In recent years, grid-connected photovoltaic system (GCPVS) has been installed at a steady pace around the world due to its clean energy generation, simple operation, and low maintenance. This technology is also a convenient solution for peak shaving in residential and commercial buildings of arid areas with great air conditioning demand in the summer noon. Several supportive policies have been accordingly legalized by countries/regions to attract private and government-based stakeholders. This paper proposes a techno-economic assessment of GCPVS in arid areas from the peak shaving perspective. As a practical case, the effect of a commissioned 102 kW GCPVS on peak shaving of the Mashhad waste management organization building is assessed, exploiting high-resolution one-year recorded data. The results endorse that installed GCPVS shaves the peak demand of this commercial building in summer noon by 40–50% on average. An economic evaluation is also conducted; the outputs highlighted that this project is economically viable with a 43,671 € net present value (NPV) and 34.5% internal rate of return (IRR). It is finally recommended that such practical and reliable studies with a large range of applications provide valuable insights and recommendations to the policymakers to adopt a well-modified policy according to the local economic and solar potential.

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Effective islanding detection is mandatory for distributed generations (DGs) to avoid equipment damage and ensure the safety of network personnel. This paper proposes a fast, accurate, power quality-friendly, and practical two-stage active power curtailment (APC)-based islanding detection technique (IDT) for photovoltaic (PV)-rich microgrids. In the first stage, a periodic small disturbance is injected into the maximum power point tracking (MPPT) algorithm to slightly curtail the DG's active power, causing a small mismatch even on a balanced island. During islanding, the introduced active power mismatch shifts output voltage, triggering the second stage disturbance to the MPPT algorithm. Hence, the output voltage drops further, resulting in islanding detection. A real-time digital simulation (RTDS) using the modified IEEE 13-node system corroborates the successful detection of all stringent cases in less than 1.2 s with no false tripping for non-islanding disturbances. This zero non-detection zone (NDZ) is achieved by curtailing less than 1 % of the DG's available output. This technique is a practical solution for microgrids with high penetration of photovoltaic generators (PVGs) due to its simple structure and straightforward threshold determination, irrespective of the microgrid structure. The fast detection time allows the DG to seamlessly transition to the standalone microgrid.

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Overvoltage instability is a growing concern in a standalone low-voltage (LV) microgrid (MG) with non-dispatchable intermittent renewable energies such as residential and commercial photovoltaic generators (PVGs). Several overvoltage controllers used in PV arrays have adopted the concept of standard deviation from the maximum power point (MPP) to curtail the generated power. However, these solutions lack presenting analytical expression for the MPP deviation size, settings tuning independent of the MG's/PV's characteristics, scalability, and accurate power-sharing in the same control structure. To overcome these limitations, this paper proposes a new analytical MPP tracking (MPPT)-based overvoltage and power-sharing control method using the series equivalent resistance of the PV module model. By applying this analytical expression, the size of the PV array voltage shift to the right-hand side of the MPP is obtained in terms of overvoltage level, while all PVGs proportionally curtail the active power output. The effectiveness of the proposed methodology is shown in various low-demand and high-PV generation cases through a real time digital simulator (RTDS) platform. In addition to the fast and accurate performance, the presented method benefits from the straightforward and communication-free structure as it solely exploits the point of common coupling (PCC) voltage. Also, the method's threshold does not require re- tuning after MG restructure, ensuring scalability. Without relying on other microgrid facilities, the proposed methodology is accordingly an effective solution for practical PV-based LV MGs.

