With the increase of the proportion of the renewables, the system inertia and frequency regulation capability in the sending-end power grid have become seriously insufficient, making the frequency stability issue increasingly prominent. This paper proposes a two-layer emergency frequency control scheme for sending-end power grid with multi-energy storage systems (MESSs) to enhance the frequency stability. At the upper layer, the total power control commands of MESSs are optimized to minimize the control energy consumption, considering the constraints of frequency and control power. It achieves the optimal utilization of energy. At the lower layer, the power commands of each ESS are solved by the model predictive controller (MPC), with the objective of minimizing the loss cost and sate of charge (SOC) deviation of ESS, considering the operating characteristics of different ESS. It achieves the reasonable distribution of power. Finally, the effectiveness of the proposed control scheme are verified in IEEE-39 bus system. The results show that the proposed scheme can effectively enhance the system frequency stability for the sending-end system.
Yu Zhang, Haiying Dong, Zifen Han et al.· 2026 5th International Confe...· 0 citations
The surging integration of volatile renewable energy severely exacerbates power grid frequency fluctuations, yet conventional frequency regulation (FR) market clearing mechanisms fail to efficiently coordinate heterogeneous energy storage systems (ESSs) due to the complete decoupling of multi-dimensional physical performance from economic dispatch. To resolve this critical industry bottleneck, this paper proposes a novel Stackelberg game-based clearing mechanism tailored for diverse ESS participation. A bi-level optimization framework is constructed to internalize physical FR characteristics into market economics; the upper level minimizes the system operator’s total procurement costs by transforming multi-dimensional physical metrics—including dynamic response rates, time delays, and control accuracy—into endogenous performance penalty factors. Concurrently, the lower level maximizes the individual revenues of heterogeneous ESS aggregators under a Gini coefficient-based fairness constraint to mitigate profit monopolization and promote a more sustainable market ecology. To address the computational challenges of high-dimensional non-convexity, an enhanced hybrid Genetic Algorithm and Quadratic Programming (GA-QP) solver is developed to secure robust convergence to the Stackelberg equilibrium. Comprehensive simulation results confirm that the proposed Stackelberg game-based clearing mechanism enables a highly rational, quality-driven allocation of frequency regulation capacity. By dynamically linking physical performance metrics with economic benefit factors, it successfully achieves an optimal balance of interests between heterogeneous energy storage aggregators and the overarching market. Crucially, compared to conventional purely economic models, this mechanism structurally prevents absolute technology monopoly—drastically reducing the market Gini coefficient from a hazardous 0.85 to a healthy 0.32—while sustaining multi-party equity at a negligible system cost increase of only 1.64%. Ultimately, this framework offers a highly feasible and resilient solution for the efficient clearing of multi-type energy storage in modern power systems.
Zhekai Xu, Chunxiang Yang, Zifen Han et al.· Energies· 0 citations
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