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The increasing growth in installed capacity for renewable energy sources has progressively replaced traditional thermal power units as synchronous power contributors. This transition has led to a reduction in system inertia and resources for frequency regulation, creating a need for renewable energy and energy storage to participate in system frequency modulation. Empirical studies indicate that the current market mechanism for frequency modulation auxiliary services, which predominantly rely on thermal power, is suboptimal for leveraging the unique capabilities of diverse frequency modulation resources. This inadequacy hinders the power industry's pursuit of the "dual carbon" goals -- carbon neutrality and carbon peak. Hence, this paper proposes a joint clearing model for the involvement of renewable energy and energy storage in the frequency modulation auxiliary service market. It considers performance differences and employs the Analytic hierarchy process (AHP) to guide the optimization of the weights of frequency modulation performance indicators for various frequency modulation resources. This approach allows renewable energy, energy storage, and thermal power to maximize the benefits of their own differentiated advantages in various frequency modulation performance indicators. Consequently, this fosters an increased share of renewable energy within the system while ensuring frequency stability, thereby expediting the achievement of the power industry's "dual carbon" goals. Finally, computational analyses substantiate that the proposed joint clearing model, accounting for performance differentials, can enhance the renewable energy share in the system and simultaneously reduce the societal costs associated with frequency modulation services. [ABSTRACT FROM AUTHOR]

The complex energy conversion and the volatility of renewable energy/load bring great challenges to the operation of the park‐level integrated energy system (PIES). To overcome this challenge, this paper proposes a multi‐timescale flexible dispatching method to fully exploit the flexibility of PIES in the energy cascade utilization mode. The cascade utilization model for energy flow is firstly established to analyse the coupling and complementary of heterogeneous energy. On this basis, the supply‐demand general equations of multi‐energy flexibility are proposed, which accurately quantify the ability to cope with uncertainty through mutual flexibility. Through coordinated complementation and mutual exchange of multi‐grade flexibility, the system realizes the suppression of random power fluctuations. The scheduling model includes day‐ahead dispatch and intraday multi‐time scale dispatch, which can satisfy the adjustment speed requirements of different energy. Numerical results demonstrate that the proposed method effectively enhances the flexibility and economy of system operation. The flexible demand for energy of all grades can be satisfied. Compared with the flexible dispatch in the triple energy supply structure, the operating cost is reduced by 9.07%. [ABSTRACT FROM AUTHOR]

Multi-battery energy storage systems (MBESSs) are widely adopted to overcome the uncertainty problem of renewable energy sources. However, state-of-charge (SOC) imbalance issue of MBESSs brings great challenges to the optimal dispatching strategy and the lifetime management strategy for the MBESS. This study proposes a distributed equalisation strategy for the MBESSs to solve the stated problem. An equitable operation optimisation model is proposed in the distributed equalisation strategy. The equitable optimisation model can be simplified as a convex quadratic optimisation problem. An equitable approximation method is utilised to solve the convex quadratic optimisation problem according to the Karush–Kuhn–Tucker optimality conditions. Based on the equitable approximation method, the SOC balance process is distributed into different iteration steps. The iteration of the SOC balance process is implemented by the communication system connecting the distributed management systems (DMSs). The distributed SOC balance step is implemented by the DMSs of the batteries. The proposed strategy is validated by a hardware-in-the-loop simulation system based on the RT-LAB. Test results show that the proposed strategy ensure the SOC balance and improve the robustness of the MBESS. [ABSTRACT FROM AUTHOR]