Voltage dips represent a significant power quality problem. The main cause of voltage dips and short-term interruptions is an electrical short circuit that occurs in transmission or distribution ...networks. Faults in the power system are stochastic by nature and the main cause of voltage dips. As faults in the transmission system can affect more customers than faults in the distribution system, to reduce the number of dips, it is not enough to invest in a small part of the transmission or distribution system. Only targeted investment in the whole (or a large part of the) power system will reduce voltage dips. Therefore, monitoring parts of the power system is very important. The ideal solution would be to cover the entire system so that a power quality (PQ) monitor is installed on each bus, but this method is not economically justified. This paper presents an advanced method for determining the optimal location and the optimal number of voltage dip measuring devices. The proposed algorithm uses a monitor reach area matrix created by short-circuit simulations, and the coefficient of the exposed area. Single-phase and three-phase short circuits are simulated in DIgSILENT software on the IEEE 39 bus test system, using international standard IEC 60909. After determining the monitor reach area matrix of all potential monitor positions, the binary bat algorithm with a coefficient of the exposed area of the system bus is used to minimize the proposed objective function, i.e., to determine the optimal location and number of measuring devices. Performance of the binary bat algorithm is compared to the mixed-integer linear programming algorithm solved by using the GNU Linear Programming Kit (GLPK).
•The optimization model finding PV configuration with maximal profit is proposed.•Introduced shading factor considers the shading influence on module output power.•Determination of shading factor ...according to measurement results is presented.
A mathematical model for finding an optimal photovoltaic (PV) system configuration for the given installation area obtaining a maximal profit during a PV power plant lifetime is presented in this paper. The model gives an optimal number of rows and a module angle taking into account the influence of the inter-row shading on the PV module output power by introducing a shading factor which depends on the ratio of a sunny part of the module and a total module surface. In order to calculate the profit of the PV installation, a net present value (NPV) methodology is used. The model is programmed in MATLAB software. The case study results demonstrate a huge influence of the inter-row module partial shading on finding the optimal PV configuration using the given PV module.
Active distribution grids that contain energy sources (so-called distributed generation or DG) are nowadays a reality. Besides the many benefits DGs bring to the distribution grid, some challenges ...are associated with their integration. Since there are DGs now in the distribution grid, the occurrence of islanding operation is possible. Since an islanding operation can be dangerous, it is necessary to have an effective method to detect it. In the last decade, scientists have made a great effort to develop and test various islanding detection methods (IDMs). Many approaches have been tested, and the methods based on computational intelligence (CI) have shown great potential. Among them, artificial neural networks (ANNs) gained most of the research attention. This paper focuses on ANN application for islanding detection. It gives an exhaustive review of the ANN types used for islanding detection, the types of input data, and their transformation to fit the ANNs. Furthermore, various applications based on specific input data, preprocessing types, different learning algorithms, real-time implementation, and various distribution models used for ANN are reviewed. This paper investigates the potential of ANNs to enhance islanding detection accuracy, reduce non-detection zone (NDZ), and contribute to an overall efficient detection method.
The high expansion of a variable and intermittent nature of distributed generation, such as photovoltaics (PV), can cause technical issues in existing distribution networks (DN). In addition to ...producing electrical energy, PVs are inverter-based sources, and can help conventional control mechanisms in mitigating technical issues. This paper proposes a multi-stage optimal power flow (OPF)-based mixed-integer non-linear programming (MINLP) model for improving an operation state in LV PV-rich DN. A conventional control mechanism such as on load tap changer (OLTC) is used in the first stage to mitigate overvoltage caused by PVs. The second stage is related to reducing losses in DN using reactive power capabilities from PVs, which defines the optimization problem as a fully centralized observed from the distribution system operator’s (DSO) point of view. The optimization problem is realized under the co-simulation approach in which the power system analyzer and computational intelligence (CI) optimization method interact through an interface. This approach allows keeping the original MINLP model without approximations and using any computational intelligence method. OpenDSS is used as a power system analyzer, while particle swarm optimization (PSO) is used as a CI optimization method in this paper. Detailed case studies are performed and analyzed over a single-day period. To study validation and feasibility, the proposed model is evaluated on the IEEE LV European distribution feeder. The obtained results suggest that a combination of conventional control mechanisms (OLTC) and inverter-based sources (PVs) represent a promising solution for DSO and can serve as an alternative control method in active distribution networks.
There is a rising trend to integrate different types of distributed generation (DG), especially photovoltaic (PV) systems, on the roofs of existing consumers, who then become prosumers. One of the ...prosumer impacts is voltage violations, which conventional strategies find hard to solve. However, some prosumers, such as those with PV with inverters in their configurations, can actively participate in voltage optimization. To help find the optimal PV inverter setting with the objective of voltage optimization, an optimal power flow (OPF) can be a promising and reliable tool. This paper tries to shed light on the complex problem of voltage optimization in distribution networks (DNs) with PV prosumers. Relevant scientific papers are analyzed and optimization characteristics such as objective functions, variables, and constraints are summarized. Special attention is given to the systematization and classification of papers according to the mathematical formulation of the optimization problem (linear, nonlinear, integer, etc.) and the applied solving methods. Both analytical and computational intelligence optimization methods as well as their advantages and limitations are considered. Papers are also categorized according to the distribution network model used for testing the developed solutions.
