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—The main objective of Energy Management is to produce demanded power with least cost and least environmental effect. This paper presents a novel algorithm for reshaping the load demand profile via day ahead hourly pricing. The day ahead hourly price schedule is determined in such a way that encourages customers to modify as much as possible of their consumption profile according to renewable energy availability. The proposed technique is composed of three optimization problems based on Non Linear Programming (NLP) solver using Sequential Dynamic Programming (SDP) algorithm. The first one is to determine the optimal consumption pattern for each load type that improves the utilization of the conventional generation through minimizing its peak to average ratio (PAR). The second is to determine the optimal price signal, which maximizes customer saving after following that optimal consumption pattern. The last one is the customer test for minimum consumption cost. The Performance of the proposed algorithm is verified by applying it to a low voltage benchmark of a smart grid with residential, commercial, and industrial loads. The simulation results proved the effectiveness of

A Novel Algorithm for Day-Ahead Real Time Pricing for Energy Management in Smart Grid