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Reliance on renewable energy is increasing, and generating units are being added to the network. Since renewable power fluctuates greatly, the frequency deviation of the grid becomes a crucial problem with access to renewable power generation. The fluctuation of the renewable power output of the system puts forward a higher demand for load frequency control of the power grid to increase the penetration of renewable power in the system. PID controller has proven its effectiveness for the LFC due to its simple structure and clear concept. In this article, the virtual synchronous generator is introduced and a fuzzy self-tuned PID controller is proposed for inertia control. The proposed controller is implemented in light of the significant integration of renewable energy and virtual inertia. The efficacy of the suggested controller is evaluated against the traditional PID controller for the Egyptian Power System as a case study under various load disturbance scenarios. The control technique is employed for variable loads with photovoltaic and wind turbine generation systems. Three instances of load changes are studied and the controller design is performed based on grey wolf optimizer in each case. The overshot and integral time absolute error are considered as comparison measures. The new contribution is applied to the proposed controller for the grid and virtual inertia. In the case of many load variations imposed, the disturbances of residential and industrial loads varied from 0.05, 0.01, 0.15, and 0.02 pu. The maximum overshoot is 0.005 for the proposed controller and 0.0078 for the classic PID controller. The integral time absolute error is 0.06429 for the proposed controller and 0.11481 for the classic PID controller. The results demonstrate the efficacy of the proposed controller for inertia control with high penetration of renewable energy. The results show that the proposed fuzzy self-tuned PID controller has an overshot less than the classical PID controller by 25% and integral time absolute error by 45%. These results show that the use of the proposed fuzzy self-tune controller for the grid and inertia gave a better performance in terms of the overshot value and the integral time absolute error. [ABSTRACT FROM AUTHOR]

This research presents a new method for controlling the maximum power point tracking (MPPT) of solar photovoltaic (PV) systems that are partially shaded. The proposed approach uses a neural network and an adaptive terminal sliding mode controller (NN-ATSMC) to ensure that the PV system operates at optimal performance under uncertain conditions. The NN-ATSMC controller is applied to a DC/DC boost converter to drive the system to the maximum power point (MPP). This method ensures that the error will converge in finite time and the chattering effect will be minimized without losing robustness under various disturbances and load conditions. Simulation results show that the proposed NN-ATSMC controller performs better than other types of controllers existing in the literature, such as a sliding mode controller (SMC) and a conventional proportional-integral controller (CPI). For the validation of the proposed controller, control hardware-in-the-loop (C-HIL) experimental implementation has been carried out through Texas Instruments digital signal processor C2000. The experimental results show the viability of real-time implementation and verify the effectiveness of the proposed method, which ensures the low cost and stability of the standalone PV systems. [ABSTRACT FROM AUTHOR]

To operate photovoltaic (PV) systems efficiently, the maximum available power should always be extracted. However, due to rapidly varying environmental conditions such as irradiation, temperature, and shading, determining the maximum available power is a time-varying problem. To extract the maximum available power and track the optimal power point under these varying environmental conditions, maximum power point tracking (MPPT) techniques are proposed. The application of MPPT for extracting maximum power plays a crucial role in developing efficient PV systems. These MPPT techniques face several issues and limitations, particularly during partial shading conditions caused by non-uniform environmental conditions. Researchers have been focusing more on mitigating the partial shading condition in PV systems for the last few years due to the need to improve power output and efficiency. This paper provides an overview of MPPTs proposed in the literature for uniform and non-uniform environmental conditions broadly categorized as MPPT-based and circuit-based methods. The MPPT-based methods are classified as conventional, soft computing, and hybrid techniques. A critical analysis of each approach regarding tracking speed, algorithm complexity, and dynamic tracking under partial shading is discussed. The literature shows hybrid strategies provide fast-tracking speed and are efficient with a tracking efficiency of around 99% compared to conventional methods; however, their design and practical implementation are complex. This comprehensive review of MPPT methods aims to provide power utilities and researchers with a reference and guideline to select the best MPPT method for normal operation and partially shaded PV systems based on their effectiveness and economic feasibility. [ABSTRACT FROM AUTHOR]

