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User centric economic demand response management in a secondary distribution system in India

机译:印度二级分销系统中以用户为中心的经济需求响应管理

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摘要

This study presents a demand response (DR) model to curtail the load during peak hours in a secondary (230/440V) distribution system of Tamil Nadu Generation and Distribution Corporation (TANGEDCO), a state-owned enterprise, India. TANGEDCO penalises utilities if they violate their permitted contractual limit of demand. Conventional demand control usually curtails a specific region of the secondary distribution network. The limitation of the complete blackout of the particular region in the distribution network increases the loss of load probability. Hence, this project implements an economic DR model in real time using demand side forecasting and by scheduling air-conditioning loads based on their priority. The pilot project is executed and is monitored at the National Institute of Technology, Tiruchirappalli, India campus. A standard back propagation neural network is used for forecasting a 15 min interval ahead maximum demand in kVA. This economic model comprises of a communication network that uses ON/OFF switching wirelessly controlled relay modules. Finally, the benefits and the strategy involved in the project are presented. It is found that the proposed scheme prevents the electrical demand from exceeding the contractual limit, whereby the penalty due to the violation is zeroed when compared to the previous year.
机译:本研究提出了一种需求响应(DR)模型,用于在泰米尔纳德邦一代和分销公司(Tangedco),印度国有企业的二级(230 / 440V)分配系统中的高峰时段缩减负荷。唐德科如果违反其允许的合约需求限额,致电公用事业。常规需求控制通常会限制二级分配网络的特定区域。分配网络中特定区域的完整停电的限制增加了负载概率的损失。因此,该项目实时使用需求侧预测和根据其优先级调度空调负载来实现经济博士模型。试点项目被执行并在印度校园蒂鲁奇拉蒂·蒂鲁奇拉利国家理工学院监测。标准后传播神经网络用于预测在KVA中最大需求的15分钟内部。这种经济模型包括用于使用ON / OFF切换无线控制的继电器模块的通信网络。最后,提出了该项目所涉及的福利和策略。结果发现,该方案防止了电气需求超过了合同限额,从而与上一年相比,由于违规行为的罚款是归零的。

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