A hierarchical control scheme is defined for the energy management of a battery energy storage system which is integrated in a low-voltage distribution grid with residential customers and photovoltaic installations. The scope is the economic optimisation of the integrated system by employing predictive control techniques. The approach is based on hierarchical decomposition of the optimisation problem in the time domain by composing a three-level scheduling and control scheme, that is, day-ahead, intra-hour, and real-time, where the initial and final states of each sub-problem are chosen as coordination parameters. The day-ahead and the intra-hour problems address the interactions with electricity markets during the scheduling phase. The real-time algorithm is able to adapt the operation of the battery system according to updated information about market conditions, residential demand, and local generation, and subject to the network capacity and other technical constraints. The simulation scenarios address the interactions with the day-ahead auction and the imbalance settlement system in the Netherlands.
This article addresses the day-ahead economic optimisation of energy storage systems within the setting of electricity spot markets. The case study is about a lithium-ion battery system integrated in a low voltage distribution grid with residential customers and photovoltaic generation in the Netherlands, whereas the optimisation objective is to maximise revenues from energy arbitrage in the day-ahead auction. Assuming accurate predictions of the photovoltaic generation, the residential load and the market clearing prices, the constrained optimisation problem is formulated as the minimisation of a cost function, and is solved by utilising an internal model of the battery system to plan the future response of the charging and discharging process. Emphasis is given on the effect of the system efficiency, which significantly impacts the economic performance due to energy losses during the charging and discharging cycles.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.