Calculation of renewable energy hosting capacity of distribution network based on multi strategy improved adaptive manta ray foraging optimization

Abstract

With the increasing penetration of renewable energy in the distribution network, however, due to the randomness and volatility of renewable energy output, the large-scale grid connection of renewable energy will bring challenges to the safe and stable operation of the distribution network. The calculation of renewable energy hosting capacity of distribution network is not only beneficial to the construction of renewable clean and low-carbon power system, but also of great significance for the planners of power grid to carry out renewable energy planning. Renewable energy hosting capacity calculation involves many constraints, including a large number of nonlinear constraints, and the hosting capacity calculation model is very complex, lacking efficient solution algorithm. Aiming at the existing problems, the calculation model of renewable energy hosting capacity of distribution network is established based on full consideration of power quality, relay protection and thermal stability test. A multi strategy improved adaptive manta ray foraging optimization algorithm (MSAMRFO) is proposed to solve the hosting capacity model. MSAMRFO algorithm adopts half uniform initialization strategy, adaptive variable step size strategy and local convergence mutation strategy to improve manta ray foraging optimization algorithm (MRFO) algorithm. Finally, the effectiveness of the proposed model and method is verified by an example. The example shows that the MRFO algorithm after multi strategy improvement has outstanding effect both in convergence speed and algorithm stability.

Evaluation Method for Hosting Capacity of Rooftop Photovoltaic Considering Photovoltaic Potential in Distribution System

“…Existing methods for evaluating PV hosting capacity are categorized into the following four main types: (i) methods based on dynamic iteration and simulation [6][7][8]; (ii) methods based on mathematical optimization [9][10][11]; (iii) methods based on random scenarios simulation [12][13][14]; and (iv) methods based on comprehensive evaluation [15][16][17][18].…”

“…Alghamdi et al [9] adopted a decoupled linear power flow model (DLPF) to ensure fast calculation and used the particle swarm optimization algorithm (PSO) to solve the maximum photovoltaic access capacity of a radial distribution system. Yuan et al [10] established a renewable energy hosting capacity calculation model for distribution networks with consideration of power quality, relay protection, and thermal stability and proposed a multi-strategy improved adaptive manta ray foraging optimization algorithm (MSAMRFO) to solve the PV hosting capacity. Gomes et al [11] constructed a model of the maximum hosting capacity of a distributed generation system in a distribution network, used a genetic algorithm (GA) to obtain the maximum hosting capacity, and proved its validity in a modified IEEE 33-bus radial distribution system.…”