Large-scale wind power grid integration will greatly change the system current distribution, making it difficult for the reactive power regulator to adjust to the optimal state. In this paper, an integrated reactive power optimisation method based on the improved Harris Hawk (HHO) algorithm is proposed. Firstly, a reactive power regulation model is constructed to solve the reactive power regulation interval of wind turbines, and the reactive power margin of wind turbines is used to participate in the system’s reactive power optimisation. Finally, a reactive power compensation capacity allocation optimisation model considering nodal voltage deviation, line loss and equipment investment cost, is established, and a reactive power optimisation scheme is obtained using the Harris Hawk optimisation algorithm on the basis of considering the constraints of the wind turbine reactive power output interval. The improved HHO algorithm is used to solve the reactive power optimisation scheme considering the constraints of tidal power, machine end voltage, a conventional generator and wind farm reactive power. In the simulation, the effects of the improved Harris Hawk optimisation algorithm and the particle swarm optimisation algorithm are compared, and the experimental results prove that compared to the particle swarm algorithm, the optimisation result of the improved Harris Hawk optimisation algorithm reduces the average loss of the system by 42.6% and reduces the average voltage deviation by 30.3%, which confirms that the improved Harris Hawk intelligent optimisation algorithm is effective in proving its superiority and solving the multi-objective model for reactive power optimisation.

With the increasing penetration of new energy sources, the volatility and uncertainty of new energy output can lead to interruptions or fluctuations in the supply of electricity. Power cuts to critical loads can have a significant impact on public safety, social stability, and the economy. Dealing with the effects of uncertainty from new energy sources means we need to find and strengthen the important loads and power sources when designing and operating the power system. Therefore, the assessment of the importance of loads, conventional power sources, and new energy sources is crucial. This paper proposes a power source importance evaluation method based on load importance and new energy uncertainty. The method constructs a load importance evaluation system considering structural characteristics, outage loss, regulation capability, and other factors. To determine the importance of each load, the method uses the ideal solution method and ranks them accordingly. Next, the method calculates the power supply coefficient, which represents the power supply capability of the power source to the critical loads. This calculation involves using the three-point estimation method, which combines the characteristics of the new energy output and the importance of each load. Following that, the evaluation of load importance and the power supply capacity to critical loads is accomplished based on the ideal solution method, taking into account the diversity of power supply characteristics. This comprehensive evaluation allows us to assess the significance of each load and the power supply capability to meet the needs of critical loads, considering the unique characteristics of each power source. Finally, an example analysis is carried out on the IEEE39 to calculate the importance of various types of power sources, which can accurately reflect the power supply capacity of power sources to important loads and verify the validity of the evaluation method. This method provides subsidies for future power system grid planning and operation.