• Energy Research

The transition to a low carbon society is dependent on renewable energy-based electrification. Nevertheless, energy programs have resulted in growing societal polarization in several regions. Therefore, around the globe, government and legislative authorities at the local, regional, national, and international levels are highly concerned about the environmental impacts and risk factors that influence the energy paradigm. Thus, to minimize and/or limit the environmental insecurity issues, the world needs swift and effective actions to secure the climate for a better tomorrow. Moreover, there is a dire need to look for new energy alternatives, along with reducing the complete dependence on petro-based energy sources. Keeping this burning issue in mind, herein, an effort has been made to present the potential of several renewable energy sources, including wind-based renewable energy, solar-based renewable energy, hydro-based renewable energy, and biomass-based renewable energy. Following a brief introduction of energy-related problems and opportunities, a comparative overview is given to renewable vs. non-renewable energy sources. Then, several renewable energy sources, including wind, solar, hydro, and biomass, along with the worldwide energy capacity of each energy source are given with suitable examples and statistics. Finally, risk factors, concluding remarks, and future guidelines are discussed towards the end.

For an efficient energy harvesting by the PV/thermoelectric system, the maximum power point tracking (MPPT) principle is targeted, aiming to operate the system close to peak power point. Under a uniform distribution of the solar irradiance, there is only one maximum power point (MPP), which easily can be efficiently determined by any traditional MPPT method, such as the incremental conductance (INC). A different situation will occur for the non-uniform distribution of solar irradiance, where more than one MPP will exist on the power versus voltage plot of the PV/thermoelectric system. The determination of the global MPP cannot be achieved by conventional methods. To deal with this issue the application of soft computing techniques based on optimization algorithms is used. However, MPPT based on optimization algorithms is very tedious and time consuming, especially under normal conditions. To solve this dilemma, this research examines a hybrid MPPT method, consisting of an incremental conductance (INC) approach and a moth-flame optimizer (MFO), referred to as (INC-MFO) procedure, to reach high adaptability at different environmental conditions. In this way, the combination of the two different algorithms facilitates the utilization of the advantages of the two methods, thereby resulting in a faster speed tracking with uniform radiation distribution and a high accuracy in the case of a non-uniform distribution. It is very important to mention that the INC method is used to track the maximum power point under normal conditions, whereas the MFO optimizer is most relevant for the global search under partial shading. The obtained results revealed that the proposed strategy performed best in both of the dynamic and the steady-state conditions at uniform and non-uniform radiation.

Recent developments have increased the availability and prevalence of renewable energy sources (RESs) in grid-connected microgrids (MGs). As a result, the operation of an MG with numerous RESs has received considerable attention during the past few years. However, the variability and unpredictability of RESs have a substantial adverse effect on the accuracy of MG energy management. In order to obtain accurate outcomes, the analysis of the MG operation must consider the uncertainty parameters of RESs, market pricing, and electrical loads. As a result, our study has focused on load demand variations, intermittent RESs, and market price volatility. In this regard, energy storage is the most crucial facility to strengthen the MG’s reliability, especially in light of the rising generation of RESs. This work provides a two-stage optimization method for creating grid-connected MG operations. The optimal size and location of the energy storage are first provided to support the hosting capacity (HC) and the self-consumption rate (SCR) of the RESs. Second, an optimal constrained operating strategy for the grid-connected MG is proposed to minimize the MG operating cost while taking into account the optimal size and location of the energy storage that was formerly determined. The charge–discharge balance is the primary criterion in determining the most effective operating plan, which also considers the RES and MG limitations on operation. The well-known Harris hawks optimizer (HHO) is used to solve the optimization problem. The results showed that the proper positioning of the battery energy storage enhances the MG’s performance, supports the RESs’ SCR (reached 100% throughout the day), and increases the HC of RESs (rising from 8.863 MW to 10.213 MW). Additionally, when a battery energy storage system is connected to the MG, the operating costs are significantly reduced, with a savings percentage rate of 23.8%.

Solar photovoltaic (PV) cell modeling is crucial to understanding and optimizing solar energy systems. While the single-diode model (PVSDM) is commonly used, the double-diode model (PVDDM) offers improved accuracy at a reasonable level of complexity. However, finding analytical closed-form solutions for the current-voltage (I-U) dependency in PVDDM circuits has remained a challenge. This work proposes two novel configurations of PVDDM equivalent circuits and derives their analytical closed-form solutions. The solutions are expressed in terms of the Lambert W function and solved using a special transcendental function approach called Special Trans Function Theory (STFT). The accuracy of the proposed equivalent circuits is demonstrated on two solar cells/modules, RTC-F and MSX-60, showing equal or better performance than the standard PVDDM equivalent circuit. Further testing on a commercial solar panel under different irradiance and temperature conditions confirms the applicability of the proposed models. To address the parameter estimation problem, a novel metaheuristic algorithm, the chaotic honey-badger algorithm, is developed and evaluated. The results obtained validate the accuracy and practicality of the proposed PVDDM equivalent circuit configurations.

