Load recovery optimization method considering unit state in system recovery process

Abstract

The invention discloses a load recovery optimization method considering a unit state in a system recovery process. Load optimization considering the unit state is established by utilizing a logic preference description language, a nonlinear model of load recovery is established, the model is solved by adopting an artificial bee colony algorithm, and a load recovery line and time considering the unit state are obtained. The method comprises the following steps of: 1, constructing a load optimization grading knowledge base considering a unit state in a system recovery process, 2, establishing aload optimization preference strategy set considering the unit state in the system recovery process, 3, establishing a load recovery optimization model considering the unit state in the system recovery process, and 4, solving the load recovery optimization model by adopting an artificial bee colony algorithm to obtain a recovery line and time of the load considering the unit state in the system recovery process. According to the method, load recovery in the system recovery process can be optimized, important loads are ensured to be rapidly recovered, and a reasonable load recovery scheme is provided.

Description

technical field [0001] The invention belongs to the technical field of power grids, in particular to a load recovery optimization method considering the state of a unit in the system recovery process. Background technique [0002] With the continuous development of the national economy, the demand for electricity from all aspects of society is increasing, and the scale of the power system is also expanding. With the development of the power grid, the connection between the networks is getting closer and closer, the structure of power components is becoming more and more complex, and the probability of large-scale power outages caused by small-scale power grid failures is also increasing. Because the operating environment of the power system is very complex, natural disasters, power supply in short supply, aging power lines and human misoperation may cause failures. Once an accident occurs, it will cause economic loss and social impact. In severe cases, small-scale accident...

AI Technical Summary

Problems solved by technology

However, in the above studies, the start-up characteristics of thermal power generating units were not taken into account. In the grid reconfiguration, the load recovered by the unit is only the load on the optimal recovery path, and the load not on the recovery path is recovered by other lines. extra recovery time

However, due to the start-up characteristics of thermal power generating units, the additional recovery time may cause a time delay for hot-starting generators and reduce the recovery efficiency of the power system

Therefore, it is necessary to take into account the start-up characteristics of the thermal power generating set, establish a suitable model, and optimize the load recovery within the time interval between the maximum hot start time and the minimum cold start time of the generating set; but there is no effective optimization in the prior art Program

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