Search

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 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]

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, 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]

This article offers a cohesive design optimization and control framework of a large-scale grid-connected battery and battery-less hybrid solar/wind system. Primarily, a techno-enviro-socio-economic design optimization and feasibility analysis were performed for eight distinct energy alternatives. Secondly, a finite-set model predictive current control (FS-MPCC) was proposed to improve both stability and dynamic behavior of the optimal energy alternative under various climatic circumstances. Moreover, finite-set model predictive control is furtherly employed to exploit the maximum permissible power from both solar and wind energies. The proposed framework is verified over a new case-study in Sokhna Industrial Zone in Suez, Egypt. The studied load demand combines both industrial and residential load sectors with a daily consumption of 40,500 kWh and of 4-MW peak. The design optimization results revealed that the grid-connected photovoltaic/wind turbines/converter system has superior sustainable and economic performances with the least net present cost ($17,371,980) and energy cost (0.0782 $/kWh). These values were less than those of the base-case system (grid-only) by 17 % and 22 %, respectively. Moreover, the reliability analysis found a tiny and tolerable daily capacity shortage of 5835-kWh despite the five annual grid outages. Besides, around 52 % of the total energy production was acquired from both solar and wind generation systems, which interpreted in a maximum saving in carbon dioxide emissions by 45.8 % compared to the base-case system and offered substantial social benefits in terms of creating nearly 10 jobs. The FS-MPCC results proved a reinforced dynamic behavior for the maximum power tracking profiles of solar and wind systems as well as in the DC-bus voltage profile regarding the over- and undershoot and the steady-state response. Compared to PI controller, the proposed FS-MPCC creates dq-axis voltages and currents with less disturbances and ripples which inject current/voltage to the grid with fewer harmonics and thus increases the generator's lifetime. To sum up, the proposed method features an integrative and compelling case to be used as an efficient tool to implement large-scale renewable energy projects. It could act as a blueprint for energy developers, researchers, investors, and authorities to achieve affordable and sustainable energy access. • On-grid solar/wind energy system is optimized to meet industrial and residential loads. • PI. FS-MPCC technique is developed and compared with PI for optimal system control. • Optimal design has the least net present and energy costs and maximum carbon savings. • FS-MPCC prove a strengthened dynamic performance under different climatic conditions. [ABSTRACT FROM AUTHOR]