Low-frequency oscillations are an inevitable phenomenon of a power system. This paper proposes an Ant lion optimization approach to optimize the dual-input power system stabilizer (PSS2B) parameters to enhance the transfer capability of the 400 kV line in the North-West region of the Ethiopian electric network by the damping of low-frequency oscillation. Double-input Power system stabilizers (PSSs) are currently used in power systems to damp out low-frequency oscillations. The gained minimum damping ratio and eigenvalue results of the proposed Ant lion algorithm (ALO) approach are compared with the existing conventional system to get better efficiency at various loading conditions. Additionally, the proposed Ant lion optimization approach requires minimal time to estimate the key parameters of the power oscillation damper (POD). Consequently, the average time taken to optimally size the parameters of the PSS controller was 14.6 s, which is pretty small and indicates real-time implementation of an ALO developed model. The nonlinear equations that represent the system have been linearized and then placed in state-space form in order to study and analyze the dynamic performance of the system by damping out low-frequency oscillation problems. Finally, conventional fixed-gain PSS improves the maximum overshoot by 5.2% and settling time by 51.4%, but the proposed optimally sized PSS employed with the ALO method had improved the maximum overshoot by 16.86% and settling time by 78.7%.

The resistance–capacitance (RC) model is one of the most applicable circuits for modeling the charging and discharging processes of supercapacitors (SCs). Although this circuit is usually used in the electric and thermal investigation of the performance of SCs, it does not include leakage currents. This paper presents exact analytical formulas of leakage-current-based supercapacitor models that can be used in industrial applications, i.e., constant-power-based applications. In the proposed model, current and voltage are represented as a solution of nonlinear equations that are solved using the standard Newton method. The proposed expressions’ accuracy is compared with the results obtained using traditional numerical integration methods with leakage current formulation and other methods, found in the literature, with no leakage current formulation. The results confirm that including leakage current represents a more accurate and realistic manner of modeling SCs. The results show that the derived expressions are precise, allowing the generation of results that closely match those obtained using traditional numerical-based methods. The derived expressions can be used to investigate SCs further and achieve more accurate and efficient regulation and control of SCs in different applications.

