In a decentralized balancing model, Balance Responsible Parties (BRPs) are encouraged by the Transmission System Operator (TSO) to deviate from their schedule to help the system restore balance, also referred to as implicit balancing. This could reduce balancing costs for the grid operator and lower the entry barrier for flexible assets compared to explicit balancing services. However, these implicit reactions may overshoot when their total capacity is high, potentially requiring more explicit activations. This study analyses the effect of increased participation in the decentralized balancing model in Belgium. To this end, we develop a market simulator that produces price signals on minute-level and simulate the implicit reactions for battery assets with different risk profiles. Besides the current price formula, we also study two potential candidates for the near-term presented by the TSO. A simulation study is conducted using Belgian market data for the year 2023. The findings indicate that, while having a significant positive effect on the balancing costs at first, the risk of overshoots can outweigh the potential benefits when the total capacity of the implicit reactions becomes too large. Furthermore, even when the balancing costs start to increase for the TSO, BRPs were still found to benefit from implicit balancing.
Global renewable energy capacity continues to grow sharply year-on-year [1]. While this helps to reduce fossil fuel consumption and global emissions, their intermittent nature poses challenges for the grid to remain in balance. Therefore, Transmission System Operators (TSOs) need to rely on the activation of grid reserves to ensure stability of the power system. The costs related to these services are attributed to Balance Responsible Parties (BRPs), who are responsible for keeping their portfolio of generators and off-takers balanced, through the imbalance settlement procedure.
The main objective of imbalance settlement is to incentivize BRPs to maintain balance within their portfolio by engaging in day-ahead and intraday trading. Any deviations from their contracted schedule are therefore penalized with the imbalance price. However, since single imbalance pricing became prevalent in Europe [2], BRPs can also be rewarded during imbalance settlement when their open positions contribute to restoring balance in the system. In a decentralized balancing model, the TSO even encourages BRPs to deviate from their schedule to help balance the grid in real-time [3]. We will further refer to this deliberate deviation from the contracted volumes as implicit balancing. To incentivize BRPs, the TSO publishes an (intermediate) real-time price signal that should guide their reactions. This model can reduce grid balancing costs and lower the entry barrier for flexible assets compared to frequency restoration reserves, though it requires the TSO to sacrifice explicit control of balancing actions. An important drawback of the decentralized balancing model is the introduction of short-term oscillations in the system, which occur when the implicit reaction is larger than the required volume to restore balance. With the growing share of flexible assets, such as grid-scale batteries or renewables, that allow for curtailment of production, this issue will likely become more pronounced. Therefore, it is essential that the TSO carefully establishes real-time price signals that align participant behavior with system balancing needs.
Past research on implicit balancing focused on developing control strategies that could increase operational profit for BRPs. To incorporate the impact of these strategies on the imbalance price, methods were proposed employing model predictive control [4], [5], reinforcement learning [6] or a combination of both [7]. However, apart from [7], they only consider a granularity of 15 minutes, whereas intermediate prices are published every minute in Belgium and the interquarter hour dynamics are also important to account for [8]. Furthermore, they focus on one market participant aiming to optimize its position using state-of-the-art forecast and optimization methods, rather than all market participants acting upon the signal provided by the TSO.
In this work, we want to take a more holistic view and study the impact of a growing number of flexible assets which participate in implicit balancing of the Belgian grid. To achieve this, we develop a market simulation model which outputs minute-level price signals and incorporate a feedback loop that simulates additional implicit response to these signals. To determine the explicit activations by the TSO, the simulator applies a mixed integer linear program to historical data of the individual balancing energy bids. The model produces price signals for every timestep by considering the imbalance price formula and the information on the activated reserves during the imbalance settlement period (ISP). In addition to the current formula, we consider two formulas proposed for the near future by the Belgian TSO (Elia) in their “Real-time price design note I” [9]. The implicit response to those signals is modelled as a collection of battery energy storage system (BESS) assets with varying properties and risk appetites. These assets are assumed to respond to the price signals provided by the TSO rather than position themselves based on price forecasts.
The main contributions of the paper are:
• We develop a market simulation model, extending previous work of [8], [10], which incorporates the feedback loop between the actions of the TSO and the reactions of BRPs. This simulator allows to study implicit balancing from the perspective of both parties for different scenarios. • This paper compares three different imbalance price formulas, the current one as well as two potential candidates for the near future [9]. • This paper illustrates how the projected expansion of flexible capacity [11] could disturb grid stability when BRPs do not account for the impact of their reaction on the market. The simulator is applied to Belgian market data of 2023. We find that a greater implicit response to the imbalance price can have a positive impact on the balancing costs, while also being profitable for BRPs. However, when the total capacity becomes too large, the risk of overshoot
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