The Impact of Control Strategies on the Performance and Profitability of Li-Ion Home Storage Systems

An increase in electricity prices along with a decrease in the price of storage systems has led to rapid expansion of the PV-battery home storage system market in Germany. In order to be economically viable PV-storage systems must fulfill certain performance criteria, and in this context the system control strategy has a large impact on the overall system performance. In a nutshell, the control software should regulate the system in such a way as to maximize the self-supply ratio as well as the battery lifetime. An intelligent control strategy also has added benefits for the grid operator. At KIT 20 commercially available PV-battery systems have been analyzed with respect to specific performance criteria: of those the following were used to quantify the level of intelligence of the storage system control software: (a) whether the software contains a predictive module at all, and if so whether it depends on external weather data; (b) the success of delayed charging in reducing the time spent at high stage of charge (SOC) levels and (c) whether prediction errors lead to the battery not being fully charged so that the user's self-sufficiency is unnecessarily reduced. Since the different effects are not independent the goal is to quantify the effects on system performance and profitability in each case. This shows the effect of software on the overall economics of energy storage systems and complements other studies based on simulation or those that look at different aspects like cell aging in an isolated context. Roughly one quarter of the systems tested have an intelligent algorithm that controls the battery charging in such a way as to minimize calendar aging. In addition, differences of up to two years in battery lifetime are shown using voltage measurements with realistic household profiles and measured PV data. In this way, the present work outlines how control software can influence the performance and in particular the calendar aging of PV storage systems. (C) 2017 The Authors. Published by Elsevier Ltd.