La protección diferencial del transformador de potencia puede enfrentar un mal funcionamiento en una auténtica discriminación entre irrupción y fallas internas. Para hacer frente a este último mal funcionamiento, se propone un nuevo algoritmo de dos etapas basado en el contenido de fase de la señal de corriente de los transformadores de corriente (CT). El algoritmo propuesto está diseñado en función del hecho de que el ángulo de fase fundamental de una señal de falla idealmente permanece constante durante la falla. Sin embargo, durante los casos de irrupción, el ángulo de fase varía. Además, durante la falla interna, los ángulos de fase de las señales de corriente de los TC están en fase, mientras que durante la falla externa, los ángulos de fase de las señales de corriente de los TC están desfasados 180°. En la primera etapa, el algoritmo propuesto calcula los ángulos de fase fundamentales de las señales actuales de los TC utilizando mínimos cuadrados recursivos (LMR) modificados por subciclo. Después, se emplea el residuo medio normalizado (RMN) para medir la distancia entre los ángulos de fase estimados de las corrientes de la TC. Los algoritmos de LMR y RMN requieren muestras limitadas (es decir, 10 y 5 muestras respectivamente) para ejecutar sus cálculos. La evaluación del rendimiento con señales de corriente registradas simuladas y experimentales muestra la capacidad del método propuesto para discriminar las fallas internas de las corrientes de irrupción y falla externa. La protection différentielle du transformateur de puissance peut être confrontée à un dysfonctionnement dans la discrimination authentique entre les défauts internes et les défauts internes. Pour remédier à ce dernier dysfonctionnement, un nouvel algorithme en deux étapes basé sur le contenu en phase du signal de courant des transformateurs de courant (CT) est proposé. L'algorithme proposé est conçu sur le fait que l'angle de phase fondamental d'un signal de défaut reste idéalement constant pendant le défaut. Cependant, en cas d'appel, l'angle de phase varie. En outre, pendant le défaut interne, les angles de phase des signaux de courant des TC sont en phase tandis que pendant le défaut externe, les angles de phase des signaux de courant des TC sont déphasés de 180°. Dans la première étape, l'algorithme proposé calcule les angles de phase fondamentaux des signaux actuels des TC à l'aide des moindres carrés récursifs modifiés par sous-cycle (LMR). Ensuite, le résidu moyen normalisé (RMN) est utilisé pour mesurer la distance entre les angles de phase estimés des courants du TC. LES LMR et les algorithmes de RMN nécessitent des échantillons limités (soit 10 et 5 échantillons respectivement) pour exécuter leurs calculs. L'évaluation des performances avec des signaux de courant enregistrés simulés et expérimentaux montre la capacité de la méthode proposée à discriminer les défauts internes des courants d'appel et de défaut externes. Power transformer differential protection may confront mal-functioning in authentic discrimination between inrush and internal faults. To tackle the latter mal-functioning, a new two-stages algorithm based on phase content of the current signal of the current transformers (CTs) is put forward. The proposed algorithm is designed based on the fact that the fundamental phase angle of a fault signal ideally remains constant during the fault. However, during inrush cases, the phase angle varies. Also, during the internal fault, the phase angles of the current signals of CTs are in phase while during the external fault, the phase angles of the current signals of CTs are 180° out of phase. In the first stage, the proposed algorithm calculates the fundamental phase angles of the current signals of the CTs using sub-cycle modified recursive least squares (MRLS). Afterward, normalized mean residue (NMR) is employed to measure distance between the estimated phase angles of the CT's currents. MRLS and NMR algorithms require limited samples (i.e. 10 and 5 samples respectively) for executing their calculations. Performance evaluation with simulated and experimental recorded current signals shows the ability of the proposed method in discrimination of the internal faults from inrush and external fault currents. قد تواجه الحماية التفاضلية لمحول الطاقة سوء الأداء في التمييز الحقيقي بين الاندفاع والأعطال الداخلية. لمعالجة سوء الأداء الأخير، يتم طرح خوارزمية جديدة على مرحلتين بناءً على محتوى المرحلة للإشارة الحالية لمحولات التيار (CTs). تم تصميم الخوارزمية المقترحة بناءً على حقيقة أن زاوية الطور الأساسية لإشارة الخطأ تظل ثابتة بشكل مثالي أثناء الخطأ. ومع ذلك، خلال حالات الاندفاع، تختلف زاوية الطور. أيضًا، أثناء العطل الداخلي، تكون زوايا الطور لإشارات التيار لـ CTs في الطور بينما أثناء العطل الخارجي، تكون زوايا الطور لإشارات التيار لـ CTs 180درجة خارج الطور. في المرحلة الأولى، تحسب الخوارزمية المقترحة زوايا الطور الأساسية للإشارات الحالية لـ CTs باستخدام المربعات الصغرى التكرارية المعدلة للدورة الفرعية (MRLS). بعد ذلك، يتم استخدام بقايا متوسطة معيارية (NMR) لقياس المسافة بين زوايا الطور المقدرة لتيارات CT. تتطلب خوارزميات MRLS و NMR عينات محدودة (أي 10 و 5 عينات على التوالي) لتنفيذ حساباتها. يُظهر تقييم الأداء مع إشارات التيار المسجلة المحاكاة والتجريبية قدرة الطريقة المقترحة في تمييز الأعطال الداخلية من الاندفاع وتيارات الأعطال الخارجية.

This paper presents a novel contribution of a low complexity control scheme for voltage control of a dynamic voltage restorer (DVR). The scheme proposed utilizes an error-driven proportional-integral-derivative (PID) controller to guarantee better power quality performance in terms of voltage enhancement and stabilization of the buses, energy efficient utilization, and harmonic distortion reduction in a distribution network. This method maintains the load voltage close to or equal to the nominal value in terms of various voltage disturbances such as balanced and unbalanced sag/swell, voltage imbalance, notching, different fault conditions as well as power system harmonic distortion. A grasshopper optimization algorithm (GOA) is used to tune the gain values of the PID controller. In order to validate the effectiveness of the proposed DVR controller, first, a fractional order PID controller was presented and compared with the proposed one. Further, a comparative performance evaluation of four optimization techniques, namely Cuckoo search (CSA), GOA, Flower pollination (FBA), and Grey wolf optimizer (GWO), is presented to compare between the PID and FOPID performance in terms of fault conditions in order to achieve a global minimum error and fast dynamic response of the proposed controller. Second, a comparative analysis of simulation results obtained using the proposed controller and those obtained using an active disturbance rejection controller (ADRC) is presented, and it was found that the performance of the optimal PID is better than the performance of the conventional ADRC. Finally, the effectiveness of the presented DVR with the controller proposed has been assessed by time-domain simulations in the MATLAB/Simulink platform.