Development of a robust and sustainable regional demography-based demand management technique

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This paper presents a robust and sustainable energy management system driven by regional demographic patterns developed using fuzzy logic and mixed integer linear programming (MILP). This method detects and integrates variations in the energy use patterns of urban and rural communities attaining improved efficiency in the management of regional power demand. The detection and integration of the urban and rural energy use patterns were done by combining period partitioning based regional time of use tariff and fuzzy based appliance level renewable resource allocation to develop a function to be optimized using an improved MILP which provides users with the optimum schedule of appliance usage based on their demographic classification. The effectiveness of the proposed method was tested by running MATLAB simulations of different scenarios emulating continuous regional renewable integration planning with urban and rural power consumption profiles generated using LoadProGen. The proposed method’s effectiveness is confirmed by the achievement of a reduction upto 31% in the community energy cost as well as significant reduction in the energy costs of each participant over different scenarios compared to the unoptimized base case. The proposed method can be effectively utilized in energy management applications catering to multiregional and mixed demographic communities.