With the increase of power generation from renewable energy sources and due to their intermittent nature, the power grid is facing the great challenge in maintaining the power network stability and reliability. To address the challenge, one of the options is to detach the power generation from consumption via energy storage. The intention of this paper is to give an overview of the current technology developments in compressed air energy storage (CAES) and the future direction of the technology development in this area. Compared with other energy storage technologies, CAES is proven to be a clean and sustainable type of energy storage with the unique features of high capacity and long-duration of the storage. Its scale and cost are similar to pumped hydroelectric storage (PHS), thus CAES has attracted much attention in recent years while further development for PHS is restricted by the availability of suitable geological locations. The paper presents the state-of-the-art of current CAES technology development, analyses the major technological barriers/weaknesses and proposes suggestions for future technology development. This paper should provide a useful reference for CAES technology research and development strategy.

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The prevalence of ED among female university students in China is now similar to that of their western counterparts, and BED is the most common ED followed by BN and AN similarly.

A virtual power plant takes advantage of interactive communication and energy management systems to optimize and coordinate the dispatch of distributed generation, interruptible loads, energy storage systems and battery switch stations, so as to integrate them as an entity to exchange energy with the power market. This paper studies the optimal dispatch strategy of a virtual power plant, based on a unified electricity market combining day-ahead trading with real-time trading. The operation models of interruptible loads, energy storage systems and battery switch stations are specifically described in the paper. The virtual power plant applies an optimal dispatch strategy to earn the maximal expected profit under some fluctuating parameters, including market price, retail price and load demand. The presented model is a nonlinear mixed-integer programming with inter-temporal constraints and is solved by the fruit fly algorithm.

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