Optimal power flow (OPF) objective functions involve minimization of the total fuel costs of generating units, minimization of atmospheric pollutant emissions, minimization of active power losses and minimization of voltage deviations. In this paper, a fuzzy multi-objective OPF model is established by the fuzzy membership functions and the fuzzy satisfaction-maximizing method. The improved arti...

The paper presents a method for the co-optimization of energy storage systems allocation and line reinforcement in active distribution networks. objective is to guarantee capability an network follow dispatch plan by appropriately coping with high uncertainties loads stochastic renewable generation while ensuring secure operation grid minimizing power losses. proposed formulation relies on modi...

AC optimal power flow (AC-OPF) problems need to be solved more frequently in the future maintain stable and economic system operation. To tackle this challenge, a deep neural network-based voltage-constrained approach (DeepOPF-V) is proposed solve AC-OPF with high computational efficiency. Its unique design predicts voltages of all buses then uses them reconstruct remaining variables without so...

The global optimum of the optimal power flow (OPF) problem can be sought in various practical settings by adopting conic relaxations, such as second order cone programs (SOCPs) and semi-definite (SDPs). However, ZIP (constant impedance, constant current, power) exponential load models are not directly amenable with these solvers. Thus, mostly treated loads literature. In this letter, we propose...

An optimal power management solution is a potential tool to produce cost-effective and environmentally friendly supply using renewable energy sources (RESs) for the electrical network. Therefore, article introduces novel optimization algorithm inspired by vitality, namely, Manta Ray Foraging Optimization (MRFO), figure out both multi- single-objective problems of flow (OPF) incorporating stocha...

The efficient solution of the AC optimal power flow (OPF) for all cases and electrical grids is not guaranteed. Heuristics, approximations relaxations have been proposed aplenty, each with pros cons. This work proposes to solve OPF binary decision trees (BDTs). starts full feasible set an instance, and, iteratively, BDTs tighten constraints/bounds that set, improve occurring by median objective...

One of the most common issues in inverters are open-circuit faults (OPF). In this scenario, a proper fault-tolerant technique must be used to improve motor performance. Although basic modulation techniques normally preferred, paper proposes discontinuous pulse-width algorithm (HD-PWM) operate five-phase under single OPF. particular, loss equalization between remaining switches after fault occur...

In this paper variation of spot price and total profits of the generating companies’ through wholesale electricity trading are discussed with and without Central Generating Stations (CGS) share and seasonal variations are also considered. It demonstrates how proper analysis of generators’ efficiencies and capabilities, types of generators owned, fuel costs, transmission losses and settling pric...

Optimal power flow (OPF) study is conducted on a power system to achieve one of the following objectives: cost/loss minimization or available transfer capability (ATC) calculation in a deregulated environment. Distributed generation (DG) is a small source of electric power conversion from nonconventional energy sources and Hybrid DGs which often the most cost-effective and reliable way to produ...

Electricity network operators use computationally demanding mathematical models to optimize AC power flow (AC-OPF). Recent work applies neural networks (NN) rather than optimization methods estimate locally optimal solutions. However, NN training data is costly and current cannot guarantee or feasible This study proposes a robust approach, which starts with small amount of seed uses iterative f...