The current work presents a mathematical model to study the performance of a multi-effect desalination system of parallel cross feed arrangement with thermal vapor compression (MED-PCF-TVC). Using energy and mass conservation laws, the system performance is evaluated to determine performance ratio among other operational parameters. Heat transfer analysis is performed to estimate specific heat transfer area. Furthermore, a multi-objective optimization method is used to find the maximum performance ratio (PR) and minimum specific heat transfer area (sA) for MED-PCF-TVC with (N) effects. This study investigates two cases of multi-objective optimization. The first case is performed to find the optimum PR at minimum sA with priority to minimize sA, while the second case considers the optimum PR at minimum sA with priority to maximize PR. Results show that for MED system with "N" number of effects, the optimum PR is obtained when the ejector is located after effect [(N/2) – 1] for the first case. For the second case, the optimum PR is attained when the ejector is located after [(N/2) + 1] effect. In addition, the optimum motive steam pressure where the PR is maximized and sA is minimized is found to be 1500 kPa for each case and each MED system. [ABSTRACT FROM AUTHOR]

Water desalination using the membrane distillation (MD) process is an emerging technique that has the potential for future commercialization. In this study, the performance of a new design multistage water-gap membrane distillation module is experimentally investigated for possible scaling up and commercialization. A new compact design is proposed for enhanced productivity, low energy consumption, and therefore low freshwater production cost. The variations of permeate flux, specific thermal energy consumption, gained output ratio, and production cost with the different operating parameters are studied. Besides, the impacts of having parallel and series flow arrangements among the module stages are investigated. Results showed that operating the multistage system at higher feed temperature increases productivity, reduces the specific energy consumption, and minimizes the water production cost. The parallel flow arrangement is slightly better than the series arrangement in terms of productivity. However, the series flow arrangement is found better in terms of energy efficiency. The best-achieved performance indicators are gained output ratio (GOR) of 0.49, specific thermal energy consumption of 1320 kWh/m3, and water production cost of 6 $/m3, which are very promising findings of the tested compact multistage water-gap MD system. [ABSTRACT FROM AUTHOR]

This paper presents an efficient power management, voltage balancing and grid synchronization control strategy to increase the stability and reliability of distributed energy resources (DERs)-based microgrid. The microgrid is composed of Photovoltaic, Double Fed Induction Generator-based wind and diesel generator with critical and non-critical loads. The system model and the control strategy have been developed in Real Time Digital Simulator. The coordination and power management of the DERs in both grid connected and island operation modes is implemented. One distinct challenge of microgrid operation in island mode is the stable control of frequency. A controller is proposed and implemented in the island mode for the diesel generator equipped with the required inertia to maintain the microgrid rated frequency by operating in the isochronous mode. To restore the microgrid back to the utility, the voltage, frequency and phase angle of the islanded microgrid should match with that of the grid network within specified limits to avoid transient instability. Switched capacitor banks are connected at the point of common coupling to balance the voltage for microgrid synchronization. The CIGRE medium voltage test bench system is used to implement the DERs and their controller. The proposed control approach has potential applications for the complete operation of microgrids by properly controlling the power, voltage and frequency in both grid and island modes. The real time digital simulator results verify the effectiveness and superiority of the proposed control scheme in grid connected, island and grid resynchronization scenarios. [ABSTRACT FROM AUTHOR]

The transition from centralized power grids to microgrids (MGs) has facilitated the increased integration of renewable energy sources (RES) to the power systems. However, the operational cost in MGs is highly dependent on planning decisions. Therefore, the optimal sizing and placement of RES will offer significant savings in operational costs and reduce power losses in the system. This study proposes a new technique for optimal sizing and placement of solar capacity in the electrical network to minimize the operational cost of conventional generators and real power losses. Due to the complexity and non-linearity associated with the problem, a new natural inspired optimization technique called lightning search algorithm (LSA) is developed to find the optimal solution. To assess LSA, differential evolution algorithm is also used to solve the same problem and a comparison is conducted to prove the superiority of LSA in reducing computation time. The optimization problem is applied to IEEE 14- and 30-bus systems with 24-hr load and solar profile. The obtained results verify the effectiveness of the proposed LSA approach to obtain the optimal sizing and placement of RES and reduce operational cost and power losses. [ABSTRACT FROM AUTHOR]

