Abstract
The setting of protection parameters is vital to the large-scale application of reverse time overcurrent protection in the distribution networks. A fixed value optimization method of inverse time overcurrent protection for the distribution networks with distributed generation based on the improved Grey Wolf algorithm is proposed, which takes the protection action equation and the sensitivity, speed, and selectivity into consideration. Subsequently, four strategies, including good point set initialization, convergence factor exponential decay strategy, mutation strategy, and heuristic parameter determination strategy, are introduced to improve the Grey Wolf algorithm on the premise of retaining fewer adjustable parameters. Simulation results verify the feasibility and superiority of the proposed model in case of the two-phase and three-phase faults and discuss the influence of time differential on parameters setting and the research direction of algorithm optimization and engineering application.
Highlights
Research efforts mainly focused on two solutions: (1) Collecting the electric parameters information of the critical nodes and processing them comprehensively to improve the protection of adjacent coordination characteristics and promoting the sensitivity of protection [8, 9]: according to the control strategy and fault current output characteristics of the inverter distributed power supply, an adaptive current velocity break protection scheme for the distribution networks is proposed in [8], and the power reference and control parameters can be obtained based on the MMS service of IEC61850 communication protocol
Inverse time overcurrent protection is widely applied in the distribution network protection scheme due to the characteristic of the short protection action time and stable
In [11], a fixed value optimization model of inverse time overcurrent protection based on an improved particle swarm algorithm is established, which considers the uncertainty of fault line, fault type, and fault point location
Summary
Distributed generation (DG), such as wind power, photovoltaic, fuel cell, and energy storage, is increasing access to the distribution networks along with China’s nonignorable energy and environmental problems and the intelligent level of the power grid [1,2,3,4]. e widespread utilization of DG can ease the energy crisis and improve the utilization rate of energy and will change the original grid structure and affect the sensitivity of protection. erefore, the risk of refusing action or misoperation of the protection may be increased [5,6,7]. In [11], a fixed value optimization model of inverse time overcurrent protection based on an improved particle swarm algorithm is established, which considers the uncertainty of fault line, fault type, and fault point location. A protection setting optimization method of inverse time overcurrent for distribution networks with DG based on the improved Grey Wolf algorithm is proposed. E target function of the setting value optimization of the inverse time overcurrent protection can be described as follows: MB L. i 1 a 1 j 1 where M is the total number of the primary protection, B is the number of backup protection, and L represents the number of fault lines. E short circuit current and the action time of the distribution network inverse time overcurrent protection depend on the access points and fault locations. When the capacity of DG access is over a specific value, the above optimization problem may not find the solution, which means that the inverse time overcurrent protection is not suitable for this scenario, and other suitable protection types should be introduced
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