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A suitable probabilistic scenario set of load demand and natural characteristics of renewable energy is becoming a crucial issue in power system planning studies. Properly addressing the impact of potentially thousands of residential PV plants on the resilience and reliability needs of substations necessitates the representation of inherent relations between photovoltaics and the load throughout the long-term planning period. The optimal planning of substation expansions is achievable through proper modeling of input parameters which describes the characteristics of the service areas. In this paper, the co-existence of PV plants and the load in a service area under three different states such as daytime with clear-sky and no-fault, daytime with abnormal events, and nighttime are incorporated into the stochastic dynamic optimization problem by using scenario-based approach. The scenario tree of the problem is branched from three different bases simultaneously instead of only one as in conventional approach. This paper also combines the risk-constrained stochastic dynamic SEP problem and Mixed Integer Linear Programming (MILP) framework under one roof. The comparison between integrating inherent characteristics of PV plants with and without considering abnormal events into the optimization is performed to show the impact of suitable probabilistic model on dynamic nature of investment decisions. [ABSTRACT FROM AUTHOR]

• No need for any external sensors, equipment and detailed PV plant information. • Compatibility with ground-mounted and rooftop PV plants. • Robust working capability in any weather condition. • Ability to work in PV plants which have different sized and oriented arrays. • Easy to implement on a newly installed or existing PV plant. Research on monitoring and fault detection systems for photovoltaic plants is significantly increasing with the continual development in technologies and the availability of qualified data. Nevertheless, many gaps still exist that need to be addressed. The electrical output of PV plants in various weather conditions is very close to those obtained under fault conditions. For a large scale PV plant, it is very crucial to utilize the data in the decision-making process without using external sensors or performing simulation studies that require detailed parameters of the plant. The main challenge here is to automatically rationalize the collected data in order to make a decision on distinguishing between faulty and natural outputs. This paper proposes a method for distinguishing faults and inherent changes in the PV plant's output to help O&M crews identify and fix system issues. The proposed method has the ability to map the inherent characteristics of the PV plant by using only the data received from inverters without using additional equipment or detailed models. It has been developed by analyzing the working mechanisms of several large scale PV plants installed in Turkey. The proposed method can easily be implemented in a newly installed or existing PV plant. The novelty of this study is detecting abnormal operations in a PV plant even under low irradiance and cloudy-sky conditions without using any irradiance and temperature sensors. The effectiveness of the proposed method is shown in rooftop and ground-mounted PV plants. [ABSTRACT FROM AUTHOR]

Harmonic distortion caused by increasing size of inverter-based distributed generation (DG) can give rise to power quality problems in distribution power networks. Therefore, it is very important to determine allowable DG penetration level by considering the harmonic related problems. In this study, an optimization methodology is proposed for maximizing the penetration level of DG while minimizing harmonic distortions considering different load profiles. The methodology is based on updating the voltage magnitude and angle at point of common coupling depending on the size of DG to be utilized in the harmonic power flow modeling. The harmonic parameters are determined by using decoupled harmonic power flow method, in which the harmonic source modeling with harmonic current spectrum angle adjustment is embedded, while the nonlinear loads and inverter-based DGs are connected to the distribution power network. The allowable penetration level of DGs is determined based on power quality constraints including total harmonic voltage distortion, individual harmonic voltage distortion, and RMS bus voltage limits in the optimization framework. Fuzzy-c means clustering method is also applied to decrease the computational effort of the optimization process in the long-term load profile. The effectiveness of the proposed method is illustrated on the IEEE 33-bus radial distribution network for different scenarios. [ABSTRACT FROM AUTHOR]

