The transition to a sustainable energy system has accelerated the integration of renewable energy sources (RES), such as wind and solar power, into electricity markets and infrastructures. While these sources contribute significantly to the decarbonization of the energy sector, their inherent variability and limited predictability introduce operational challenges for maintaining system balance and ensuring cost-effective grid utilization. Additionally, the geographic distribution of RES, often located in remote areas, has exacerbated issues of grid congestion, leading to limitations in grid access, rising curtailment levels, and deferred renewable projects. In response to these challenges, Hybrid Power Plants (HPPs), which co-locate RES with Battery Energy Storage Systems (BESS), have emerged as a viable solution offering increased operational flexibility, improved forecast error mitigation, and enhanced economic performance, while utilizing one grid connection point.

This study evaluates the added economic and energetic value of co-locating a BESS with a RES under the Dutch electricity market structure. A multi-stage stochastic optimization framework is developed to simulate HPP participation across the day-ahead, intraday, and imbalance markets. The model incorporates power forecast uncertainty through scenario generation and reduction techniques, and captures the physical constraints of energy systems, including battery operations and capacity, RES capacity, and restricted grid connection capacity. Optimization is conducted on a rolling horizon to reflect the sequential nature of market decision-making.

Three configurations are analyzed: a standalone RES system, a standalone BESS, and a co-located HPP. These systems are evaluated based on simulated operations over four weeks each representing a season using real market prices and wind power data. The co-located HPP demonstrates superior performance in terms of both economic return and renewable energy utilization. By enabling time-shifting of generation, reducing curtailment, and participating more effectively in short-term markets, the HPP captures additional value that standalone systems cannot access. Moreover, the ability to operate flexibly within a fixed grid export limit allows the HPP to relieve grid congestion, using storage to shift energy dispatch in line with the needs of the electricity system, indicated by price signals, thereby reducing strain on network infrastructure.

A comprehensive analysis investigates the impact of key assumptions regarding price and power forecasts and operational parameters, such as battery size, technology characteristics, grid connection capacity, and reoptimization frequency. Results indicate that system performance is highly dependent on the quality of imbalance price forecasts and the ability to respond dynamically to power forecast updates and market prices. This has been demonstrated by a comparison between no foresight, perfect foresight and using the day-ahead clearing price as imbalance forecast. Moreover, allowing the HPP to withdraw energy from the grid, results in signficant economic gains, however, this comes at the cost of renewable energy utilization. Although the study excludes capital and degradation costs, the findings underscore the operational advantages of co-locating RES and BESS under uncertainty and grid limitations.

Overall, this research contributes to a deeper understanding of how flexible, market-responsive HPPs can support the transition to a resilient and economically efficient low-carbon power system. It highlights the importance of integrated modeling approaches for optimizing renewable dispatch strategies in evolving electricity markets, while also demonstrating how HPPs can contribute to better utilizing grid connection capacity and enabling greater renewable integration.