Fuzzy stochastic control algorithm for virtual power plant capacity of source-grid-load-storage integration under demand constraints

Le résumé fourni par la source

Traditional deterministic control algorithms are difficult to adapt to fuzzy random scenarios, which can lead to risks such as excessive remaining SOC and resource waste in the system. Therefore, a fuzzy stochastic control algorithm for the capacity of a virtual power plant with "source network load storage integration" under the constraint of design requirements is proposed. The controllable units are quantified through the fuzzy mathematics method. The start-stop state variables of the equipment and the start-stop cost parameters are introduced. The load ramp/descent rate limit is incorporated into the demand response model. The start-stop state constraints and the standby market scheduling constraints are constructed. The power allocation is achieved by calculating the charging and discharging power margin of the energy storage units separately. By combining the fuzzy evaluation score matrix with the process matrix and replacing the traditional fuzzy operator with real number multiplication and addition operations, rapid decision-making and precise control can be achieved. The experimental results show that the remaining SOC of the proposed method fluctuates within the range of 0.2-0.8, and the statistical frequency reaches 958, reducing the power and capacity of the control.

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