This paper presents genetic algorithm optimization method with a suitable objective function to determine optimum location and rated values of FACTS devices by taking into account changes in the power system load over time. In this study, annual daily load profile is considered as a whole instead of an instant load profile while looking for optimum size and location of FACTS devices. For this reason, to simplify the optimization procedure, a graph-based panelized objective function is developed, which can be used in a mixed integer search heuristic optimization technique. This paper focuses on the evaluation of the simultaneous use of thyristor controlled series capacitor and static VAR compensator. The proposed method allows including, in a simple way, the long term load profile in the planning stage to improve the power system performance using FACTS devices. After the optimization process, the performance of the proposed method has been tested on the IEEE-30 bus system with several annual test load profiles. The planning horizon is included in the optimization framework and the impact of planning horizon result is presented to compare with that of single load profile. The optimization strategy is shown to lead a significant reduction in the voltage and line violations under the long term test load profiles. [ABSTRACT FROM AUTHOR]

In this study, two important planning problems in power systems that are transmission expansion and reactive power are formulated as a mixed-integer linear programming taking into account the bilevel structure due to the consideration of market clearing under several load-wind scenarios. The objective of the proposed method is to minimize the installation cost of transmission lines, reactive power sources, and the annual operation costs of conventional generators corresponding to the curtailed wind energy while maintaining the reliable system operation. Lower level problems of the bilevel structure are designated for the market clearing which is formulated by using the linearized optimal power flow equations. In order to obtain mixed-integer linear programming formulation, the so-called lower level problems are represented by using primal-dual formulation. By using the proposed method, power system planners will be able to find economical investment plans by considering the balance between wind power curtailment and the installation of transmission lines and reactive power sources. [ABSTRACT FROM AUTHOR]

Integration of wind turbines introduces new challenges in terms of planning criteria. In this study, a new transmission expansion planning methodology considering N-1 contingency conditions is proposed to minimize investment cost and curtailed wind energy over planning period. To deal with the uncertainty of load and output power of wind turbines, probabilistic method based on clustering is used for determination of load and wind model. To incorporate the wind power curtailment into the proposed methodology, optimal power flow which uses DC-power flow equations is utilized by including cost functions of generators and overall optimization is carried out by using an integer genetic algorithm. Finally, the proposed methodology is applied to the modified IEEE RTS 24-bus test system by considering different case studies in order to show the effects of including cost functions. [ABSTRACT FROM AUTHOR]

The level of uncertainty increases with growing distributed generation (DG) penetration in the power systems, thus convincing and user-friendly planning tools and strategies should be developed. We investigate the comparison between single- and multiple-DG concepts in terms of power loss, voltage profile, and line flows. A new procedure is presented based on grading the restructuring priorities by using a simple power flow analysis based probabilistic assessment including the output power uncertainties in DG resources. This procedure can facilitate the choice of which infrastructure of an existing network has precedence in the modernization of a network when DG units are integrated. Note that there is a threshold penetration level in terms of line losses, and trade-off between single- and multiple-DG concepts in respect of the capacity of existing lines and voltage profiles. [ABSTRACT FROM AUTHOR]

This paper presents a new approach for efficient utilization of building integrated photovoltaic (BIPV) systems under partial shading conditions in urban areas. The aim of this study is to find out the best electrical configuration by analyzing annual energy generation of the same BIPV system, in terms of nominal power, without changing physical locations of the PV modules in the PV arrays. For this purpose, the spatial structure of the PV system including the PV modules and the surrounding obstacles is taken into account on the basis of virtual reality environment. In this study, chimneys which are located on the residential roof-top area are considered to create the effect of shading over the PV array. The locations of PV modules are kept stationary, which is the main point of this paper, while comparing the performances of the configurations with the same surrounding obstacles that causes partial shading conditions. The same spatial structure with twelve distinct PV array configurations is considered. The same settling conditions on the roof-top area allow fair comparisons between PV array configurations. The payback time analysis is also performed with considering local and global maximum power points (MPPs) of PV arrays by comparing the annual energy yield of the different configurations. [ABSTRACT FROM AUTHOR]

