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考虑可再生能源跨区域消纳的主动配电网多目标优化调度
引用本文:曾博,杨煦,张建华. 考虑可再生能源跨区域消纳的主动配电网多目标优化调度[J]. 电工技术学报, 2016, 0(22): 148-158. DOI: 10.3969/j.issn.1000-6753.2016.22.018
作者姓名:曾博  杨煦  张建华
作者单位:新能源电力系统国家重点实验室 华北电力大学 北京 102206
基金项目:国家重点研发计划重点专项(2016YFB0101903),国家自然科学基金(51507061),中央高校基本科研业务费专项基金(2015QN01)资助项目。
摘    要:提高对可再生能源的综合利用能力是主动配电网(ADN)运行控制面临的新增重要任务。为此,提出了一种面向促进可再生能源跨区域消纳的ADN多目标运行优化方法。首先,基于并网接口模型,推导了集中控制模式下分布式发电(DG)的有功、无功功率解耦可调范围,并提出考虑可再生能源跨区域消纳的ADN能量管理策略。在此基础上,分别以系统运行成本、可再生能源发电功率削减量以及系统网损三方面最小化作为目标,构建ADN多目标优化调度模型。该模型综合考虑了DG有功、无功出力控制、储能设备充放电以及可中断负荷的调用,并详细分析了网络潮流和分布式资源特性两方面的约束及其多时段耦合特征。鉴于所建模型具有高维、非线性特点,采用基于启发式策略的多目标和声搜索算法实现高效求解。以扩展的33节点配网系统为例,验证了所提模型的有效性以及ADN运行中计及可再生能源DG无功控制潜力的必要性。

关 键 词:主动配电网  可再生能源发电  优化运行  多目标优化

Multi-Objective Optimization for Active Distribution Network Scheduling Considering Renewable Energy Harvesting Across Regions
Abstract:Increasing the efficiency of renewable energy usage is a newly-supplemented target for active distribution network (ADN) operation. Thereby, a multi-objective optimization framework for ADN operation that considers cross-regional utilization of renewable energy is proposed in this study. Firstly, based on the DC/AC model, the active/reactive decouple model of DG units under the centralized control mode is derived, and then the strategy for ADN operation considering cross-regional usage of renewable energy is put forward. Accordingly, a multi-objective model for ADN scheduling is built, taking the minimization of operation cost, renewable energy curtailment and network losses as objectives. In this model, the management for the active/reactive power output from DG units, energy storages and interruptible loads has been considered, taken the inter-temporal constraints into account. Due to high dimension and nonlinearity of the proposed model, the multi-objective harmony search algorithm is adopted. A modified 33-bus distribution system has verified the proposed method as well as the necessity for incorporating reactive capability of renewable-based DG units.
Keywords:Active distribution network  renewable energy generation  optimal scheduling  multi-objective optimization
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