This paper proposes an inaccuracy mitigation measure to reduce the error associated with distribution line parameters identification. Additionally, it introduces the concept of positive sequence quantities for determining the line resistance, reactive inductance, and shunt admittance. The positive sequence-based analysis is required for asymmetrical related studies such as unbalanced fault analysis. The paper, also, includes the consideration of noisy distribution networks. It compares the performance of three line parameters identification techniques by using different statistical measures. A total of 12,960 different case studies are simulated and analyzed under six main loading scenarios and four categories with changing line parameters. The line parameters are calculated online using voltage and current signals obtained from phasor measurement units (PMUs) placed at the line two terminals. Finally, the study outcomes and the associated recommendations have been summarized for future works considerations. [ABSTRACT FROM AUTHOR]

Heuristic approaches are proposed and implemented to optimize the air gap membrane distillation (AGMD) system for water desalination. A mathematical model to predict the permeate flux of the AGMD system was developed based on the analysis of heat and mass transfers within the module. The developed mathematical model is linked to two optimization algorithms, namely the ant colony optimization (ACO) and particle swarm optimization (PSO). These algorithms have been developed and employed to find the optimal set of variables for the maximum permeate flux of distilled water. The considered variables included feed water temperature, coolant water temperature, air gap width, feed flow rate, and coolant flow rate. The PSO provides comparatively better solution and is computationally less intensive. The differences between the optimum values of flux from the two techniques were found to be less than 3%. Effects of extending the limits (ranges) of different variables were considered. [ABSTRACT FROM AUTHOR]

This study presents a new formulation for optimal power flow (OPF) to enhance the overall transient stability of the power system in addition to the traditional fuel cost minimisation. To overcome the shortcomings of the traditional formulation, this study formulates OPF as a true multi‐objective optimisation problem. One objective is to operate the system economically within the system physical bounds. The other objective is to withstand severe contingencies by enhancing the system transient stability. To overcome the inconsistency and sub optimality problems, strength Pareto evolutionary algorithm is developed for solving multi‐objective OPF (MOOPF) problem. Time domain simulations (TDSs) are employed for handling transient stability problem that knocks out the numerical inaccuracy and convergence problems. To speed up the transient stability assessment, a hybrid stability classifier is developed that combines TDS and transient energy function methods. To demonstrate the effectiveness of the proposed strategy, two standard test systems have been considered. The results show the effectiveness of the proposed approach to solve the MOOPF and enhance greatly the system transient stability. The results also show the superiority of the proposed approach compared with those reported in the literature. [ABSTRACT FROM AUTHOR]

—In this article, a new nature-inspired metaheuristic technique called the differential search algorithm is proposed to solve the optimal power flow problem. The proposed differential search algorithm has been developed and tested under normal and contingency power system conditions. To show the effectiveness of the proposed method, it has been demonstrated on the standard IEEE 30-bus and IEEE 118-bus test systems with different objectives that reflect performance indices of the power system. Obtained results using the proposed technique indicate that the proposed differential search algorithm provides an effective, a robust, and a high-quality solution for the optimal power flow problem. The comparisons of the proposed differential search algorithm results with those reported in the literature reveal the potential and superiority of the proposed algorithm in terms of the optimal solution quality and robustness. [ABSTRACT FROM AUTHOR]

