Today, electricity tariffs play an essential role in the electricity retail market as they are the key factor for the decision-making of end-users. Additionally, tariffs are necessary for increasing competition in the electricity market. They have a great impact on load energy management. Moreover, tariffs are not taken as a fixed approach to expense calculations only but are influenced by many other factors, such as electricity generation, transmission, distribution costs, and governmental taxation. Thus, electricity pricing differs significantly between countries or between regions within a country. Improper tariff calculation methodologies in some areas have led to high-power losses, unnecessary investments, increased operational expenses, and environmental pollution due to the non-use of available sustainable energy resources. Due to the importance of electricity tariffs, the authors of this paper have been inspired to review all electricity tariff designs used worldwide. In this paper, 103 references from the last ten years are reviewed, showing a detailed comparison between different tariff designs and demonstrating their main advantages and drawbacks. Additionally, this paper reviews the utilized electricity tariffs in different countries, focusing on one of the most important countries in the Middle East and North Africa regions (Egypt). Finally, some recommended solutions based upon the carried-out research are discussed and applied to the case study for electricity tariff improvement in this region. This review paper can help researchers become aware of all the electricity tariff designs used in various countries, which can lead to their design improvements by using suitable software technologies. Additionally, it will increase end-users’ awareness in terms of deciding on the best electricity retail markets as well as optimizing their energy usage.

Distributed generation (DG) systems achieve an important role in electrical power networks due to their technical and economic benefits. This paper presents a novel application of the Crow Search Algorithm (CSA) with purpose of enhancing the performance of an inverter-based DG system. The control strategy of the inverter is based on a vector cascaded control scheme, which relies on the Proportional plus Integral (PI) controller. The proposed CSA is utilized to fine tune the PI controller parameters. The response surface methodology (RSM) is used to create the objective and constraint function of the optimization problem. The validity of the proposed control strategy is extensively verified using the simulation results, which are performed using PSCAD/EMTDC environment. These simulation results are investigated under different operating conditions such as 1) transition of the system from grid connected to islanded mode of operation, and 2) subject the system to a single line to ground fault in the autonomous mode. The effectiveness of the proposed controller is verified by comparing its results with that obtained using the genetic algorithm-based PI controller.

This paper discusses the importance of microgrids in power systems and introduces a new method for enhancing their performance by improving the transient voltage response in the face of disturbances. The method involves using a hybrid optimization approach that combines driving training-based and particle swarm optimization techniques (HDTPS). This hybrid approach is used to fine-tune the system’s cascaded control scheme parameters, based on proportional–integral–accelerator (PIA) and proportional–integral controllers. The optimization problem is formulated using a central composite response surface methodology (CCRSM) to create an objective function. To validate the suggested control methodology, PSCAD/EMTDC software is used to carry out the simulations. The simulations explore various scenarios wherein the microgrid is transformed into an islanded system and is subjected to various types of faults and load changes. A comparison was made between the two proposed optimized controllers. The simulation results demonstrate the effectiveness of using a PIA-optimized controller; it improved the microgrid performance and greatly enhanced the voltage profile. In addition, the two controllers’ gains were optimized using only PSO to ensure that the outcomes of the HDTPS model demonstrated the same results. Finally, a comparison was made between the two optimization techniques (HDTPS and PSO); the results show a better impact when using the HDTPS model for controller optimization.

The Microgrid achieve nowadays a great importance in providing energy to isolated areas. This paper demonstrates a new application of the Artificial Neural Networks (ANN) for online modification of the inverter based microgrid operation. A vector cascaded control technique is utilized as an inverter control strategy, which depends on the Proportional plus Integral (PI) controller. The suggested ANN is used to adapt the controller constants instantly. The ANN is simulated using MATLAB program. The input training samples of the ANN is obtained by carrying out different working settings simulated by PSCAD/EMTDC program. The optimal output training data fed to ANN is obtained by finding the optimal PI constants utilizing Evaporation Rate Water Cycle Algorithm (ERWCA). The utilized objective optimization problem used by the ERWCA is created by the Response Surface Methodology (RSM). The working scenarios included in this paper are 1) system conversion from grid connected mode to stand alone one, 2) system exposure to three lines to earth fault in the stand alone mode and 3) The steady state operation at grid connected mode.

Decentralized Energy Generation Systems (DEG) acquire their vital role in power systems owing to their practical and cost effectiveness advantages. This paper illustrates a new metaheuristic application called the Evaporation Rate based Water Cycle Algorithm (ER-WCA) for improving the inverter based (DEG) system operation. The controlling methodology of the inverter applied is the vector cascaded control technique, that depends on the Proportional-Integral (PI) controller. The optimization of the PI controller constants is carried out using ER-WCA method. The optimization problem target and constraint functions are created by the Response Surface Methodology (RSM). The validation of the suggested control technique is checked by utilizing the simulation outcomes, which are carried out by PSCAD/EMTDC program. These simulations outcomes are tested under various working settings as an example 1) system conversion from network connected to stand alone scenario, and 2) the system exposure to three lines to earth fault in the stand alone mode The adequacy of the suggested controller is proved by carrying out a comparison between its outcomes with that utilizing the Genetic Algorithm (GA) technique.