Energy management for stationary electric energy storage systems: A systematic literature review

Multidisciplinary Approach for the Development of Smart Distribution Networks

“…Based on the all the above considerations, it seems clear that the main issue that prevents ESS diffusion consists mainly of high investment costs, which may not be completely counterbalanced by subsequent economic benefits [103]. This is mainly due to the limited number of energy and/or power services that a single ESS technology can provide, especially for FES and UC.…”

“…The EMS optimization criterion can be satisfied by using a number of optimization algorithms [5,103,107], which can be carried out in advance and/or in real-time depending on the kind of services to provide [108]. The most important optimization algorithms are summed up in Table 1; each of these presents advantages and drawbacks, thus its employment is strictly related to the specific optimization criterion and inherent features of the system to optimize.…”

“…A variety of optimization goals can be used, which can be classified in four main categories: economic, environmental, technical and user-driven [103]. Although each of these optimization goals can be pursued individually, they may be also combined to each other by following, for example, a multi-objective optimization (see, for example, Chapter 11 of [104]).…”

“…This is mainly due to the limited number of energy and/or power services that a single ESS technology can provide, especially for FES and UC. In this regard, a viable and very promising solution is represented by hybrid energy storage systems (HESSs); these combine two or more ESS technologies characterized by complementary features, in order to increase the number of grid services they can provide and, thus, their economic viability [103]. Among all the possible ESS combinations, those made up of EB and UC seem the most promising [114,115]; this is mainly due to their high level of modularity, which enables them to fit different energy and/or power requirements and, thus, to provide multiple grid services simultaneously [116][117][118].…”

“…Although each of these optimization goals can be pursued individually, they may be also combined to each other by following, for example, a multi-objective optimization (see, for example, Chapter 11 of [104]). In this regard, two main approaches can be followed, namely "single numeric" or "Pareto" [103]: the former consists of combining all the objectives into a single function, e.g. by a weighted sum.…”