In this paper, a new global decentralized discrete-time quasi-sliding mode control of linear interconnected systems is presented. The proposed controller is free of chattering problem and can be applied to a broader class of large-scale systems. Additionally, it is capable to deal with both known and unknown interconnections among the subsystems. Stability of the reduced-order interconnected systems is analyzed using Lyapunov approach. The proposed decentralized controller guarantees the reachability of the connective sliding manifold. The resultant dynamics are proved to be globally asymptotically stable. Furthermore, the controller is made robust to external disturbances by employing a disturbance estimation scheme. The simulations are performed on model of a two-area power generation system and the results show the efficacy of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, an efficient under frequency control and the energy management of a distributed energy resources (DERs)-based microgrid is presented. The microgrid is composed of a photovoltaic (PV), double-fed induction generator (DFIG)-based wind and diesel generator with critical and non-critical loads. The system model and the control strategy are developed in a real time digital simulator (RTDS). The coordination and power management of the DERs in both grid-connected and islanded operation modes are implemented. During power imbalances and frequency fluctuations caused by fault or islanding, an advanced automatic load shedding control is implemented to regulate and maintain the microgrid frequency at its rated value. One distinct feature implemented for the load shedding operation is that highly unbalanced critical loads are connected to the microgrid. The diesel generator provides the required inertia in the islanded mode to maintain the microgrid rated frequency by operating in the isochronous mode. The International Council on Large Electric Systems (CIGRE) medium voltage (MV) test bench system is used to implement the DERs and their controller. The proposed control approach has potential applications for the complete operation of microgrids by properly controlling the power, voltage and frequency in both grid-connected and island modes. The real time digital simulator results verify the effectiveness and superiority of the proposed control scheme in grid connected, island and fault conditions. [ABSTRACT FROM AUTHOR]

Distributed generation (DG) units are utilized to feed their closed loads in the autonomous microgrid. While in the grid-connected microgrid, they are integrated to support the utility by their required real and reactive powers. To achieve this goal, these integrated DGs must be controlled well. In this paper, an optimal PQ control scheme is proposed to control and share a predefined injected real and reactive powers of the inverter based DGs. The control problem is optimally designed and investigated to search for the optimal controller parameters by minimizing the error between the reference and calculated powers using particle swarm optimization (PSO). Microgrid containing inverter-based DG, PLL, coupling inductance, LC filter, power and current controllers is implemented on MATLAB. Two microgrid cases with different structure are studied and discussed. In both cases, the microgrid performance is investigated under different disturbances such as three-phase fault and step changes. The simulation results show that the proposed optimal control improves the microgrid dynamic stability. Additionally, the considered microgrids are implemented on real time digital simulator (RTDS). The experimental results verify the effectiveness and tracking capability of the proposed controllers and show close agreement with the simulation results. Finally, the comparison with the literature confirms the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

An efficient power management control for microgrids with energy storage is presented in this paper. The proposed control scheme increases the reliability and resiliency of the microgrid based on three distributed energy resources (DERs), namely Photovoltaic (PV), battery, and diesel generator with local active loads. Coordination among the DERs with energy storage is essential for microgrid management. The system model and the control strategy were developed in Real Time Digital Simulator (RTDS). Decoupled d-q current control strategy is proposed and implemented for voltage source converters (VSCs) used to interface the PV and battery sources to the AC grid. A dc-dc buck converter with a maximum power point tracking function is implemented to maximize the intermittent energy generation from the PV array. A controller is proposed and employed for both grid connected and island modes of operation. In grid connected mode, the system frequency and voltage are regulated by the grid. During a fault in island mode, the diesel generator controls the system frequency and voltage in isochronous mode. Results based on the real time digital simulator are provided to verify the superiority and effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Controller gains and power-sharing parameters are the main parameters affect the dynamic performance of the microgrid. Considering an active load to the autonomous microgrid, the stability problem will be more involved. In this paper, the active load effect on microgrid dynamic stability is explored. An autonomous microgrid including three inverter-based distributed generations (DGs) with an active load is modeled and the associated controllers are designed. Controller gains of the inverters and active load as well as Phase Locked Loop (PLL) parameters are optimally tuned to guarantee overall system stability. A weighted objective function is proposed to minimize the error in both measured active power and DC voltage based on time-domain simulations. Different AC and DC disturbances are applied to verify and assess the effectiveness of the proposed control strategy. The results demonstrate the potential of the proposed controller to enhance the microgrid stability and to provide efficient damping characteristics. Additionally, the proposed controller is compared with the literature to demonstrate its superiority. Finally, the microgrid considered has been established and implemented on real time digital simulator (RTDS). The experimental results validate the simulation results and approve the effectiveness of the proposed controllers to enrich the stability of the considered microgrid. [ABSTRACT FROM AUTHOR]