Power systems are undergoing a policy-driven transition to decarbonization, which increases uncertainty and fluctuation due to the high penetration of renewable energy. Concurrently, advancements in communication and control technologies are unlocking greater demand-side flexibility. However, existing conventional long-term resource planning models for power systems do not adequately integrate demand response (DR) resources, operation simulations that account for uncertainty, and social factors such as government policy. To address these shortcomings, this paper introduces a robust planning frame-work for power system decarbonization pathways, specifically considering DR load as a critical flexible resource along with other techniques and impacting factors. Firstly, the long-term impacts of government policies and other social factors on system resource investment costs and development constraints are quantitatively considered, and the adjustable and transferable DR loads as key flexible resources are incorporated to smooth the fluctuations caused by renewable energy generation. Then, a three-stage robust planning model is developed by integrating long-term development planning, day-ahead unit commitment simulation, and intra-day power dispatch simulation to obtain the optimal solution with the lowest total cost over the planning period. Moreover, the column and constraint generation algorithm is modified to solve the planning model, specifically designed to address the decision-dependent uncertainty arising from new asset investments. Case study based on a provincial power system shows that the proposed framework enhances the integration of renewable energy by applying DR resources in line with real social development trends. The combination of long-term system planning, refined short-term operation simulation, and strategic DR integration ensures that the resulting decarbonization pathway is not only economically feasible but also highly robust and reliable.
Haiyue et al. (2026) studied this question.