Economic Dispatch Model Based on Time-of-Use Electricity Price for Photovoltaic Systems

Due to the energy storage limitations of photovoltaic systems and the uneven time-of-use of electricity by users and the policies of different time-of-use electricity price, scheduling and dispatching of photovoltaic systems incurs irregular trend of electricity consumption and associated price hikes which influences by supply and demand. To this end, this paper proposes a novel model for photovoltaic system based on sensor networks system exploiting the historical factual data and the real-time data obtained from various sensors of the system, where adaptive particle swarm optimization and bacteria foraging algorithms are used for optimizing the scheduling process. The algorithm enhances the capacity of both global and local searches, and the convergence speed and estimation accuracy are promoted obviously compared to the other algorithm. Experiments results demonstrate that the ED model in this paper has the effect of peak cutting and valley filling, which ultimately bring the greatest economic benefits to the users.

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