Profit-Maximizing Planning and Control of Battery Energy Storage Systems for Primary Frequency Control (1604.00952v1)

Abstract: We consider a two-level profit-maximizing strategy, including planning and control, for battery energy storage system (BESS) owners that participate in the primary frequency control (PFC) market. Specifically, the optimal BESS control minimizes the operating cost by keeping the state of charge (SoC) in an optimal range. Through rigorous analysis, we prove that the optimal BESS control is a "state-invariant" strategy in the sense that the optimal SoC range does not vary with the state of the system. As such, the optimal control strategy can be computed offline once and for all with very low complexity. Regarding the BESS planning, we prove that the the minimum operating cost is a decreasing convex function of the BESS energy capacity. This leads to the optimal BESS sizing that strikes a balance between the capital investment and operating cost. Our work here provides a useful theoretical framework for understanding the planning and control strategies that maximize the economic benefits of BESSs in ancillary service markets.

• The paper introduces a two-level, profit-maximizing strategy for BESS in primary frequency control, proving the optimal control is state-invariant for efficient real-time operation.
• Numerical results demonstrate the strategy reduces operating costs and regulation failure probabilities compared to benchmark algorithms.
• The research establishes the convexity of operating cost relative to energy capacity, providing a basis for optimal BESS sizing decisions.

Summary of Strategies for Battery Energy Storage in Primary Frequency Control

This paper addresses the optimal planning and control strategies for battery energy storage systems (BESS) participating in primary frequency control (PFC) markets, where PFC is essential for maintaining the nominal frequency in power systems. The focus lies on devising strategies that enhance economic benefits while managing operational complexities.

Key Contributions

A significant contribution is the formulation of a two-level profit-maximizing strategy combining both planning and real-time control. The paper demonstrates that optimal BESS control is state-invariant, meaning the ideal state of charge (SoC) does not change with the system's current state. This revelation allows computation of the optimal strategy offline, enabling real-time operation with minimal computational load. There is also a proof that the operating cost is a decreasing convex function of the BESS energy capacity, guiding optimal sizing decisions to balance between investment and operating costs.

Numerical Results and Claims

One of the numerical findings includes demonstrated reductions in operating costs and regulation failure probabilities when adopting the proposed optimal charging strategies compared to benchmark algorithms. For instance, the optimal strategy shows better performance in minimizing penalties for regulation failures, contributing to more efficient economic planning and operation. Furthermore, graphs and metrics illustrate how various parameters such as battery efficiency ($\eta$), penalty rates ($c_p$), and battery energy capacity ($E_{max}$) affect the optimal SoC targets and overall costs.

Implications and Future Directions

The proposed strategy offers both theoretical and practical implications. Theoretically, it establishes a comprehensive framework for dynamic programming in frequency control, highlighting the reduction of problem dimensions via state invariance of the control action. Practically, it suggests that energy storage systems can become financially viable participants in ancillary service markets, providing rapid response instead of traditional mechanical systems. Future work could extend these methods to multi-purpose BESS applications including demand response and peak shaving, as integrating services presents both challenges and opportunities to optimize value extraction.

Conclusion

This paper provided a methodical approach to understanding profit-maximizing strategies for BESS in frequency control, leveraging the unique properties of energy storage devices. The findings form a cornerstone for further research and development in optimizing energy storage deployments for grid stability and economic efficiency. The convexity and state-invariance principles serve as critical insights, offering pathways to improved planning and operational protocols in the evolving landscape of power system ancillary services.