This paper proposes a new multi-objective transmission expansion planning (TEP) in order to find optimum location of lines/transformers by considering intermittent nature of wind power and variable load structure. To reveal the benefit of wind power in the context of TEP, curtailed wind energy is considered as one of the objective functions besides the sum of the investment costs and penalty for energy not supplied (ENS). By this way, a trade-off between investment cost and curtailed wind energy is established using fuzzy satisfying approach while maintaining the adequacy of power system. The multi-objective nature of the proposed method is handled by using the Non-dominated Sorting Genetic Algorithm-II combined with the DC-optimal power flow which is performed several times to obtain curtailed wind energy and ENS. The nature of load and wind power is incorporated into the methodology by using agglomerative hierarchical clustering to reduce computational effort. The proposed methodology is illustrated on the different configurations of modified IEEE-RTS 24 bus test system. Numerical case studies indicate the effectiveness of the proposed method for reduction of total investment cost in TEP of power systems with wind power integration. [ABSTRACT FROM AUTHOR]

Highlights: [•] This paper presents a new global maximum power point tracking (MPPT) algorithm for PV systems. [•] This algorithm takes into account the number of bypass diodes in a PV string. [•] This paper states that the global MPP can be tracked by considering only the possible voltage bands. [•] The possible voltage bands can be found simply by using the proposed analytical equation. [•] The effectiveness of proposed method has been validated by simulation and experimental studies. [ABSTRACT FROM AUTHOR]

Highlights: [•] A weighting-based methodology is developed to find optimum wind-turbine size. [•] The time-varying characteristics of load and wind-generation profiles are considered. [•] The harmony of correspondence between load and generation profiles is preserved. [•] The optimization is carried out by using genetic algorithm with utilizing power flow analysis. [•] The fuzzy-c means clustering is utilized to reduce execution time and allow long term planning. [ABSTRACT FROM AUTHOR]

Abstract: This work presents a new analytical method to evaluate the efficiency of PV systems working in partial shading conditions by taking into account the effect of surrounding obstacles. A mathematical procedure to determine the shadowed area on PV modules, depending on the location of the PV system and obstacles nearby the array has been implemented. This methodology allows the study of the power losses present in the PV systems due to partial shading conditions as well as its effect on the evolution of the maximum power point of the array. The application of this methodology on the behavior of three PV systems located in different cities of Turkey, such as Istanbul, Izmir, and Antalya, working under the same conditions of obstacle surrounding, along a year is presented. [Copyright &y& Elsevier]

Highlights: [•] We present a novel fault diagnosis method for PV systems based on operating voltage. [•] The method can identify the faults under both uniform and non-uniform irradiations. [•] The method takes into consideration of the minimum number of sensors. [•] The method needs only the operating voltage of PV string and ambient temperature. [•] The effectiveness of the proposed method has been validated by experimental results. [ABSTRACT FROM AUTHOR]

Abstract: The penetration of distributed generation (DG) in power system is continually increasing. Hence, there is a need to investigate the potential benefits and drawbacks of DGs when integrating DG units in existing networks. The challenge of identifying the optimal locations and sizes has triggered research interest and many studies have been presented in this purpose. Different analytical techniques have been developed to minimize power losses for single-DG unit integration. If DG units are integrated at nonoptimal locations, the power losses increase, resulting in increased cost of energy. The novelty of this paper lies in studying the optimal placement of multiple-DG units in order to minimize power losses. In this study, an optimality criterion is investigated to minimize losses by including load uncertainty, different DG penetration levels and reactive power of multiple-DG concept. The simulation results show that it is not possible to form an analytical equation for optimum planning of DG in terms of load distribution, penetration level and reactive power. Due to the complexity of the multiple-DG concept, artificial neural network based optimal DG placement and size method is developed. The proposed method is implemented to the IEEE-30 bus test network and the results are presented and discussed. The results show that the proposed method can be applied to a power network for all possible scenarios. [Copyright &y& Elsevier]

