Abstract

To achieve maximum profit by dispatching a battery storage system in an arbitrage operation, multiple factors must be considered. While revenue from the application is determined by the time variability of the electricity cost, the profit will be lowered by costs resulting from energy efficiency losses, as well as by battery degradation. In this paper, an optimal dispatch strategy is proposed for storage systems trading on energy arbitrage markets. The dispatch is based on a computationally-efficient implementation of a mixed-integer linear programming method, with a cost function that includes variable-energy conversion losses and a cycle-induced battery capacity fade. The parametrisation of these non-linear functions is backed by in-house laboratory tests. A detailed analysis of the proposed methods is given through case studies of different cost-inclusion scenarios, as well as battery investment-cost scenarios. An evaluation with a sample intraday market data set, collected throughout 2017 in Germany, offers a potential monthly revenue of up to 8762 EUR/MWh cap installed capacity, without accounting for the costs attributed to energy losses and battery degradation. While this is slightly above the revenue attainable in a reference application—namely, primary frequency regulation for the same sample month (7716 EUR/MWh cap installed capacity)—the situation changes if costs are considered: The optimisation reveals that losses in battery ageing and efficiency reduce the attainable profit by up to 36% for the most profitable arbitrage use case considered herein. The findings underline the significance of considering both ageing and efficiency in battery system dispatch optimisation.

Highlights

  • An increasing number of investors are considering the installation and marketing of utility-scale battery energy storage systems (BESSs)

  • Whilst pumped-hydro electric power plants are well-suited to monetise the diurnal fluctuations in electricity cost and have generated large revenues, the peak and off-peak patterns significantly changed as renewable energy sources (RESs) became widespread, and the price variability is often recorded on shorter timescales, rendering this application increasingly attractive for fast-reacting storage systems, such as lithium-ion batteries (LIBs) [5,6]

  • To explore the range of results using the optimisation approach, we differentiate between three different cases: Case 1, where all losses are neglected; Case 2, where battery energy efficiency as well as battery cycle ageing are considered; and, lastly, Case 3, where the dissipation losses of the power-electronic equipment are added into case 2

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Summary

Introduction

An increasing number of investors are considering the installation and marketing of utility-scale battery energy storage systems (BESSs). An adequate cost analysis, including the battery dispatch, is generally not provided in the literature In this contribution, we will demonstrate how to optimise battery operation while considering the most relevant cost factors: battery ageing and energy losses in the system. We implemented all relevant cost and revenue functions for BESS operation in an arbitrage market scenario in a mixed integer linear programming (MILP) framework, which allows us to derive the maximum profit attainable and best operational behaviour for the storage system. We, compared these values to the profit attainable through operation of a technically-equivalent storage system in frequency control reserve markets

Literature Review
Structure of This Work
Techno-Economic Framework for Battery Storage Dispatch
System Layout and Framework for Profitability Analysis
Battery Model and Storage System Parameters
Market Data and Battery Cost Analysis
Reference Scenario Operation
Marginal Cost for Battery Operation
Optimisation Framework
Battery Dynamics Modelling
Battery Ageing Modelling
Results and Discussion
Conclusions and Outlook
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