Mostafa Esmaeilbeig

TL;DR: Genetic algorithm has been employed to solve power flow equations, and generating scaling factor (GSF) has also been used for simultaneous calculations of power passing through in transmission lines so that by gaining some knowledge on the capacity of transmission lines, the electricity price could be determined by uniform market pricing or LMP methods.

TL;DR: The proposed model includes a series of probabilistic scenarios used to consider the uncertainty of wind/solar generation and determines the status of VPP units based on the best-case scenarios and the VPP profitability calculated for the day-ahead energy and reserve market.

TL;DR: Simulation results show that the maximum scales of horizontal components and the energy stored in these components strongly depend on the fault resistance, type of fault, fault angle and fault location, and results indicate that the proposed algorithm can estimate fault distance depending on thetype of fault in different conditions.

TL;DR: In this article, a GA-GSF algorithm is used to identify the network's weaknesses such as the lines that have reached their maximum capacity, and then by considering three terms and two scenarios condition of the buses connected to the filled lines will be discussed and extract the best places for installing DG on the network, and finally, the algorithm output including place and optimal size of DG unit in the network is minimized by line congestion and LMP, and DG installation is economically justified.

TL;DR: In this article, the authors present a method for calculating the optimal size and place of DG in the distribution network based on nodal pricing, which is done to maximize the profits of distribution companies that have used DG in their network to meet several advantages.