Abstract: This paper proposes a simple diagnostic method to determine the number of open and short circuited PV modules in a string of a PV system by taking into account the economical factor, such as minimum number of sensors. The diagnostic algorithm has as inputs the irradiance level, the PV modules temperature, the number of PV modules present in the string analyzed and its output power. So, just temperature and irradiance sensors, as well as a power meter by string are needed in the monitoring system forming part of the fault diagnostic system. The proposed fault detection method has been successfully validated experimentally. [Copyright &y& Elsevier]

Distributed generation is becoming a part of the strategic plans of electricity providers for effective system management. The proper planning of multiple distributed generation units plays an important role in modern power systems to offer a highly reliable system. Computation of power flows is one of the major tasks in system planning studies. Conventional load flow analysis methods are impractical to evaluate every possible or probable combination of loads and different allocations of distributed generation units because of the extremely large computational effort required. This article proposes an expansion method to perform load flow analysis with consideration of multiple distributed generation integration and load uncertainties. The proposed approach offers a method to handle the impacts of all possible allocations of distributed generation units without increasing computational efforts. The impacts of placement and penetration level of multiple distributed generation on power losses, voltage deviation, and line capacity are investigated under load uncertainty over a long-term period on the IEEE 57-, IEEE 30-, IEEE 14-, and 9-bus networks for future planning study purposes. The study results indicate that the proposed method has significantly reduced the computational efforts while maintaining a high degree of accuracy in evaluating various possible scenarios in which multiple distributed generation units have to be integrated into the grid. [ABSTRACT FROM PUBLISHER]

Abstract: This paper presents different approaches to find out and address some rules for distributed generation (DG) integrated mesh type networks, which can be used in the management of future power systems. There are so many influencing factors of efficiency in the integration of DG that we need to analyze these influencing factors obviously. Hence, carefully planning plays a key role in tackling these challenges in the future power systems. In contrast to the majority of existing observations, we focus on the case where the underlying states are multiple and single DG allocations with changing conditions. In several previous studies, the best single bus has been investigated under the specified conditions. However, it follows from the results of this study that all issues concerning DG strongly depend on power network structure and DG locations, and it is worth to note that the best location changes with penetration levels. Also, it is observed that the all buses show different characteristics in terms of DG integrations under the different cases, moreover their optimum size and power factor are different. It means that optimum bus in a network changes with the conditions. On the other hand, the problematic buses can be occurred in voltage profile after the DG integration. As a result, an investigation of rule of thumb approach is performed for evaluation of performance enhancement of DG integrated meshed networks. The results are also used to discuss the integration of DG management strategies under various operating conditions. [Copyright &y& Elsevier]

Abstract: The emerging non-crystalline silicon (c-Si) solar cell technologies are starting to make significant inroads into solar cell markets. Most of the researchers have focused on c-Si solar cell in maximum power points tracking applications of photovoltaic (PV) systems. However, the characteristics of non-c-Si solar cell technologies at maximum power point (MPP) have different trends in current–voltage characteristics. For this reason, determining the optimum operating point is very important for different solar cell technologies to increase the efficiency of PV systems. In this paper, it has been shown that the use of fuzzy system coupled with a discrete wavelet network in Takagi–Sugeno type model structure is capable of identifying the MPP voltage of different non-c-Si solar cells with very high accuracy. The performance of the fuzzy-wavelet network (FWN) method has been compared with other ANN structures, such as radial basis function (RBF), adaptive neuro-fuzzy inference system (ANFIS) and three layered feed-forward neural network (TFFN). The simulation results show that the single FWN architecture has superior approximation accuracy over the other methods and a very good generalization capability for different operating conditions and different technologies. [Copyright &y& Elsevier]

