• Energy Research

The appropriate control and management of reactive power is of great relevance in the electrical reliability, stability, and security of power grids. This issue is considered in order to increase system efficiency and to maintain voltage under the acceptable value range. In this regard, novel technologies as FACTS, renewable energies, among others, are varying conventional grid behavior leading to unexpected limit capacity reaching due to large reactive power flow. Thus, optimal planning of this must be considered. This paper proposes a new application for a simple and easy implementation optimization algorithm, called Rao-3, to solve the constrained non-linear optimal reactive power dispatch problem. Moreover, the integration of solar and wind energy as the most applied technologies in electric power systems are exploited. Due to the continuous variation and the natural intermittence of wind speed and solar irradiance as well as load demand fluctuation, the uncertainties which have a global concern are investigated and considered in this paper. The proposed single-objective and multi-objective deterministic/stochastic optimal reactive power dispatch algorithms are validated using three standard test power systems, namely IEEE 30-bus, IEEE 57-bus, and IEEE 118-bus. The simulation results show that the proposed optimal reactive power dispatch algorithms are superior compared with two recent algorithms (Artificial electric field algorithm (AEFA) and artificial Jellyfish Search (JS) algorithm) and other optimization algorithms used for solving the same problem.

This paper is concerned with an imperative operational problem, called the optimal power flow (OPF), which has several technical and economic points of view with respect the environmental concerns. This paper proposes a multiple-objective optimizer NSWOA (non-dominated sorting whale optimization algorithm) for resolving single-objective OPFs, as well as multi-objective frameworks. With a variety of technical and economic power system objectives, the OPF can be formulated. These objectives are treated as single- and multi-objective OPF issues that are deployed with the aid of the proposed NSWOA to solve these OPF formulations. The proposed algorithm modifies the Pareto ranking and analyzes the optimum compromise solution based on the optimal Euclidian distances. This proposed strategy ensures high convergence speed and improves search capabilities. To achieve this study, an IEEE 30-bus (sixth-generation unit system) is investigated, with eight scenarios studied that highlight technical and environmental operational needs. When compared to previous optimization approaches, the suggested NSWOA achieves considerable techno-economic improvements. Additionally, the statical analyses are carried out for 20 separate runs. This analysis proves the high robustness of the proposed NSWOA at low levels of standard deviation.

This paper presents the importance of load management methodology (LM) and helps in clarifying the difference between load management versus demand-side management (DSM), as LM is a crucial method of controlling the loads especially in peak periods, to prevent tripping. It was found that the previous researches focused on the dual tariff meters to force and motivate the consumer to change the demand time which was a gleam in overcoming the phenomena. However, the dilemma of the DSM was relying mainly on the consumer, who has to change the time of his needs. Therefore, it is difficult to be controlled. Consequently, they cannot find effective feedback as well. On the other hand, LM relies only on the designer or service provider in re-distributing loads according to the load behavior studies (time, location, and type of user) without depending on the consumer in solving the phenomena of extreme fluctuations of loads on the electrical equipment. In this paper, the second methodology is by the service provider, it is going to be handled and discussed by Selecting medium voltage (MV) feeders, re-distribute loads equally, and variously on transformer preventing unifying load which causes overloaded transformer on one period rather than the other. Consequently, it will lead to protect electrical equipment from no-load or overload effects, selecting the exact size. That will improve the economic status and will lead to a stable, balanced system, besides reduce heat island effects and prevent load shedding caused by sudden overloading. The model was created by using DIgSILENT power factory software.

This paper presents an optimized design of an off-grid microgrid capable of fulfilling the year-round power demands of a remote area in Egypt. The proposed system combines photovoltaic, Wind Turbine (WT), backed by batteries, and biomass technologies to ensure consistency and eco-friendliness with fewer pollutants. A comprehensive analysis using HOMER Pro software was utilized to identify the optimum design, considering the energy demand, renewable resource availability, and net present cost (NPC) of the system. The results show that the optimal design includes a solar Photovoltaic (PV) system, WT, backed up by batteries, and a stand-by biomass generator (BIOMG). The design can significantly decrease reliance on conventional energy sources and promote the growth of renewable energy in the region. This study is considered the cheapest model in this configuration (PV, WT, Batteries, BIOMG) if compared to previous studies in the same location through a total NPC of USD3,483,519.00and the best cost of energy (COE) of USD0.118. Additionally, the proposed system decreases emissions that contribute to global warming with a GHG of 28,516 tons/year. A sensitivity analysis of the uncertainty of renewable resources and economics has been conducted. The sensitivity analysis illustrates the variety of results.

In this paper, a modified version of a recent optimization algorithm called gradient-based optimizer (GBO) is proposed with the aim of improving its performance. Both the original gradient-based optimizer and the modified version, MGBO, are utilized for estimating the parameters of Photovoltaic models. The MGBO has the advantages of accelerated convergence rate as well as avoiding the local optima. These features make it compatible for investigating its performance in one of the nonlinear optimization problems like Photovoltaic model parameters estimation. The MGBO is used for the identification of parameters of different Photovoltaic models; single-diode, double-diode, and PV module. To obtain a generic Photovoltaic model, it is required to fit the experimentally obtained data. During the optimization process, the unknown parameters of the PV model are used as a decision variable whereas the root means squared error between the measured and estimated data is used as a cost function. The results verified the fast conversion rate and precision of the MGBO over other recently reported algorithms in solving the studied optimization problem.

The International Marine Organization (IMO) regulations forcing shipbuilders to use electric ships to reducing pollution emitted from ship engines. Renewable energy resources are the perfect solution to solve this issue. The ship’s hybrid energy power system consists of several non-homogeneous energy resources diesel generator, renewable energy source or more, energy-storing system, and may hydrogen source as fuel cells. The EMS manages and controls the balance between the different types of sources and loads demand to ensure system stability and dependability. In this paper, energy management strategy (EMS) for fuel cell and battery hybrid systems is an essential property of controlling power flow between sources. A crucial ingredient of an intelligent control strategy is to manage the flow of a hybrid system corresponding to the changing of the load demand and battery state of charge (SoC) using the ANFIS/Simulink toolbox implements a case study architecture. This paper proposes a hybrid energy source for use in a naval ship’s silent mode of operation while looking for submarines with a low acoustic signature based on adaptive neuro-fuzzy procedures. The main objective of this analysis is to investigate the efficiency of the proposed system preserving compared with practical results obtained from previous work. These studies provide valuable understandings into hybrid power systems’ flow of EMS on the marine field.