考虑需求侧低碳资源的新型模糊双目标机组组合模型

A Novel Fuzzy Bi-objective Unit Commitment Model Considering Demand Side Low-carbon Resources

提出一种可促进电力系统碳减排的新型机组组合模型。相比于传统模型,该模型在以下两方面进行了改进:一是综合考虑供应侧资源与需求响应、电动汽车、分布式可再生能源发电等低碳的需求侧资源的最优组合;二是机组调度的规则在经济目标之外充分考虑碳排放目标,提出可计及目标相对优先级的模糊双目标优化方法。另外,在求解优化模型时,对粒子群优化算法进行改进,引入了遗传算法中的"交叉"、"变异"两个算子,提高了粒子群算法的全局寻优能力。通过对10机系统进行算例分析,验证了模型与算法的有效性。

A novel unit commitment model to promote carbon reduction of a power system is proposed.Compared with traditional models,this one is improved in the following two aspects.On the one hand,low-carbon demand side resources, such as demand response,vehicle to grid and distributed renewable energy generation,are considered together with power supply resources to achieve an optimal schedule.On the other hand,a new fuzzy bi-objective optimization approach that can reflect the relevant priority between objectives is presented to strike an effective balance between economic objective and carbon emission objective.To solve the unit commitment optimization problem,the particle swarm optimization (PSO) is improved by employing crossover operator and mutation operator from the genetic algorithm,which enhances the global optimization ability of PSO.Numerical studies of a 10-unit system have verified the effectiveness of the model and the algorithm.