The energy transition inspired by carbon neutrality targets and the increasing threat of extreme events raise multi-objective development requirements for power systems. This paper proposes a multi-objective resource allocation model to determine the type, number and location of flexible resources to increase the values of resilience, carbon reduction and renewable energy consumption. To evaluate the values of resilience, a restoration model for transmission systems is established that considers the coordination of fossil-fuel generators, energy storage systems (ESSs) and renewable energy generators in building restoration paths. The collaborative power-carbon-tradable green certificate (TGC) market model is then applied to evaluate the resource values in terms of carbon reduction and renewable energy consumption. Finally, the model is formulated as a mixed-integer linear programming (MILP) with a nonconvex feasible domain, and the normalized normal constraint (NNC) method is applied to obtain approximate Pareto frontiers for decision makers. Case studies validate the effectiveness of the proposed model in improving multi-factor values and analyze the impact of resource regulation capacity on values of restoration and carbon reduction.

The increasingly frequent extreme events pose a serious threat to the safe operation of distribution systems. A detailed description of the impact of extreme events on the supply-network-demand status of distribution networks is crucial for scientific disaster prevention of power systems. To this end, this paper proposes a method for generating disaster scenarios by combining conditional generative adversarial networks (CGAN) with Monte Carlo simulation (MCS) and further proposes a quantitative assessment method for the resilience of distribution systems under typhoon conditions. First, an event-triggered resilience assessment framework combining Monte Carlo simulation and generative AI-driven techniques is proposed. Next, a simulation-based disaster scenario-generation algorithm that considers spatiotemporal correlated supply-demand uncertainty and typhoon-affected component vulnerability is developed. Then, a series of event-affected resilience indices are defined, and the impact of a typhoon on distribution network performance is calculated by simulating during-event disaster scenarios and performing post-event restoration strategies. Finally, extensive numerical results validate the effectiveness of our proposed method.

The research on reliability evaluation of an integrated energy system (IES) is of great significance to system planning and operations. The differences of multiple energy subsystems must be considered in reliability evaluation of an IES, in which energy quality differences of various energy resources is critical. Current reliability evaluation of an IES cannot uniformly evaluate the reliability of multiple energy subsystems due to neglecting the energy quality differences of various energy resources. To address this problem, a novel reliability evaluation method for IESs based on exergy is proposed for the first time in this paper. The exergy of an energy resource or a substance is a measure of its usefulness, quality or potential to cause change. The models of exergy not supplied minimization and exergy efficiency maximization are proposed to alleviate energy capacity deficiency and transmission component overload in the reliability evaluation of an IES. These two models are compared to analyze exergy efficiency for the proposed method. The energy supply priority strategy of an IES is proposed considering energy quality differences of various energy resources, in which electricity, gas and heating/cooling subsystems are supplied in an orderly manner. Furthermore, a reliability evaluation indices system of an IES based on exergy is proposed in this paper. An extensive case study on an actual IES demonstrates the feasibility and effectiveness of the proposed reliability evaluation method.