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This paper proposes a rule-based power management algorithm to enable the dispatch of a utility-scale PV power plant consisting of a hybrid energy storage system, in accordance with the Australian national electricity rules. This algorithm is purposely designed to regulate the instantaneous power of a PV plant with the same level of dispatchability as conventional power plants. Additionally, the proposed algorithm is robust under large forecasting errors (up to 60%) of solar irradiance and it can be easily implemented in practice. Specifically, this algorithm can be executed within seconds even when considering detailed market operation and model nonlinearities. A 30 MW PV plant, including a 7.5 MW/1.25 MWh vanadium redox battery and a 1.5 MW/0.25 MWh suppercapacitors bank, has been modeled using MATLAB/Simulink and PLECS software environment. The simulation results were based on various scenarios and confirmed the effectiveness of the proposed power management algorithm. It has been shown that even in the worst-case scenario of solar forecasting error of 60%, the proposed algorithm still managed to deliver over 94% of the available energy for a given solar irradiance profile of one month. [ABSTRACT FROM AUTHOR]

Electricity expenditure comprises a significant fraction of the total operating cost in data centers. Hence, cloud service providers are required to reduce electricity cost as much as possible. In this paper, we consider utilizing existing energy storage capabilities in data centers to reduce electricity cost under wholesale electricity markets, where the electricity price exhibits both temporal and spatial variations. A stochastic program is formulated by integrating the center-level load balancing, the server-level configuration, and the battery management while at the same time guaranteeing the quality-of-service experience by end users. We use the Lyapunov optimization technique to design an online algorithm that achieves an explicit tradeoff between cost saving and energy storage capacity. We demonstrate the effectiveness of our proposed algorithm through extensive numerical evaluations based on real-world workload and electricity price data sets. As far as we know, our work is the first to explore the problem of electricity cost saving using energy storage in multiple data centers by considering both the spatial and temporal variations in wholesale electricity prices and workload arrival processes. [ABSTRACT FROM AUTHOR]

A modular multilevel converter ( MMC ) integrated with split battery cells (BIMMCs) is proposed for the battery management system ( BMS) and motor drive system. In order to reduce the switching losses, the state of charge (SOC) balancing strategy with a reduced switching- frequency ( RSF) is proposed in this paper. The proposed RSF algorithm not only reduces the switching losses, but also features good balancing performance both in the unbalanced and balanced initial states. The results are verified by extensive simulations in MATLAB/Simulink surroundings. [ABSTRACT FROM AUTHOR]

This paper deals with a new control algorithm for a voltage and frequency controller (VFC) of an isolated wind energy conversion system (IWECS) using an isolated asynchronous generator to feed three-phase four-wire consumer loads. The reference source currents are estimated for the indirect current control of a voltage source converter (VSC) using the single-phase PQ theory to control the voltage and frequency of IWECS. A three-leg VSC with a battery energy storage system is used as a VFC for an IWECS. A nonisolated star-polygon transformer is used to provide a neutral terminal for four-wire loads and to compensate the neutral current resulting in reduction in rating of VSC. The proposed VFC is implemented using a DSP. Experimental results are presented to demonstrate the additional capabilities of VFC as a load leveler, a load balancer, a harmonic eliminator, and a neutral current compensator. [ABSTRACT FROM AUTHOR]

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Urban rail transit can solve the current inconvenient transportation problem for China's large urban population. A compound onboard energy storage system can meet vehicles' traction requirements and recover energy in vehicles' braking stage to improve energy utilisation. However, the composite onboard energy storage system has several concerns, such as its power and energy demand, battery aging, and maintenance costs. Therefore, the NSGA-II algorithm is proposed to optimise matching the composite energy storage system parameters for urban rail trains. The NSGA-II algorithm was used with an improved elite retention strategy to optimise the parameters matching of the composite power supply. The optimisation's objective concerns the replacement costs and economy of the composite power supply. The method increases the vertical diversity of searching and avoids genetic precocity. The NSGA-II algorithm calls the simulation model of composite power supply in real-time and simultaneously optimises the composite power supply and control parameters. The Pareto set of optimisation objectives and corresponding parameters and control strategies of composite power supply are obtained. The NSGA-II algorithm can optimise the composite energy storage system's parameters and improve the train and the composite power supply's performance indexes. The algorithm greatly reduces the composite power supply's capacitance and reduces the system's total energy consumption. Then, the multi-component energy loss caused by the multi-power source system can be effectively controlled. The total capacitance is reduced by 12.1%, the battery life is prolonged by 18.86%, and the optimised composite power supply's energy storage is increased by 17.6%. [ABSTRACT FROM AUTHOR]

Inspired by the concept of energy internet and energy problems including greenhouse gas emission and regional shortage, this article will propose an idea of electric power distribution using city bus lines running electric vehicles. The designed power distribution system includes renewable energy sources as the energy input, power storage stations placed at some bus stops as the fixed energy output, and bus lines running electric vehicles as the connections between them. As the basic and priority problem, choosing the suitable location to place power storage stations can not only reduce the total number of construction but also increase the utilization rate of each one. Main work involves the two branch algorithms for solving the placement problem; simulation while using real-world transportation data of two city bus maps and analysis about the advantages and disadvantages of algorithms. [ABSTRACT FROM AUTHOR]