性,建立风光联合并网情况下的输电网扩展规划模型。该模型兼顾投资成本和收益预期,以最大投资回报率为规划目标,采用基于Monte Carlo模拟的直流概率潮流模型计算支路潮流过负荷的概率,采用机会约束思想处理支路过负荷约束,并利用改进遗传算法求解模型。通过对改进Garver 6节点系统的求解,验证了模型的合理性及算法的有效性。
Considering the uncertain output of wind power generation and photovoltaic （PV） power generation, a transmission network expansion model containing grid-connected wind-PV hybrid system is proposed in this paper. Dif- ferent with the conventional model, the maximum return rate of investment is put forward as planning objective in which both investment cost and profit expectation are considered. The probabilistic DC power flow based on the Monte Carlo simulation is applied to calculate the probability of branch overload, and the chance constrained programming （CCP） is u- tilized to satisfied the constraints of branch transmission capacities. An improved genetic algorithm （IGA） is utilized to solve the optimal planning model. The feasibility of the model and the effectiveness of the algorithm are verified by an ex- ample of improved Garver six-bus test system.
出处
《水电能源科学》
北大核心
2013年第10期221-224,共4页
Water Resources and Power
基金
江苏省电力设计院科技基金资助项目(32-JK-2011-017)
关键词
电网规划
投资回报率
风光联合并网
机会约束规划
遗传算法
power network planning
return rate of investment
grid-connected wind-PV hybrid system
chance con-strained programming
genetic algorithm
