To address the static voltage stability issue and suppress the voltage fluctuation caused by the increasing integration of wind farms and solar photovoltaic (PV) power plants, a two-tier reactive power and voltage control strategy based on ARMA power forecasting models for wind and solar plants is proposed in this paper. Firstly, ARMA models are established to forecast the output of wind farms and solar PV plants. Secondly, the discrete equipment is pre-regulated based on the single-step prediction information from ARMA forecasting models according to the optimization result. Thirdly, a multi-objective optimization model is presented and solved by particle swarm optimization (PSO) according to the measured data and the proposed static voltage stability index. Finally, the IEEE14 bus system including a wind farm and solar PV plant is utilized to test the effectiveness of the proposed strategy. The results show that the proposed strategy can suppress voltage fluctuation and improve the static voltage stability under the condition of high penetration of renewables including wind and solar power.

Under high renewable energy penetration, nuclear power units face significant challenges in peak regulation and market clearing due to constraints on minimum technical output and ramping capability. To address this issue, a long-term power system of Guangdong Province in 2035 is taken as the study case, and an energy–reserve co-clearing simulation framework based on Security-Constrained Unit Commitment (SCUC) and Security-Constrained Economic Dispatch (SCED) is established to systematically evaluate the clearing performance of nuclear power and the formation mechanism of residual electricity under multiple market scenarios. On this basis, a nuclear power-coupled Alkaline Electrolysis (AEL) hydrogen production pathway is proposed as a peak-shaving utilization option, and an economic assessment model for nuclear-based hydrogen production is developed to quantify the investment performance under different hydrogen production capacities and operating modes. The results indicate that the integration of an AEL hydrogen production system can effectively alleviate the rigidity of nuclear power output. Under the “12-3-48-3” flexible peak-shaving mode, the residual electricity available for hydrogen production increases by approximately 30% compared with a typical peak-shaving strategy. Under scenarios with low electricity prices and green hydrogen prices, when the hydrogen production capacity is configured at 50–100 MW, the investment payback period is approximately six years, and the project exhibits strong economic robustness against variations in the discount rate. These findings demonstrate that nuclear-based hydrogen production is economically feasible in future power systems with high renewable penetration, providing quantitative support for nuclear flexibility enhancement and the coordinated development of low-carbon energy systems.

Sharing the benefits of distribution systems from the integration of distributed photovoltaic systems (DGPVs) with investors is vital to the coordinated development of DGPVs and active distribution systems (ADN). The investment and development of DGPVs, incentive policies, and the development of distribution system interact, and the interactions vary with the changes in the on-grid capacity of DGPVs. In this paper, an event-driven co-simulation platform is built to simulate the abovementioned interaction among DGPVs, ADN, and incentive policy under a long-term time frame. The platform includes an investment model of DGPV investors and an ADN model with consideration of the growth of the ADN. On this platform, we study how multiple factors, including incentive system, global horizontal radiance (GHR), and cost, affect the investment and integration of DGPVs in the future 10 years. Simulation and analysis showed that investors’ decisions are more sensitive to variation in GHR and cost, followed by variation in tariff system, subsidy, and self-use ratio. Distribution subsidies have certain impact on the development of DGPV and could partially replace the national and provincial capacity and generation subsidies. When the on-grid capacity reaches a certain level, the distribution subsidy reaches a dynamic equilibrium.

China’s nuclear power plants traditionally operate to meet baseload needs, with minimal involvement in peak load regulation. However, as the share of renewable energy generation rapidly increases, the volatility of the power system and the demand for peak load regulation have significantly risen, necessitating greater nuclear power flexibility to meet the new power system’s requirements. Our study forecasts the energy structure and load demand for the Province of Liaoning in Northeastern China in 2035. Under this vision, it analyzes the flexibility challenges faced by nuclear generation units. A joint clearing model for spot electricity and ancillary services, along with an energy storage revenue model, was established. Based on this, this study analyzed the clearing results for various typical scenarios in the Province of Liaoning in 2035. The simulation results demonstrate that nuclear units will participate in peak shaving by the target year. This study demonstrates the feasibility of solid-state thermal storage in improving both flexibility and economic efficiency of nuclear generation. Based on these findings, policy recommendations are proposed, including improving regulation compensation mechanisms and promoting multi-energy coupling, providing crucial theoretical and practical support for the role transformation of nuclear generation entities in the new power system. This study establishes a full lifecycle economic assessment model for combined heat and power revenue versus thermal storage investment costs, considering integrated nuclear power–solid thermal energy storage heating systems as the primary technical pathway. Taking a configuration plan with a 715 MW heating capacity and a 6000 MWh thermal storage capacity as an example under Liaoning Province’s 2035 long-term scenario, the simulation results indicate that introducing solid thermal energy storage can significantly improve the revenue structure of nuclear units while meeting deep peak shaving demands, reducing the project’s static payback period to under 11 years.