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IoT based Demand Response Management in Microgrids
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DOI：10.1109/ICEES51510.2021.9383763.png)
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Abstract
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This paper proposes to use a different kind of management system on microgrids, that prices electricity consumption with a more dynamic approach based on the demand rather than using the conventional average consumption pricing. This approach is greatly beneficial in decreasing dependency on nonrenewable sources of electricity as well as reducing the wholesale price of electrical commodities is the big picture. By using the IoT platform, UBIDOTS, all the load patterns and pricing is made transparent to the customer, who in turn can choose [9]to reduce their load consumption during peak hours and shift their usage to off peak hours. Smart switches can be used to make noncritical load shedding one click away. The primary input data in our system are those related to number of units of power produced (solar, wind, battery) and the load details (critical and noncritical loads). Our setup consists of 3 microgrids whose load pattern is analyzed, and accordingly, a tariff is calculated for the demand based on the cost of production, level of demand and other parameters. Apart from this, an incentive is also provided to the customers based on certain criteria. We also examine the trend of the load and its pricing and create a regression model in MATLAB and predict load values to analyze in the future.
Keywords:
Demand Response Management
Dynamic Pricing
Peak Hour Pricing
Internet of Things
Machine Learning
Microgrid
smart switch
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