Jordan Journal of Energy <p><strong>Jordan Journal of Energy (JJE)</strong><br />JJE aims to provide a highly readable and valuable addition to the literature in the field of energy to reflect the evolving needs of the energy sector. All energy-related research is in scope, including interdisciplinary and multidisciplinary studies. The journal will serve as an indispensable reference tool for years to come. The journal’s scope includes all new theoretical and experimental findings that cover a wide range of topics in energy. JJE aims to strengthen relations between the energy sector, research laboratories, and universities. All the manuscripts must be prepared in English and are subject to a rigorous and fair peer-review process.</p> <p><img src="" alt="" width="1510" height="382" /></p> en-US (Jordan journal of Energy (JJE)) (Deanship of Scientific Research) Tue, 06 Sep 2022 08:01:53 +0200 OJS 60 Adaptive Overcurrent Protection Scheme for Power Systems with High Penetration of Renewable Energy Recourses <p>Due to high penetration of renewable energy recourses in the existing distribution network, the protection system faced a new challenge. This paper presents an adaptive overcurrent protection scheme for active distribution network ADN enhanced by real time measurement gathered from micro phasor measurement unit <em>μ</em>PMU.The <em>μ</em>PMU measurement is used in this paper to estimate the network topology of the ADN. The proposed scheme has been tested and validated using MATLAB programing environment. The simulation results demonstrate the effectiveness of the proposed adaptive protection scheme.</p> Khaled Al-Maitah, Batool AL-Khreisat Copyright (c) 2022 Jordan Journal of Energy Wed, 24 Aug 2022 00:00:00 +0200 Islanding Detection Method Based Artificial Neural Network <p><em>This paper presents a new islanding detection technique based on an artificial neural network (ANN) for a doubly fed induction wind turbine (DFIG). This technique takes advantage of ANN as pattern classifiers. Five different ANN systems are presented in this paper based on various inputs: three phase power, phase voltage, phase current, neutral voltage, and neutral current. An ANN structure is trained for each input, and the comparison between the different structures is presented. Feedforward ANN structures are used for the five systems. Three different learning algorithms are used: backpropagation and two artificial optimization techniques: Genetic Algorithm (GA) and Cuckoo optimization algorithm. For each method in each training technique, the results and the cost function are presented. The comparison of different inputs different algorithms is conducted. MATLAB 2020a is used to simulate the ANN structure and code the training algorithms. A detailed discussion of the input sample rate has also been manipulated to make the computational burden a factor in assessing the performance.</em></p> Mohammad M. Al-Momani, Seba F. Al-Gharaibeh, Ali S. Al-Dmour, Ahmed Allaham Copyright (c) 2022 Jordan Journal of Energy Wed, 24 Aug 2022 00:00:00 +0200 Distributed Energy Resources Electrical Systems: Current status and Future prospective <p><em>Distributed generation (DG) is an approach that utilizes small scale technologies to generate electricity close to the consumer side. Generally, DG can provide high reliability, high security, low cost electricity, and less environment impact. This paper gives an overview of some of the most significant issues related to the distributed generation (DG). It discusses different aspects of DG, such as definitions, technologies, motivation for moving to DG, some drawbacks associated with the centralized systems which have led to DG. DGs challenges, standards and polices are also presented. In addition, the economic impact and a price comparison between central power plants and DGs are discussed. Also a case study was conducted in order to study the impact of using distributed generations in Edmonton downtown. Three distributed generations, combustion turbine types with 25 MW capacities each have been implemented in Edmonton power system. The total cost estimations have been studied in this case, and the results have revealed that this type of distributed generation is inexpensive and more economic compared with price from the utility. It was estimated from the calculation that the price for the energy is about ¢6.27/kWh while the current electricity price from the utility is ¢8.561/kWh, for long term estimation it is found that the proposed CTs in this project has 11 years for a payback period, after that the project start earning money which is relatively good and wroth investment. The second part of the study analyses the impact of DGs on the system losses using Power-World software, and the result have proven that the loss is significantly decreases when the DG systems are in operation, hence DGs help reducing the costs that associated with the system’s losses.</em></p> khaled Alawasa Copyright (c) 2022 Jordan Journal of Energy Wed, 24 Aug 2022 00:00:00 +0200 Experimental investigation of the effect of using different refrigerant gases on refrigerator performance <p>An experimental study of the performance of a refrigerator using two refrigerants R-134a and R-410A has been conducted. The R-134a was the original design refrigerant, while the R-410A was the drop-in refrigerant. The study was performed on a small refrigerator charged with each refrigerant alone at nearly the same ambient conditions. Temperatures at various locations in the refrigeration system were measured using thermocouples during the running of the experiments, and the data collected were processed into performance refrigeration parameters. The results have indicated that both the refrigeration capacity and coefficient of performance were remarkably higher for the refrigerant R-410a by about 23 and 24%, respectively.</p> Saad alrwashdeh, Handri Ammari, Mahmoud Hammad, Heening Markotter Copyright (c) 2022 Jordan Journal of Energy Wed, 24 Aug 2022 00:00:00 +0200 Global-Binary Algorithm; New Optimal Phasor Measurement Unit Placement Algorithm <p><em>This paper proposes a new algorithm for the optimal placement of the phasor measurement unit. The proposed algorithm is based on the concept of finite space solution of any binary problem. This algorithm has considered all possible cases; therefore, the possibility of obtaining a global solution is very high. The large system is divided into several subsystems. The buses (transmission lines) connected between the subsystems are called interconnected buses (lines). The proposed algorithm is implemented through two steps. First step identifies the optimal placement for each subsystem by checking on all possible solutions, the overall optimal placement for the entire system is gathered in the second step. Finally, all possible placements of the phasor measuring units with the optimal numbers are identified to select the best placement based on the user applications. In this work, the Jordanian power system is considered as a case study to validate the proposed algorithm. Four algorithms in the literature are used for the comparison using different IEEE test systems. The algorithm is computed in MATLAB 2020a.</em></p> Mohammad M. Al-Momani, Seba F. Al-Gharaibeh, Khaled Al-Awasa, Amneh Almbaideen, Ahmed Allaham Copyright (c) 2022 Jordan Journal of Energy Wed, 24 Aug 2022 00:00:00 +0200