Coupling an energy storage to a photovoltaic (PV) system not only increases the self-consumption but also solves the over-voltage issues if the cycling of the storage is properly controlled. Whatever the application the storage is used for, the primary concern of the system owner is to maximize the profits. Therefore, this paper addresses an energy management system for a PV system coupled with battery energy storage, which maximizes the daily economic benefits while curtailing the power injection to the grid in such a way that helps to mitigate over-voltage problems caused by reverse power flow. A time dependent grid feed-in limit is proposed achieve this objective. The daily operational cost that includes the energy cost and the battery degradation cost is considered as the objective function. The non-linear constrained optimization problem is solved using dynamic programming. The analyses are made to investigate the economic benefits of charging the battery from the grid. It is found that there is a possibility for these systems for participating in load-levelling if batteries are charged from the PV system. In order for that to be feasible, the peak-hour sell-back price for the energy from storage should be higher than the off-peak utility electricity price.

A distributed control method for residential battery energy storage (BES) units coupled with photovoltaic (PV) systems is presented. The objective is to utilize customer owned BES units for solving the over-voltage issues caused by high PV penetration without significantly affecting the BES owners local objectives. 24 hour ahead active power set points of the BES unit are calculated by an optimization based scheduling algorithm. The objective function is locally decided and the optimization is performed at the local level.The BES units are charged from the excess energy from the PV systems mostly during the period the grid is under risk of over-voltage. If the set points that were calculated by the optimization, turn out not to be able to maintain the voltages within the statutory limits in real time operation, the active power set points are modified. Reactive power is also utilized when active power is not sufficient. The new set points are calculated by a central controller. The performance of the proposed method is validated in a simulation study. It is shown that the residential BES units can successfully be utilized for solving over-voltage issues without significantly affecting the primary needs of the BES owners. Keywords

This paper proposes a real-time energy management system (EMS) suitable for rooftop PV installations with battery storage. The EMS is connected to a smart grid where the price signals indirectly control the power output of the PV/battery system in response to the demand variation of the electricity networks. The objective of the EMS is to maximize the revenue over a given time period while meeting the battery stored energy constraint. The optimization problem is solved using the method of Lagrange multipliers. The uniqueness of the proposed EMS remains in the reactive real-time control mechanism that compensates for the PV power forecast error. The proposed EMS requires only forecasting the average PV power output over the total optimization period. This is in contrast to the predictive power scheduling techniques that require accurate instantaneous PV power forecast. The proposed EMS method is verified by benchmarking against the predictive brute-force dynamic programming (DP) approach. The simulation analysis considers days with varying solar irradiance profiles. The simulation analysis shows the proposed EMS operating under practical assumptions, where the battery storage capacity is subject to constraints and the PV power output is not known a priori.

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