基于商业园区源/储/荷协同运行的储能系统多目标优化配置

Multi-Objective Optimal Configuration of Energy Storage Systems Based on Coordinated Operation of Source/Storage/Load in Commercial Park

科技园等商业园区的用电负荷类型多样,用电特征和规律与传统高耗能工厂园也有较大区别。通过分析商业园区多负荷特征和人员作息规律,基于分时电价机制采取低谷储能峰平释能的运行策略动态调整冷负荷侧制冷机组功率和园区与电网联络线功率,既实现了对蓄冰槽出力的优化调度,同时由园区能量平衡原则得到储能系统的实时充放电功率,实现对储能功率和容量的配置。建立基于能效、经济、环境的多目标优化模型,分别实现蓄能装置的循环电量和循环冷量最小、储能系统成本及购电费用之和最少和环境污染成本最小。采用基于动态惯性权重的多目标非支配粒子群算法对所建模型进行求解,对生成的Pareto解集使用模糊隶属度法筛选得到最优解。通过上海某商业园区算例验证了所提方法的有效性和可行性。

Commercial parks,such as science parks,have various kinds of electrical loads with features different from those of traditional high energy-consuming plant parks.By analyzing the features of multi-type loads and people＇s regular routine,an energy storage strategy in valley period（or energy release in peak/flat period） is proposed based on time-of-use price.Refrigerator power in cooling demand side and power exchange between the commercial parks and main grid are dynamically adjusted.Optimized scheduling of ice storage tank is realized,and charging/discharging power of storage battery is obtained simultaneously with energy balance principle.Relying on above data,power and capacity configuration of storage can be achieved.Based on indexes of energy efficiency,economy and environment,multi-objective optimization model is established to obtain minimums of circulating power and circulating cooling energy,total costs of energy-storage investments and power-purchase and environmental pollution cost.Non-dominated multi-objective particle swarm optimization（MOPSO） strategy with dynamic inertia weight is adopted to optimize the model,and final Pareto solution can be selected using method of fuzzy membership degree.Validity and feasibility of the proposed method are verified with a case study of a commercial park in Shanghai.