Stochastic production from wind power plants imposes additional uncertainty in power system operation. It can cause problems in load and generation balancing in the power system and can also cause ...congestion in the transmission network. This paper deals with the problems of congestion in the transmission network, which are caused by the production of wind power plants. An optimization model for corrective congestion management is developed. Congestions are relieved by re-dispatching several cascaded hydropower plants. Optimization methodology covers the optimization period of one day divided into the 24 segments for each hour. The developed optimization methodology consists of two optimization stages. The objective of the first optimization stage is to obtain an optimal day-ahead dispatch plan of the hydropower plants that maximizes profit from selling energy to the day-ahead electricity market. If such a dispatch plan, together with the wind power plant production, causes congestion in the transmission network, the second optimization stage is started. The objective of the second optimization stage is the minimization of the re-dispatching of cascaded hydropower plants in order to avoid possible congestion. The concept of chance-constrained programming is used in order to consider uncertain wind power production. The first optimization stage is defined as a mixed-integer linear programming problem and the second optimization stage is defined as a quadratic programming (QP) problem, in combination with chance-constrained programming. The developed optimization model is tested and verified using the model of a real-life power system.
The integration of distributed energy sources transforms passive distributed grid, in which the energy flows only in one direction (from the source to the consumer), in an active one, in which energy ...flows in both directions. To maximize positive impacts, which distributed generation (DG) can provide to the distribution network, it is necessary to determine the optimal allocation of distributed generation. The optimal allocation can be determined by using the optimization method. There are two main categories: exact methods (traditional) and heuristic (non-traditional) methods. Exact methods search for global optimum while heuristic methods achieve satisfactory solutions with greater computation speed. This paper gives a brief review of non-traditional methods used for determining optimal location and optimal power of DG with the aim to reduce real power losses and to improve voltage characteristics. Also, there is a review of the application of those methods in determining the optimal power, optimal location and optimal cycle of charging/discharging of electrical energy storage systems.
In this paper, a fuzzy expert off-line system has been developed for fault diagnosis in the distribution network based on the structural and functional operation of the relay and circuit breakers. ...Functional operations (correct operation, false operation and
failure to operate) of the relays and circuit breakers are described by fuzzy logic. Input data for the proposed fuzzy expert fault diagnosis system (FDS) are status and time stamps of the alarms, associated with relays and circuit breakers. The diagnostic system
from a huge number of alarms sets, logically organizes and quantifies the diagnosis. FDS can diagnose correct operation, false
operation and failure to operate of the relays and circuit breakers. Also, it can identify and quantify fault location based on the
Hamacher’s operator of a fuzzy union. The additional contribution of this paper is in modeling unknown information using linear
fuzzy membership function. Statuses of certain components may be unknown due to telemetry failures or are simply unavailable to
the operator and proposed FDS can make diagnosis in such a situation. Developed fuzzy expert FDS is tested on the two examples
of faults in real life distribution network
A new technique for identifying the location of a fault on a power line utilizing neural networks is presented in this paper. Specifically, the procedure involves four stages (three of which employ ...neural networks): gathering voltage input data via simulation, classifying the fault type, detecting the faulted line, and determining the fault position on the power line. This model was developed and tested for the IEEE 39 bus test system. Input voltages are obtained using DigSILENT PowerFactory software in which a set of three-phase and single-phase short circuits are simulated. Not voltages from all buses are used for the subsequent stages, only voltages from the optimally placed 12 buses in the IEEE 39 bus test system are used. In the second step, the first neural network is employed in order to classify the fault type – single-phase or three-phase. In the second stage, another neural network is used to determine the faulted line and in the third stage, the last neural network is developed to determine the fault position on the faulted line.
This paper presents an analysis of the harmonic influence of an electric vehicle charging station (EVCS) on the harmonic distortion of the voltage in a low-voltage (LV) distribution network. The ...analysis was performed by simulations of harmonic power flows for different sources of harmonic distortion. In the first case, the source of harmonic distortion is existing non-linear loads in the 0.4 kV network. In the second case, EVCS is added, and in the third case, the photovoltaic power plants are added as another harmonic distortion source. Input data on harmonics for the 0.4 kV network and EVCS were obtained by measurements in the real life and input data for the harmonic influence of the photovoltaic power plants is taken from the literature. The results of the simulations indicate the possibility of deteriorating the power quality when analyzing the joint impact of EVCS and photovoltaics.
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