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首页> 外文期刊>Future generation computer systems >A dual objective approach for aggregator managed demand side management (DSM) in cloud based cyber physical smart distribution system
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A dual objective approach for aggregator managed demand side management (DSM) in cloud based cyber physical smart distribution system

机译：基于云的网络物理智能分配系统中聚合器管理的需求侧管理（DSM）的双目标方法

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This paper presents an incentive based framework for demand response scheduling in smart distribution networks with commercial, residential and industrial load sectors using designated cloud storage in cyber physical cloud based smart distribution system. The proposed approach consists of a two stage procedure where dual objective problem is modeled to achieve both responsive load agent (RLA) economic benefits as well as distribution system operator (DSO) preferences. The two stage coordinated scheduling of RLAs with DSO network operation preferences is carried out by demand response aggregation agent (DRAA) through incentives. The cloud based information exchange between different stakeholders provides the necessary communication at different stages of responsive load scheduling. The concept of private, shared and community clouds are incorporated into the cyber physical cloud based DAM framework proposed in this work. The first stage scheduling of responsive loads is carried out by RLAs with electricity payment minimization objective looking into the tariff structure. Whereas, the second stage scheduling is carried out by DRAA in which incentives are offered to RLAs for the deviation from personalized schedules of first stage. The customer characterization and behavior (risk averse, incentive preferences etc.) of scheduling the responsive loads is considered through incentive range based clusters. The proposed DRAA coordinated DR scheduling framework is simulated using IEEE 37 bus distribution test system with commercial, residential and industrial sectors. The impact of stage 1 and stage 2 scheduling of responsive loads is analyzed with respect to system performance indices such as total operational cost, load factor, total network losses etc. The sensitivity analysis is performed to examine the impact of weightage assignment to DSO and RLA objectives on system performance aspects. The proposed DRAA coordinated two stage framework has shown considerable improvement in techno-economic aspects of responsive load scheduling in distribution network that can be appended to real world applications at distribution level/retail markets.
机译：本文提出了一种基于激励的框架，用于在具有商业，住宅和工业负载部门的智能配电网中使用基于网络物理云的智能配电系统中的指定云存储进行需求响应调度。所提出的方法由两阶段程序组成，其中对双重目标问题进行建模以实现响应式负载代理（RLA）的经济利益以及配电系统运营商（DSO）的偏好。具有DSO网络操作首选项的RLA的两阶段协调调度是由需求响应聚集代理（DRAA）通过激励来执行的。不同利益相关者之间基于云的信息交换在响应负载调度的不同阶段提供了必要的通信。私有云，共享云和社区云的概念已合并到本工作中提出的基于网络物理云的DAM框架中。响应负载的第一阶段调度由RLA进行，其电费最小化目标是研究电价结构。鉴于第二阶段的调度是由DRAA执行的，其中向RLA提供了与第一阶段的个性化调度偏离的激励措施。通过基于激励范围的集群来考虑安排响应负载的客户特征和行为（规避风险，激励偏好等）。所提出的DRAA协调的DR调度框架是使用IEEE 37总线配电测试系统对商业，住宅和工业部门进行仿真的。针对系统性能指标（例如总运营成本，负载因子，总网络损耗等）分析了响应负载的第1阶段和第2阶段调度的影响。进行了敏感性分析，以检查权重分配对DSO和RLA的影响系统性能方面的目标。拟议中的DRAA协调的两阶段框架在配电网络中响应负荷调度的技术经济方面已显示出显着改进，可以将其附加到配电级/零售市场的实际应用中。

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