Abstract: It is crucial to improve the photovoltaic (PV) system efficiency and to develop the reliability of PV generation control systems. There are two ways to increase the efficiency of PV power generation system. The first is to develop materials offering high conversion efficiency at low cost. The second is to operate PV systems optimally. However, the PV system can be optimally operated only at a specific output voltage and its output power fluctuates under intermittent weather conditions. Moreover, it is very difficult to test the performance of a maximum-power point tracking (MPPT) controller under the same weather condition during the development process and also the field testing is costly and time consuming. This paper presents a novel real-time simulation technique of PV generation system by using dSPACE real-time interface system. The proposed system includes Artificial Neural Network (ANN) and fuzzy logic controller scheme using polar information. This type of fuzzy logic rules is implemented for the first time to operate the PV module at optimum operating point. ANN is utilized to determine the optimum operating voltage for monocrystalline silicon, thin-film cadmium telluride and triple junction amorphous silicon solar cells. The verification of availability and stability of the proposed system through the real-time simulator shows that the proposed system can respond accurately for different scenarios and different solar cell technologies. [Copyright &y& Elsevier]

Abstract: Partially shaded photovoltaic (PV) modules typically exhibit additional difficulties in tracking the maximum power point since their power–voltage characteristics are complex and may have multiple local maxima. For this reason, conventional techniques fail to track the maximum power point effectively if the PV array is partially shaded or some of its cells are damaged. This paper presents a novel power compensation system for PV arrays for complicated non-uniform insolation conditions. The proposed system is based on recovering the power of non-shaded PV modules into the system again completely by forward biasing a bypass diode of the shaded PV modules. For this purpose, the proposed system uses dc–dc converters equipped with each PV string in the PV array. For identifying which shaded PV modules should be deactivated, the operating voltage of the PV modules are monitored and compared. The proposed system enables the non-shaded PV modules to operate effectively at their normal maximum power point. The effectiveness of the proposed system is investigated and confirmed for complicated partially shaded PV arrays. [Copyright &y& Elsevier]

Abstract: The aim of this study is to investigate the effects of non-uniform solar irradiation distribution on energy output of different interconnected configurations in photovoltaic (PV) arrays. In order to find which configuration is less susceptible to mismatch effects, a PV module model is developed. This model can take into consideration the effects of bypass diodes and the variation of the equivalent circuit parameters with respect to operating conditions. The proposed model can provide sufficient degree of precision as well as solar cell-based analysis in analyzing large scale PV arrays without increasing the computational effort. In order to produce more reliable and robust simulations, improved and extended algorithms are presented. Some results are discussed in detail and some recommendations are extracted by testing several shading scenarios. [Copyright &y& Elsevier]

Abstract: This paper presents a neural network based approach for improving the accuracy of the electrical equivalent circuit of a photovoltaic module. The equivalent circuit parameters of a PV module mainly depend on solar irradiation and temperature. The dependence on environmental factors of the circuit parameters is investigated by using a set of current–voltage curves. It is shown that the relationship between them is nonlinear and cannot be easily expressed by any analytical equation. Therefore, the neural network is utilized to overcome these difficulties. The neural network is trained once by using some measured current–voltage curves, and the equivalent circuit parameters are estimated by only reading the samples of solar irradiation and temperature very quickly without solving any nonlinear implicit equations that is necessary in conventional methods. To verify the proposed model, an experimental set up is installed. The comparison between the measured values and the proposed model results shows higher accuracy than the conventional model for all operating conditions. [Copyright &y& Elsevier]

• Dependence of harmonic spectrum of PV current on solar irradiance is considered. • Update of PV current harmonic spectrum is included in the optimization problem. • Optimization problem is solved by both probabilistic and deterministic methods. • Optimal PV penetration levels are obtained in unbalanced distribution systems. • PV and load uncertainties are considered in the optimization problem. Photovoltaic (PV) system is one of the most important technologies among the renewable energy resources. With the increasing penetration of PV systems in distribution networks, harmonic distortions also rise due to the inevitable effects of PV inverters. Therefore, determination of the optimal PV penetration level is a vital issue in terms of preventing power quality problems. In this paper, probabilistic and deterministic approaches are proposed to determine the optimal penetration levels of PV systems in unbalanced distorted distribution networks by taking into account the uncertainty of load profile and the intermittent characteristic of PV system output power due to changes in solar irradiance. The Interior Point (IP) method is applied to solve the optimization problem in conjunction with the Monte Carlo Simulation (MCS) and K – means clustering, respectively. The methodology is based on the dependence of the harmonic spectrum of PV injected current on solar irradiance. The harmonic power quality parameters are calculated by using loop frame of reference based three phase harmonic power flow method in the unbalanced distribution network, where the nonlinear loads and PV systems are interfaced. The allowable PV penetration levels are determined based on power quality parameters comprising of total harmonic voltage and individual harmonic voltage distortions, and RMS bus voltage limits. [ABSTRACT FROM AUTHOR]

