Rapid renewable energy deployment driven by global decarbonization goals is accelerating worldwide. However, seasonal variability and evolving climate patterns pose great challenges to the long-term adequacy of power supply. This study focuses on the long-term climate risks associated with inadequate renewable supply. First, the climate risk is defined and quantified as the seasonal inadequacy of renewable supply. Then, the risk formulation is incorporated into the optimal planning model as a three-stage framework. Finally, a 2030 China-provincial case study is performed. The case results show that the climate-risk-aware planning scheme raises total system costs by approximately 0.5% but cuts expected load curtailment by nearly 40%. Additionally, residual climate risk is concentrated in a few coastal and southwestern provincial-level regions, primarily in winter, and in southern coastal regions in summer. The introduction of climate risk reshapes capacity portfolios, raises costs, and exposes seasonal reliability gaps in coastal areas.

With increasing awareness of environmental protection and rising carbon emission costs, participation in electricity and carbon markets for energy-intensive industrial users will become an effective way to reduce operating costs and carbon emissions. In this regard, a novel Stackelberg game framework is developed in this study for coordinated participation in coupled electricity‒carbon markets. Specifically, generalized carbon emission models and electricity consumption models for different energy-intensive industrial users are established, and a Stackelberg game-based interactive operation strategy is proposed for load aggregators (LAs) and energy-intensive industrial users in joint electricity‒carbon markets, where the LA works as a leader who chooses proper interactive prices to maximize the comprehensive benefit, whereas energy-intensive industrial users serve as followers who minimize the total energy costs in response to the interactive prices set by the LA. Then, the existence and uniqueness of the Stackelberg equilibrium (SE) are analyzed, and a decentralized solution algorithm is suggested to reach the SE. Finally, the simulation results demonstrate that the proposed interactive operation strategy can not only increase the profit of the LA but also reduce the cost of energy-intensive industrial users, which achieves a win-win result.

The large-scale integration of power electronic interface-based renewable energy with intermittency and uncertainty poses severe challenges for power system secure operation, especially frequency security. Determining the system frequency regulation ability under contingency is an open problem. To bridge this gap, a unit commitment (UC) to concentrate solar power considering operational risk and frequency dynamic constraints (RFUC-CSP) is proposed in this paper. A concentrating solar power (CSP) plant with renewable energy characteristics and synchronous units is employed to improve renewable energy utilization and provide frequency support. Firstly, an analytical operational risk model is established to quantify the operational risk under renewable energy integration. Then, the frequency dynamic response characteristic of the system is considered to construct frequency security constraints. A novel RFUC-CSP framework is formulated by incorporating operational risk and frequency security constraints into the UC model, which can allocate operational flexibility of power systems by optimizing the admissible uncertainty level to reduce operational risk. The effectiveness of the proposed RFUC-CSP model is demonstrated by case studies on the modified IEEE 30-bus and IEEE RTS-79 system, and the cost-effectiveness of the CSP plant is quantified.