With the advancement of China’s carbon policy, the proportion of renewable energy, mainly wind and solar, has increased, which brings greater challenges to the reservation of power systems. Due to the complexity of China’s power systems, adopting the method of the zonal reserve to ensure stable system operation is very difficult. Among the existing clearing results for calculating reservation, the unit reservation will be restricted by the network security constraints, leading to system operation risks. To obtain the unit reservations efficiently without breaking the security constraints, this paper proposes an effective reserve calculation method for engineering implementation. A box robust optimization is further utilized for Security Constrained Unit Commitment in the method to ensure the consumption of renewable energy, and the stability and clearing efficiency of the power system. Furthermore, a data-driven robust random optimization is employed for Security Constrained Economic Dispatch optimizing the economy of power systems. This multi-stage robust optimization model, which has good extensibility, is in line with China’s clearing process. The simulation analysis based on the actual operation data of a province in China and the IEEE 300-bus system verifies the correctness and feasibility of the proposed model and theory.
Summary
The increasing penetration of renewable generation significantly challenges the balancing between generation and demand in power systems. The traditional method that relies on dispatching generating units to satisfy load demand has shown its limitations in coping with the augmented volatility in the system. On the other hand, the introduction of smart grid technologies facilitates customers' interactions with the grid and makes them the provider of demand response (DR) resource. In this paper, we focus on the demand shifting as the major form of DR and propose an integrated demand shifting bidding framework to aggregate DR resources from both large and small customers. A market clearing model is proposed for the ISO to formalize the day‐ahead scheduling of both generation and the demand shifting resources. The demand shifting cost is also proposed which can be used as a tool for load aggregators to reward the customers. The model is simulated on the IEEE 30‐bus system, and results successfully demonstrate that the proposed model can reduce peak load, system cost, and price spikes.
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