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Due to a 15% electricity shortage in Iran, the scheduled shutdown occurs frequently in summer noon in 2021. These power cuts lead to serious social and economic effects on both private and government sectors. As a solution, Mashhad Electric Energy Distribution Company extended the current FiT11Feed-in-tariff (FiT) framework in a way that any individual can upgrade its existing GCPVS22Grid-connected photovoltaic system (GCPVS) to the hybrid one through exploiting BESS33Battery energy storage system (BESS) and substituting the grid-tie inverter with a hybrid one. When the grid is present, the investor sells the whole generated energy at a guaranteed price. Further, he/she benefits continuous supply of energy for domestic loads during the grid power cut. This paper presents the economic evaluation of the residential hybrid PV-BESS under FiT policy in Mashhad as a case study. The BESS is initially designed for a traditional residential demand taking the frequency and duration of the power cuts into account. Afterwards, the hybrid system is assessed under the current FiT policy from the economic perspective. The presented analyzes endorse that although the initial cost of the hybrid system raises with respect to the grid-connected type, this project with 463,425,280 Iranian Rials NPV44Net present value (NPV), 12.68 PBT55Payback period time (PBT), and 28.3% IRR 66Internal rate of return (IRR) is economically viable under the current FiT policy.

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The connection of renewable energy sources (RESs) to the distribution network has been rising at a steady pace over the past decades. The great penetration of RESs such as grid-connected photovoltaic system brings new technical challenges to the distribution networks such as unintentional islanding. Conceptually, this situation occurs when a portion of the network that has been isolated from the main grid remains energised by the embedded RESs. This unexpected scenario should be thereby identified effectively to avoid frequency and voltage deviations and their hazardous effects. The aim of this paper is to provide a comprehensive review on the recently developed islanding detection methods for grid-following/grid-connected photovoltaic system, analyse their existing limitations, and suggest possible future research implementations. In this context, an in-depth comparison is provided considering the main features used in islanding detection methods such as non-detection zone, detection time, implementation cost and complexity, and power quality degradation. Finally, the main technical requirements established by the current grid codes are recalled identifying potential multi-functional approaches to expand the current islanding detection capabilities.

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This paper proposes a fast and reliable hybrid islanding detection method (IDM) for mini-hydro-based distributed generations (DGs) with zero non-detection zone (NDZ). The proposed IDM aims to tackle the islanding events caused by a self-excited induction generator (SEIG) when it is driven by a mini-hydro turbine system utilising the transient dynamic response of the governor for the first time. To achieve such a goal, it takes advantage of a two-stage process in which both passive and active techniques are combined. Thus, if the rate of change of frequency (ROCOF)-based threshold of the first stage is exceeded, the power reference of the mini-hydro unit is modified, implying a change in the turbine governor gate position. The mechanical torque applied to the prime mover is accordingly shifted to a new state so that both frequency and its derivative will exceed the established thresholds in the second stage in the islanding mode. Conversely, the effect of imposed disturbance is eminently negligible in the grid-connected mode since the frequency is strictly dictated by the main grid. The proposed IDM has been evaluated through numerous islanding and non-islanding case studies considering both single and multi-DG scenarios in MATLAB/Simulink. The outcomes highlight the outstanding performance of the proposed algorithm with zero NDZ and 473 ms average detection time, indicating the capability of the governor system as a reliable tool to identify islanding operations. The proposed technique does not degrade the power quality (PQ) of the grid, requires a low level of computational complexity and provides a high degree of reliability. Therefore, it is a robust and cost-effective solution for future microgrids with great penetration of mini-hydro units.

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Islanding is a condition when distributed generators (DGs) are disconnected electrically from the upstream network. This unwanted situation should be detected effectively to ensure the safety of the maintenance staffs and power quality (PQ) requirements. This paper presents a new high PQ maximum power point tracking (MPPT)-based methodology for detecting the islanding operating mode of grid-connected photovoltaic systems (GCPVSs). In the recommended two-level scheme, a disturbance is injected into the MPPT algorithm under suspicious conditions, recognized by a passive criterion. This disturbance declines the DG active power output remarkably, drifting the output voltage beyond the minimum standard set in islanding state while its impact is negligible at the network presence. The effectiveness of the proposed technique has been evaluated through several hardware-in-the-loop simulations for a case study system, containing two power plant GCPVSs equipped with a pair of multi-functional relays. The results highlight precise islanding classification within 137 ms with the small non-detection zone. Moreover, the results of PQ analyses indicate acceptable total demand distortion and harmonic spectra of the output current in compliance with the existing standards under various DG power penetrations. Since the presented scheme diminishes the active power output in case of suspicious islanding events, its influence on GCPVS efficiency has been studied as well. The outputs underline that the efficiency drops by 0.52% whilst the disturbance is stimulated every minute of the time. It is finally concluded that the proposed technique provides a reliable islanding classification as well as insignificant degradation of PQ and efficiency.@en

