Added value of Energy Storage Systems

Abstract

Energy storage systems (ESS) are expected to be one of the main pillars for a future renewable based power system. Since all sectors are electrifying and variable renewable energy (VRE) is being deployed more quickly than transmission and distribution operators are able to connect them to the electricity grid. Flexible capacity on multiple positions along the electricity value chain is needed to maintain stability of the network. However, the original design of the grid was not based on decentralized and variable generation. Together with uncertain regulations that are not up-to-date with innovations in the grid. Results in multiple barriers that the ESS needs to overcome and therefore have not been widely integrated yet. Since investment decisions by decision-makers are not only based on technical and economic features but also on social and environmental features better insight in the impact of different power system design is needed.

Several studies have been performed on the tech-economic modelling of singular ESS services, often using perfect foresight for prices and market behavior for different parts of the electricity value chain. This work presents foundation for valuation of ESS for industrial sites in the Netherlands in a future scenario with large increase of VRE in the energy mix.
Since energy systems are highly complex systems. Modelling and simulation is performed to get a better understanding of the system by simplifying interactions and functional relations within the industrial power system. Hence, the model provides insights that help to reevaluate the power operation of an industrial cluster. As a result it helps to reshape the power system investment strategy for the future. Considering that ESS are multi-applications this study analyses how different operations strategies including multiple services influence the performance of the industrial power system. The operation strategies of enhancing self-consumption (greedy) and peak shaving are compared on the following performance indicators: self-consumption, self-sufficiency, utilized and unutilized VRE, size of network connection, capacity for flexibility and influence of transit power generation. The greedy and peak shaving operations are simulated in combination with the services of providing transit power for back-up generation and ability to provide flexibility service for the imbalance market.

The model is run for three different industrial loads (scenarios) for five different configurations of either a Photo-Voltaic (PV) system or a PV system in combination with an ESS. In all scenarios, the power systems performance is better when ESS is integrated in comparison to the PV-system. In the scenarios the scoring varies considerably between the configurations, primarily due to the heterogeneity of the used load profiles. Hence, allowing to identify the characteristics of industrial load profiles more suitable for a combined PV and ESS system. The results of this study are relevant for decision-makers considering to adapt their power system design strategy by providing a better understanding of their system. It shows how different services run in parallel allow the ESS to be operated less idle. Nevertheless, should decision-makers establish operational priorities since some services can be competitive and
result in a sub-additive value. Furthermore, can the findings help policy makers and utilities to see what the influence is of increased VRE generation at the industrial load side of the network on the larger system.