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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：这项研究提出了一种需求响应（DR）模型，以减少印度国有企业泰米尔纳德邦发电与配电公司（TANGEDCO）的二次（230 / 440V）配电系统在高峰时段的负载。如果公用事业违反了许可的合同要求限制，TANGEDCO将对其进行处罚。常规的需求控制通常会限制次级分销网络的特定区域。配电网络中特定区域完全停电的限制增加了负载损失的可能性。因此，该项目使用需求侧预测并根据优先级安排空调负荷来实时实施经济的灾难恢复模型。该试点项目已在印度Tiruchirappalli的国家技术研究所执行并受到监控。标准反向传播神经网络用于预测最大需求之前15分钟的间隔，以kVA为单位。这种经济模型包括一个使用ON / OFF切换无线控制继电器模块的通信网络。最后，介绍了该项目涉及的收益和策略。发现所提出的方案防止电力需求超过合同限制，从而与上一年相比，由于违规而导致的罚款为零。

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