Abstract
Demand-side energy management is used for regulating the consumers’ energy usage in smart grid. With the guidance of the grid’s price policy, the consumers can change their energy consumption in response. The objective of this study is jointly optimizing the load status and electric supply, in order to make a tradeoff between the electric cost and the thermal comfort. The problem is formulated into a nonconvex optimization model. The multiplier method is used to solve the constrained optimization, and the objective function is transformed to the augmented Lagrangian function without constraints. Hence, the Powell direction acceleration method with advance and retreat is applied to solve the unconstrained optimization. Numerical results show that the proposed algorithm can achieve the balance between the electric supply and demand, and the optimization variables converge to the optimum.
Highlights
The power system includes generators, transformers, transmission, and distribution lines that deliver electricity power to terminal users
This work studies a demand-side energy management problem based on the nonconvex optimization algorithm
One of the major advantages of this algorithm is that it can be applied in solving the unknown objective function caused by the thermal comfort model
Summary
The power system includes generators, transformers, transmission, and distribution lines that deliver electricity power to terminal users. Smart grid enables real-time control and monitoring to provide distributed generation and storage. It can make grid operating reliably, economically and efficiently [1,2]. The energy providers can monitor the operating states of the loads in real time and control power supply directly. Demand-side energy management has been a hot topic in recent years [3,4]. Demand-side energy management is a mechanism which requires the consumers’ response to pricing strategy [8,9,10]. The real-time price is an effective strategy to achieve demand-side response [11,12,13]
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