This paper proposes a new hybrid islanding detection method for grid-connected photovoltaic system (GCPVS)-based microgrid. In the presented technique, the suspicious islanding event is initially recognized whilst the absolute deviation of the point of common coupling (PCC) voltage surpasses a threshold. After an intentional delay, a transient disturbance is injected into the voltage source inverter’s d-axis reference current to decline the active power output. As a result, the PCC voltage reduces in islanding operating mode whilst its variation is negligible in the grid presence. Therefore, the simultaneous drop of PCC voltage and active power output is used as an islanding detection criterion. The effectiveness of the proposed algorithm is investigated for various islanding and non-islanding scenarios for a practical distribution network with three GCPVSs. The simulation results in MATLAB/Simulink show successful islanding detection with a small non-detection zone within 300 ms without false tripping during non-islanding incidents. In addition to the precise and fast islanding classification, the presented scheme is realized inexpensively; its thresholds are determined self-standing, and its output power quality degradation is eminently small. Moreover, the active power output is restored to the nominal set after islanding recognition, enhancing the chance of GCPVS generation at its highest possible level in the autonomous microgrid.@en

Currently, the economy of Middle Eastern countries relies heavily on fossil fuel sources. The direct and indirect adverse consequences of fossil fuel utilization for power generation enforce the region’s countries to raise the share of renewable energy. In this context, various incentive policies have been developed to encourage the residential and industrial sectors to support a portion of energy needs through renewable energy resources. In this case, a solar water heating system (SWHS) as an application of solar thermal technology provides some of the heat energy requirements for domestic hot water (DHW) and space heating, supported conventionally by electricity or natural gas, or even other fossil fuels. This paper reviews the feasibility of the SWHS in the Middle East region from technical and economical standpoints and investigates some of the progress, challenges, and barriers toward this market. The pay-back times and CO₂ emission reduction under different incentive frameworks and configurations of each system have been assessed in this context. Furthermore, the advantages and weaknesses of the SWHS in several countries have been reported. Finally, various guidelines have been proposed to enhance the development of this technology.

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This paper proposes a novel islanding detection method (IDM) for grid-connected photovoltaic systems (GCPVSs) through a disturbance injection in the maximum power point tracking (MPPT) algorithm. When an absolute deviation of the output voltage exceeds a threshold, the applied disturbance shifts system operating point from its maximum power point (MPP) condition. This leads to a sharp active power output reduction and consequently, a significant voltage drop in islanded mode beyond the standard voltage limit. The proposed algorithm is defined in a way that the distributed generator (DG) can be restored to MPP after islanding classification. It is thereby effective in microgrid in where the power injection at maximum level to cater the critical loads and maintain the stability of the isolated area are pursued. An intentional time delay has also been considered to avoid nuisance tripping in short-circuit faults which do not require tripping. The assessment of the proposed technique has been conducted for a sample network containing two GCPVSs in a real-time platform including actual relays in hardware-in-the-loop (HiL). The provided results under extensive islanding scenarios defined in islanding standards endorse timely and accurately detection with negligible non-detection zone (NDZ) as well as no false tripping in non-islanding disturbances. The comparative analysis of the presented scheme with a few recent IDMs for GCPVS highlights its overall superiorities, including very small NDZ, fast detection, thresholds self-standing determination, no adverse effect on power quality, and simple and inexpensive integration.

