Multi-Agent BESS Capacity Auction Strategy with AutoGen and Google Jules

This challenge focuses on building a multi-agent simulation to optimize bidding strategies for Battery Energy Storage Systems (BESS) in the newly established German capacity market. Using Microsoft's AutoGen framework, you will design a system of collaborating agents: a 'Market Analyst' to forecast demand and prices, a 'BESS Operator' to calculate state-of-health and discharge costs, and a 'Bid Strategist' to synthesize these inputs into a winning auction bid. The implementation must incorporate Google Jules for AI-assisted engineering and code generation of the underlying physics-based battery models. Participants will tackle the complexities of energy arbitrage and capacity availability requirements. The goal is to maximize revenue while adhering to strict market regulations (such as those recently announced in Germany and Poland). You will need to implement complex logic for state-of-charge (SOC) management and cycling constraints, ensuring that the agents communicate effectively to reach a consensus on the optimal bid price and volume for a 200MW/800MWh BESS facility.