| Under the background of China’s "Carbon Peak,carbon neutrality" target,with the increasing installed capacity and power generation of renewable energy,building a new power system with new energy as the mainstay is the key to China’s low-carbon energy transition.Due to the differences in China’s geographical distribution,new energy-rich areas are located in remote areas far away from load centers,while DC transmission has the advantages of large transmission capacity,long transmission distance and low network losses,and can serve as a good carrier for new energy consumption and power transmission.As the scale of hybrid AC-DC transmission continues to expand,the DC system is more closely linked to the AC system,and the new energy represented by photovoltaic and wind power has a strong randomness,volatility and uncontrollability,bringing huge challenges to the safe and economic operation of the grid.In view of this,under the conditions of large-scale new energy access to the grid,in order to improve the operational stability of the system and reduce the system operating losses,this paper conducts a study on the optimal operation of the AC-DC hybrid grid,with the main research content as below:Firstly,the development status of new energy generation and DC transmission is analyzed,the current research on the optimization of hybrid AC-DC system operation is summarized,the hybrid AC-DC transmission model is established,the formulae for solving the power flow model based on the Newton-Raphson method are derived,and the alternating iteration method is used for tidal calculation.The mechanism of the impact of different access locations and capacities of new energy sources on the system network loss and voltage is then analyzed from two perspectives:active power and reactive power,which are verified by simulation using IEEE 39 nodes,laying the foundation for the optimization design later.Secondly,a multi-objective reactive voltage control optimization model that takes into account network losses and voltage deviations is developed for the hybrid AC-DC system,with the generator terminal voltage,on-load regulator transformer ratio,reactive power compensation capacity and DC system control parameters as the control quantities to be optimized.Since the established model is a complex non-linear programming problem with multiple variables and constraints,a hybrid whale swarm algorithm based on the combination of the whale optimization algorithm(WOA)and the traditional particle swarm(PSO)is proposed,by introducing the whale By introducing the encircling strategy of the whale algorithm,the iterative search process of the particle swarm is accelerated,thus improving the global search capability of the algorithm and the disadvantage that the algorithm easily falls into local optimum.The multi-objective whale swarm algorithm is used to solve the optimization model to derive the Pareto optimal solution set,and the fuzzy subordination function is used to select the compromise solution as the final optimization solution.The accuracy and validity of the proposed algorithm and model are demonstrated by conducting example tests on the modified IEEE 39 and IEEE 30 node systems respectively.Finally,to address the uncertainty of wind power and photovoltaic output,a stochastic model of scenery output is established,based on the probability distribution functions of wind speed and light intensity,and scenario analysis techniques are used to obtain the typical output of scenery,transforming the uncertainty problem into an optimization problem with multiple scenarios of certainty.Based on the obtained scenic output,a two-layer coordinated optimization model for AC-DC hybrid grid with active and reactive power is established.The upper model takes the minimization of network loss as the objective and the charging and discharging power of the energy storage system as the control quantity to be optimized;the lower model constructs a multiobjective function for minimizing voltage deviation and network loss and takes the reactive power compensation parameters in the system as the control quantity to be optimized.The validity of the model proposed in this paper is verified through case studies. |
