Modelling and optimal energy management for battery energy storage systems in renewable energy systems: A review

Incorporating Battery Energy Storage Systems (BESS) into renewable energy systems offers clear potential benefits, but management approaches that optimally operate the system are required to fully realise these benefits. There exist many strategies and techniques for optimising the operation of BESS in renewable systems, with the desired outcomes ranging from specific dispatch aims to targets that cover financial, technical or hybrid objectives. The optimisation techniques employed can be grouped into three main categories; directed search-based methods; probabilistic methods; and rule-based strategies. A key focus of past studies has been specific renewable energy systems with targeted applications, such as large scale, or distributed generation. This review, whilst providing a comprehensive summary of battery management approaches, analyses these studies in terms of linking the application purpose and the optimisation technique employed. This approach means correlations between specific optimisation targets and preferred optimisation techniques can be identified. It is found that financial objective optimisations are more likely to be solved by directed search-based methods, and control strategies applied for technical objective optimisations. The choice of solution technique is also shown to strongly depend on how well the problem is formulated mathematically. The relative strengths and weaknesses of the reported optimisation techniques are compared leading to the conclusion that hybrid approaches, combining advantages from different approaches, will play an increasing role in the future operation strategy development. In addition to a state-of-the-art review of battery applications and optimisation techniques, this review should help researchers quickly identify suitable optimisation techniques for new generation applications. • Battery optimisation targets reviewed include financial, technical and hybrid objectives. • Battery optimisation techniques employed can be categorised as directed search-based methods, probabilistic methods, and control strategies. • The correlations between specific optimisation targets and preferred optimisation techniques are identified. • The choice of solution technique strongly depends on how well the problem is formulated mathematically.