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This article proposes a fast and reliable two-level islanding detection method (IDM) for grid-connected photovoltaic system (GCPVS)-based microgrid. In the first level of the proposed IDM, the magnitude of the rate of change of output voltage (ROCOV) is computed. If this variable exceeds a predefined threshold, a disturbance is injected into the duty cycle of DC/DC converter after a given time delay to deviate the system operating point away of its maximum power point (MPP) condition. This leads to a substantial active power output and voltage reduction in an islanded mode. Therefore, the ROCOV and the rate of change of active power output (ROCOP) indices, measured in the second stage, pose great negative sets at the same time in islanding states. However, the variation of at least one of these variables is near-zero in non-islanding switching events. The assessment of the presented algorithm has been conducted under extensive islanding and non-islanding scenarios for a case study system with two PV power plants using hardware-in-the-loop (HiL) simulation tests. The provided results remark precise islanding classification with an eminently small non-detection zone (NDZ) within 510 ms. The presented IDM has the advantages of self-standing thresholds determination, no improper effect on the output power quality, and simple and inexpensive structure. Moreover, the fast MPP restoration of the proposed scheme after islanding identification boosts the chance of seamless reconnection and DG autonomous operation in microgrid.

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This paper investigates the economic viability of a commercial grid-connected photovoltaic system (GCPVS) in the Middle East region. In this regard, an economic assessment of a 120 kW_p GCPVS connected in December 2017 under a feed-in tariff (FiT) scheme in Iran—the leading country in the region establishing a supportive policy—is carried out. In this plan, private enterprises can install GCPVS and sell whole generated energy at a high guaranteed price for twenty years. Several economic indices, including net present value (NPV), internal rate of return (IRR), benefit-cost ratio (BCR), payback period time (PBT), and levelized cost of energy (LCOE) are determined to unveil the effectiveness of the enacted program. This paper exploits one-year recorded energy data of this commercial system to boost the reliability of the results. Moreover, PV module degradation factor is taken into account to make the analysis as realistic as possible. The computed outputs imply that this commercial system, with 3.36 BCR, 31.88% IRR, 5.24 years PBT, and 0.0477 $/kWh LCOE, is highly appealing. The sensitivity analysis also highlight that the profitability of the GCPVS investment is secure under a wide range of unpredictable parameters. It is shown for instance that the PBT and IRR are deteriorated by 5.48% and 1.50 years, while the generated energy lowers by 20% compared with the predicted value for the upcoming years. Having said that, it is still far away from the infeasible condition. A comparative analysis between the current findings and similar researches endorse the Middle East region as the highest potential site for PV installation. It is finally deduced that a properly modified FiT scheme can be set in the region's countries concerning the local meteorological and economic conditions to stimulate the investment of this technology.

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Islanding refers to a condition where distributed generators (DGs) inject power solely to the local load after electrical separation from power grid. Several islanding detection methods (IDMs) categorized into remote, active, and passive groups have been reported to detect this undesirable state. In active techniques, a disturbance is injected into the DG's controller to drift a local yardstick out of the permissible range. Although this disturbance leads to more effective detections even in well-balanced island, it raises the total harmonic distortion (THD) of the output current under the normal operation conditions. This paper analyzes the power quality aspect of the modified sliding mode controller as a new active IDM for grid-connected photovoltaic system (GCPVS) with a string inverter. Its performance is compared with the voltage positive feedback (VPF) method, a well-known active IDM. This evaluation is carried out for a 1 kWp GCPVS in MATLAB/Simulink platform by measuring the output current harmonics and THD as well as the efficiency under various penetration and disturbance levels. The output results demonstrate that since the proposed disturbance changes the amplitude of the output current, it does not generate harmonics/subharmonics. Thereby, it has a negligible adverse effect on power quality. It is finally concluded that the performance of the sliding mode-based IDM is reliable from the standpoints of islanding detection and power quality. @en

This study proposes a fast and precise voltage feedback-based islanding detection method (IDM) for grid-connected photovoltaic systems (GCPVSs) based microgrid. In this algorithm, a disturbance containing the absolute deviation of the output voltage is injected into the inverter's d-axis reference current which tunes the active power output. In islanded mode, the applied disturbance reduces the active power output and consequently point of common coupling voltage beyond the standard setting while its effect at the presence of the grid is negligible. The assessment of the proposed IDM has been conducted in the MATLAB/Simulink platform under extensive scenarios defined by IEEE 1547-2008 and UL 1741 standards for a case study system with two large-scale GCPVSs. The provided outputs remark accurate islanding classification in all cases within 810ms, much lower than the maximum permissible time postulated in islanding standards. This time is short enough to restore GCPVS for autonomous operation of microgrid as well. The comparative analysis of the proposed strategy with a few existing IDMs confirmed its overall superiorities in the terms of non-detection zone, detection time, being applicable into the microgrid, simple threshold determination, and straightforward and cost-effective implementation.