Highlights: [•] Procedure for automatic supervision of PV systems. [•] Toolbox for monitoring, modeling, simulation, and diagnosis of grid connected PV systems in real time. [•] Fault detection algorithm that identifies the most probably fault present in the PV system. [•] The proposed method has been experimentally validated in a grid connected PV system. [Copyright &y& Elsevier]

To ensure the optimization of the energy generated by grid connected PV (photovoltaic) systems is necessary to plan a strategy of automatic fault detection. The analysis of current and voltage indicators have demonstrated effectiveness in the detection of permanent faults in the PV array in real time as short-circuits or open circuits present in the system. In this paper, the analysis of the evolution of these indicators is focused on the detection of temporary faults due to partial shade on the PV array or disconnection of the inverter in case of grid fluctuations of voltage or frequency to prevent islanding. These situations can be identified by observation of the evolution of both indicators and power losses due to these effects can be evaluated from them. The analysis and experimental validation were carried out in two grid connected PV systems in Spain and Algeria. [ABSTRACT FROM AUTHOR]

In this work we present a new procedure for automatic fault detection in grid connected photovoltaic (PV) systems. This method is based on the evaluation of new current and voltage indicators. Thresholds for these indicators are defined taking into account the PV system configuration: number of PV modules included and series and parallel interconnection to form the array. The procedure to calculate the thresholds that allow the identification of the faults is described. A simulation study was carried out to verify the evaluation of current and voltage indicators and their corresponding thresholds for a set of PV systems with different sizes and different configurations of interconnection of PV modules. The developed method was experimentally validated and has demonstrated its effectiveness in the detection of main faults present in grid connected applications. The computational analysis has been reduced and the number of monitoring sensors minimized. The fault detection procedure can be integrated into the inverter without using simulation software or additional external hardware. [ABSTRACT FROM AUTHOR]

String inverter photovoltaic (PV) systems with bypass diodes require improved global maximum power point tracking (GMPPT) algorithms to effectively reach the absolute maximum power operating point. Several GMPPT algorithms have been proposed to deal with this problem, but most of them require scanning wide voltage ranges of the PV array from nearly zero voltage to open-circuit voltage that increases the scanning time and, in turn, causes energy loss. This paper presents a novel GMPPT method which significantly restricts the voltage window search range and tracks the global power peak rapidly in all shading conditions. Simulation tests and experimental comparisons with another GMPPT algorithm are presented to highlight the features of the presented approach. [ABSTRACT FROM PUBLISHER]

Abstract: This paper presents a detailed characterization of the performance and dynamic behaviour of photovoltaic systems by using LabVIEW real-time interface system. The developed software tool integrates several types of instruments into a single system which is able to offer online measurements all data sources and comparison simulation results with monitored data in real-time. Comprehensive monitoring and analyzing of PV systems play a very important role. The proposed method is a low-cost solution to provide fast, secure and reliable system by making the system database-ready for performance analysis of PV systems. The proposed method is also applied to a grid connected PV system in the Centre de Developpement des Energies Renouvelables (CDER) in Algeria. The results show that there is a good agreement between the measured and simulation results values. The integration methodology of robust simulation and monitored data in real-time can be extended to study the fault diagnosis of a PV system. [Copyright &y& Elsevier]