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Recently, Home Energy Management (HEM) controllers have been widely used for residential load management in a smart grid. Generally, residential load management aims to reduce the electricity bills and also curtail the Peak-to-Average Ratio (PAR). In this paper, we design a HEM controller on the basis of four heuristic algorithms: Bacterial Foraging Optimization Algorithm (BFOA), Genetic Algorithm...
With the emergence of smart grid which has bidirectional communication capability plays a key role in maintaining balance between demand and supply. The major portion of energy consumed by residential sector creates a huge deficit between generation and consumption. Home energy management (HEM) system incorporation scheduling algorithm is an efficient alternate to cover this deficit by appropriate...
Demand side management (DSM) will play a significant role in the future smart grid by managing loads in a smart way. DSM programs, realized via home energy management systems for smart cities, provide many benefits; consumers enjoy electricity price savings and utility operates at reduced peak demand. In this paper, evolutionary algorithms-based (binary particle swarm optimization, genetic algorithm,...
Today, energy is the most valuable resource, new methods and techniques are being discovered to fulfill the demand of energy. However, energy demand growth causes a serious energy crisis, especially when demand is comparatively high and creates the peak load. This problem can be handled by integrating Demand Side Management (DSM) with traditional Smart Grid (SG) through two way communication between...
The state of the art of old-age grids into smart grids provides residents the opportunity to schedule their appliances to consume the energy optimally that leads to potentially balance the demand side as well as the supply side more effectively and minimizes the power Peak-to-Average Ratio (PAR), which ultimately provides benefit to the residents in the form of reduction cost and expense. The Energy...
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