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Nowadays, grid–connected photovoltaic (GCPV) system is known as a top leading technology among all resources. However, it still suffers from drastic investment costs. Detailed economic studies should be conducted in this regard to make this technology as gainful as possible. A practical approach is the “optimum economic design”, trying to find an electrically possible layout, i.e. number of series modules and parallel strings as well as the inverter number with the highest profit. This problem is inherently an quadratic integer programming owing to the multiplication of two integer variables in its objective function and some technical constraints. This nonlinear problem should be solved by exhaustive search methods, including comparative and evolutionary algorithms (EAs) such as particle swarm optimization (PSO) and genetic algorithm (GA). In this paper, a new formulation based on the definition of new binary variables has been proposed to convert this problem to the binary linear programming (BLP). The provided method finds the global optimum solution in a scale of seconds while EAs have to be run numerous times in a scale of hours to reach a sufficiently good answer. Moreover, although current methodologies are rarely covered GCPV systems with multiple inverter types, this formulation can be easily developed for systems with several inverter types. The simulations of a 1.1 MW power plant system endorse that the output design provided by the proposed method assures 95,000 $ (1.94%) higher profit compared with those presented by GA. The sensitivity analysis, provided for the prototype system by the efficient new algorithm, also unveils it is economically viable for even 52% of the current feed–in tariff, 40% energy generation lower than the estimated value and 1.1 $/W price rise for the initial investment.@en

Grid–connected photovoltaic (GCPV) systems are currently known as a top leading source of energy among all distributed generators. Despite numerous benefits, this technology suffers from the high initial burden cost. Hence, governments have been decided to encourage the investors to install GCPV systems through different support mechanisms such as feed–in tariff (FIT). This paper investigates the viability of GCPV technology under a new dynamic FIT strategy. The new scheme introduces the annual update of the FIT regarding the goods retail prices and Euro exchange rate rather than the retail electricity cost. These objects are two parameters mostly affect the justification of a project in developing countries with predominantly imported equipment and unstable economic conditions. The new policy is described, and the economic perspective is cleared by computing the economic indices, including net present value (NPV), internal rate of return (IRR), and payback period time (PBT) as well as the levelized cost of energy (LCOE) for Iran as a case study. The computed outputs and significant rise in the installed capacity rate after running the proposed scheme, remark the technology viability for short and mid–term courses in the country. The outputs demonstrate proper attractiveness of the power stations for foreign investment probably does not benefit from excess FIT regarding the utilization of foreign PV module. Finally, it has been concluded that this program can be implemented in developing countries, especially in the Middle East region with almost similar climate patterns.@en

Nowadays installed power capacity of grid-connected photovoltaic (GCPV) systems has an exponential increase around the world. Since these systems are more expensive than other conventional electricity resources, optimal economic designing is much necessary. In this paper, a new intelligent-based approach is proposed to design GCPV systems using Genetic Algorithm (GA). By defining the net present value (NPV) of system as the objective function and considering electrical constraints, the optimal value for sizing factor and also system configuration are determined. In order to calculate the annual produced energy of system with high accuracy, the accurate efficiency model and power equations are used for inverter and PV module, respectively. Also, five-parameter, i.e. linear and five-point, i.e. nonlinear, models of PV module are used to evaluate the behavior of PV array in different temperature and solar radiation conditions. This approach is presented for GCPV systems in all sizes including two or more inverters even with different topologies. The proposed method is applied for designing of a power plant system with multiple inverters.@en