Objective: Reactive power compensation is crucial for enhancing fault ride-through capability in new energy field clusters, making the effective configuration of reactive power compensation devices increasingly important. This involves selecting compensation points and determining reactive power compensation capacity. Traditional site selection methods for reactive power compensation devices overlook the nonlinear characteristics of continuous power flow in the sending end system of the new energy field group and the impact of later compensation points on previous compensation points, resulting in inaccurate site selection. Methods: Considering the nonlinear characteristics of the sending end system of new energy field groups, based on the traditional first-order network loss reactive power sensitivity method, this study develops a second-order network loss reactive power sensitivity calculation method. To eliminate the influence of later compensation points on previous compensation points, this paper adopts the method of traversing each node. Firstly, the second-order network loss reactive power sensitivity of the current node is calculated, and then compared with the calculated sensitivity in a loop. After traversal, the compensation points are selected based on the sensitivity ranking of all nodes. To meet the fault ride-through requirements of the sending end system of new energy field groups and reduce the calculation consumption in optimizing the compensation capacity of reactive power compensation devices, based on the undervoltage area of low-voltage ride-through, a fault ride-through risk index for new energy field groups is proposed. The proposed index is developed in the context of low-voltage and high-voltage ride-through requirements for new energy sources such as photovoltaics and wind power. By scanning the faults in the sending end system of new energy field groups and calculating the fault ride-through risk index under different faults based on the time series voltage values, key fault sets are selected by sorting the fault ride-through risk index values under each fault, thereby reducing the flow sample data in capacity optimization. In terms of optimizing the capacity of reactive power compensation devices, an optimization model was established using the equal annual value method with the comprehensive investment cost of static var generator (SVG) and synchronous condenser (SC) and fault ride-through penalty as the optimization goal. In order to meet the timing voltage requirements of the sending end system of new energy field groups during fault ride-through, an optimization iterative algorithm for electromechanical transient simulation in the loop was designed. Through electromechanical transient simulation, the timing voltage is verified to meet the fault ride-through requirements. If the timing voltage does not meet the requirements, the initial value of the optimization model is updated with the optimized configuration capacity of reactive power compensation devices, and the next optimization step is carried out until the timing voltage requirements during fault ride-through were met. Results: During the verification of the calculation example, under the same compensation capacity, the system network loss increment and network loss reactive power sensitivity calculated using the traditional first-order network loss reactive power sensitivity method and the second-order network loss reactive power sensitivity method proposed in this paper were compared. Compared with the network loss increment obtained by power flow calculation, the method proposed in this paper calculates a smaller error in the network loss increment, and using the second-order network loss sensitivity correction method to select the position of the reactive power compensation device is more accurate. Four key faults were selected using the fault ride-through risk index. While optimizing the capacity of the reactive power compensation device, a comparison was made between the economic value of two configuration schemes: "SVG" and "SVG+SC". Conclusions: The results showed that the configuration scheme of "SVG+SC" can fully utilize the overvoltage suppression ability of SVG during fault recovery and the voltage support ability of SC during faults, thereby reducing the investment cost by 72.1 million yuan. This validates the feasibility and effectiveness of the reactive power compensation device capacity optimization method proposed in this paper.