This paper evaluates the participation of a grid-connected BESS Energy Storage System (BESS), in the Day ahead (DA) and Frequency Containment Reserve (FCR) markets in Europe. Through annual simulations, the study demonstrates the substantial revenue potential of providing multiple services (DA+FCR) by a single BESS, resulting in a significant 74% increase compared to the sum of individual markets’ participation. Furthermore, a comprehensive sensitivity analysis is conducted to determine the optimal sizing of the BESS, revealing the advantages of higher power-to-energy ratios in terms of profitability and payback periods. An oscillation penalty is introduced to mitigate the BESS degradation by reducing the BESS’s depth of discharge. This leads to a reduction of BESS capacity fade behavior by 7 % while incurring only a marginal 9 % loss in the annual revenues. These findings contribute valuable insights for decision-making in deploying grid-connected batteries, considering revenue optimization and BESS performances.

Battery energy storage systems (BESSs) are more and more considered as a potential asset to provide frequency containment reserve (FCR) services. In practical deployment, it is challenging for the BESS owner to secure benefits when submitting bids for FCR one day ahead under the uncertainty of prices and frequency deviations. Moreover, the energy capacity constraints for such a system make it difficult to assure the availability of the reserve over the day without knowing in advance the need for regulation. Thus, in this paper, an operational planning consisting of a look-ahead bidding strategy followed by a rule-based control is presented for a BESS participating in the FCR market. Historical data are used to compute the day-ahead bids before four different controllers are proposed for reaf-time operation on the day of delivery. Yearly simulations show the trade-off between profits, penalties for non-activation, and BESS lifetime. The results show that corrective charging/discharging in real-time enables the BESS to achieve up to 97% of the maximum theoretical profits.

BESS Energy Storage Systems (BESS) are increasingly recognized as crucial participants in the energy market, offering versatile grid services. To maximize profitability, this paper explores the opportunity to stack services while participating in the Day-Ahead market (DA) and the Frequency Containment Reserve (FCR) market. Look-ahead optimization is proposed assuming that energy and reserve prices and requirements are known to examine the interplay between DA and FCR products. In particular, two management strategies are proposed to provide the two services and hence evaluate the maximum theoretical profits assuming a perfect price forecast. Strategy (a) allows participation in only one service at each hour of the day. Strategy (b) enables the simultaneous provision of the two services all the time. Additionally, a baseline case is introduced while allowing the BESS to participate only in one market. The simulations use historical data to compute the DA energy and FCR schedule. Furthermore, a storage degradation analysis is performed to evaluate the effect of the predicted operations on the BESS lifetime, considering both cycling and calendar aging.

As renewable energy sources become more prevalent, effective grid balancing becomes crucial due to their inherent uncertainty. Battery Energy Storage Systems (BESS) can enhance grid reliability and efficiency by complementing these variable sources. However, to encourage investments in BESS, market participation must be economically viable for owners. Energy arbitrage is one of the main revenue streams for BESS allowing them to buy electricity when prices are low and sell it when they become higher, thus optimizing the revenues. However, in energy markets such as the Day-Ahead market (DA), the BESS owners submit their bids/offers one day before delivery, without perfect foresight of the future rates. This uncertainty poses a challenge that limits the energy provision capabilities and can incur a loss of profit due to the imperfect price forecast. Tailored strategies are then needed to mitigate those uncertainties and minimize the profit loss. This article proposes different operational planning strategies for a BESS participating in DA. Specific interest is attached to the explainability of the proposed methods to assure high profits while reducing the model’s complexity and computational time. The proposed strategies include 1) price forecast and scenario generation, using Geometric Brownian Motion (GBM) based either on a single-point forecast or historical data; 2) optimization process; and 3) choice of a single BESS bidding and operating schedule that is ultimately applied in real-time. Two baselines are introduced, one relying on a back-casting method, and a second based on traditional stochastic optimization. Several studies have neglected to thoroughly assess the bidding strategies by evaluating the profit against the actual prices. Hence, this study assesses the performance of the proposed methods and the baselines relative to the profit obtained in an ideal scenario with a perfect forecast in the French market over 2021.

Energy Storage Systems (ESSs) potentially enhance the flexibility of power grids, and their operators can benefit from various streams of revenues to recover the investment. This study targets the estimation of revenues expected from the provision of Frequency Containment Reserve (FCR), or primary reserve, in the European market. A reference model is introduced, where the FCR activation is decided based on the actual frequency measurements (Model 1). As those measurements may not be systematically available, this paper proposes two additional models in the form of offline approaches that enable the ESS operator to determine the economic viability of targeting the FCR market without the need for actual frequency data. Model 2 is an improved version of a conventional formulation based on a constant coefficient of activated energy concerning the battery-rated power (i.e. reserved capacity). Model 3 is a novel simplified model based on a variable activation coefficient that depends on the total activated reserve by the system operator. The validity of the proposed models is assessed compared to the exact formulation over six months considering the French market in 2021. Results show that adopting Model 2 s is preferable in the cases where the quantity of activated energy is high (high-frequency gain), resulting in a 3 % error compared to Model 1. However, in the opposite case (low-frequency gain), Model 3 is favorable to use, with an error of 2 %.

This paper investigates the opportunity for a Battery Energy Storage System (BESS) to participate in multiple energy markets. The study proposes an offline assessment to calculate the maximum annual revenues to reach the optimum stack of services through deterministic simulations. The markets include wholesale energy markets (day-ahead and intraday), ancillary services (frequency regulation and reserve), and the capacity mechanism. The study case performed on the French markets shows that frequency services overperform the other markets, where the long-term capacity market has the least potential. Moreover, providing multiple services maximizes the battery's revenues, for example, participating in joint energy and reserve markets showed a 76% increase in annual profits. Furthermore, a novel operation approach was proposed to enhance the performance of these joint markets, by indirectly utilizing energy products as frequency reserves. The results demonstrate that the proposed formulation allows a revenue increase of similar to 23% compared to the conventional framework for the provision of frequency regulation with BESSs. Additionally, the joint markets have been shown to be economically viable with 6.2 years payback period after considering battery degradation and depreciation cost.