Autonomous Operation of Stationary Battery Energy Storage Systems—Optimal Storage Design and Economic Potential

Abstract

Global warming requires a changeover from fossil fuel based to renewable energy sources on the electrical supply side and electrification of the demand side. Due to the transient nature of renewables and fluctuating demand, buffer capacities are necessary to compensate for supply/demand imbalances. Battery energy storage systems are promising. However, the initial costs are high. Repurposing electric vehicle batteries can reduce initial costs. Further, storage design optimization could significantly improve costs. Therefore, a battery control algorithm was developed, and a simulation study was performed to identify the optimal storage design and its economic potential. The algorithm used is based on autonomous (on-site) optimization, which relies on an incentive determining the operation mode (charge, discharge, or idle). The incentive used was the historic day-ahead stock market price for electricity, and the resulting potential economic gains for different European countries were compared for the years 2015–2019. This showed that there is a correlation between economic gain, optimal storage design (capacity-to-power ratio), and the mean standard deviation, as well as the mean relative change of the different day-ahead prices. Low yearly mean standard deviations of about 0.5 Euro Cents per kWh battery capacity lead to yearly earnings of about 1 €/kWh, deviations of 1 Euro Cent to 10 €/kWh, and deviations of 2 Euro Cents to 20 €/kWh. Small yearly mean relative changes, lower than 5%, lead to capacity-to-power ratios greater than 3, relative changes around 10% to an optimal capacity-to-power between 1.5 and 3, and for relative changes greater than 10% to an optimal capacity-to-power ratios of 1. While in countries like the United Kingdom, high potential earnings are expected, the economic prospective in countries like Norway is low due to limited day-ahead price performance.

Multiple Scenario Analysis of Battery Energy Storage System Investment: Measuring Economic and Circular Viability

“…Due to incomplete day-ahead electricity price data for Romania and Ireland, these were replaced with United Kingdom and Slovenia, the next countries listed in the ranking in these regions. Because this study included several countries, the most profitable average capacity-to-power ratio for stationary battery storage system was applied (2.32) [26]. Thus, the battery power was assumed to be 79.7 kW.…”

“…The four energy management strategies were used as incentive in the optimization method to assess the economic savings Faessler and Bogunović Jakobsen [26] Currency converter Currency per 15 March 2021 Morningstar [58]…”

“…An optimization method [26] developed in MATLAB [59] was applied in the simulations. The direct economic savings for the different scenarios were calculated by multiplying the total power consumed for each hour (minus for positive power and plus for negative power) with the day-ahead price at that time from the respective country.…”

“…The objective of this study is to measure economic performance of the battery repurposing CBM [19] and assess other opportunities to lower BESS investment costs. Simulations were based on a battery optimization method [26] and performed for seven European countries investigating the economic potential of the battery storage to generate profit: (1) making use of energy price arbitrage; (2) using it to harvest photovoltaic energy; (3) performing load shifting from peak to low demand times; and (4) improving self-consumption by balancing demand and self-generated photovoltaic energy. Based on the different countries and strategies, 28 scenarios were designed.…”

Stationary, Second Use Battery Energy Storage Systems and Their Applications: A Research Review

“…Behind-the-meter Time-of-use bill management Shifting energy purchases to periods of low prices and using stored energy when the prices are high (price incentivised demand optimisation [52,53]).…”