An improved wild horse optimization algorithm for reliability based optimal DG planning of radial distribution networks

Recent deployment of distributed generation has led to a revolution in distribution systems and the emergence of “smart grid” concepts. The smart grid mainly intends to facilitate integration of renewable energy sources and to achieve higher system reliability and efficiency. Different distributed generation types found in modern distribution systems can be classified into two main categories: intermittent- and dispatchable-based distributed generation; the latter has a unique capability of enabling successful islanding operation, thus improving system reliability. This article proposes a methodology for allocating dispatchable distributed generation units in distribution systems to economically improve system reliability. Distributed generation installation and operation costs are to be optimized against the reliability value, expressed as customers’ “willingness to pay” (WTP) to avoid power interruptions. Therefore, the main goal of this research work is to determine the optimal combination between distributed generation units to be installed and loads to be shed during all possible contingencies. A probabilistic load model is adopted to determine the optimal size of allocated distributed generation units.

In electrical systems the most critical disturbance is the interruption of the power service. However, the main concern for many commercial and industrial users is the mal-operation produced by voltage sags. This paper presents a study about performance of a distribution system in presence of voltage sags using a distribution generation (DG) unit and a distribution static compensator (DSTATCOM). The analysis is performed by using a stochastic generation of disturbances method and ATP/EMTP software tool. Several case studies in the IEEE-13 bus test feeder taking to account different DG locations and penetration levels for DG unit are presented. In addition, the relation between the injected DSTATCOM reactive power, the type of sag and the location of affected nodes is considered. Simulations show that for IEEE-13 system the DSTATCOM is the best alternative for sags mitigation. However, the DG unit is an alternative that can be considered in larger distribution systems to reduce the effects of voltage sags.

Minimizing power loss and improving voltage stability are crucial aspects of power systems, driven by transmission line contingencies, financial losses for utilities, and potential power system blackouts. Optimal allocation comprising the sizing and operating power factor—of Distributed Generation (DG) units and capacitor banks (CBs) significantly enhances power system efficiency. Efforts by power system operators and researchers focus on addressing issues related to power loss, energy loss, voltage profiles, and voltage stability through the strategic placement of DGs and CBs. Additionally, optimal DG and CB allocation protects the distribution system from unforeseen events and enables operators to run the system in islanding mode when necessary. The integration of DG units and CBs in distribution systems aims to enhance overall system performance. This research paper introduces a Water Cycle Algorithm (WCA) for the optimal placement and sizing of DGs and CBs. The proposed method targets both technical and economic benefits, considering multiple objective functions: minimizing power losses, reducing voltage deviation, lowering total electrical energy costs, and improving the voltage stability index. The WCA emulates the natural water cycle, from streams to rivers and rivers to the sea. Five different operational scenarios are evaluated to test the performance of this methodology. Simulations are conducted on distribution systems: the IEEE 69-bus test system and the Sankhu feeder network, a real system. The results demonstrate the superior performance of the proposed WCA compared to other optimization algorithms. The findings highlight the WCA's flexibility, efficiency, and significant improvements in economic benefits, establishing it as a promising approach for optimizing the placement of DG and CB in distribution systems.

Distributed generation (DG) is integrated in a passive distribution system to reduce power loss, improve voltage profile, and increase power output. To reap the most benefits of the distribution system, the best location and appropriate DG size must be determined. This paper presents a hybrid Grey wolf Optimizer (GWO) and Particle swarm optimization (PSO) approach for determining the best placement and DG size while considering a multi-objective function that includes active and reactive power loss minimization as well as voltage profile enhancement. Dilla distribution system was used as a case study and the weighted technique was used to convert to a single objective function while taking into account multiple constraints such as bus voltage limit, DG output limit, and branch current limit. DG penetration is limited to up 60% of the total active load on the feeder and a forward–backward sweep load flow algorithm was used to generate the load flow solutions. The findings of the study show that combining three PV-DGs (Case 3) is the best way to improve voltage profile and minimize losses. In addition, the proposed hybrid GWO-PSO algorithm performed better compared to the other four algorithms (Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), Particle swarm optimization (PSO), and sine cosine algorithm (SCA)) in terms of achieving the best multi-objective function (MOF) outcome.

The paper seeks analysis of unbalance radial distribution system (URDISY) with distributed generator (DG) and distribution static compensator (D-STATCOM). The paper's main objectives are optimal allocation DG and D-STATCOM through a metaheuristic technique known as Atom Search Optimization (ASO) algorithm, intending to provide real and reactive power support by enhancing voltage profile reducing total real and reactive line losses. Also, impact of DG and D-STATCOM on total savings in cost of energy losses. Further, different loading conditions and load growth model are considered for better planning of the power distribution system. The DG and D-STATCOM power factors are considered unity and zero pf lag, respectively. The results are obtained for standard 25-bus URDISY using simulation in MATLAB.

Distributed generation (DG) units has become an essential part of the smart grid due to increased penetration of renewable energy sources. These units help to improve power quality according to their position and control. Grids could face unexpected faults which affects power quality most especially voltage profile and power losses. This paper presents the potential application of (DG) units as a solution for improving voltage profile and mitigating power losses in loop distribution systems in case of faults for different positions of DG unit. Load flow analysis of a 66/20 kV distribution line network is performed to calculate the various values of voltage and power flow at each bus for different faults in each position of DG unit. Simulation of this distribution substation network with DG units have been developed in the MATLAB/Simulink Environment. The objective of this study is enhancement of voltage profile at various buses and the improvement in power flows in the distribution network with reduction in branch losses in the presence of fault.

Increased non-linear residential loads in today's distribution system is a concern due to the harmonics related power quality issues. The situation gets worsened by the harmonic resonance introduced by the installation of power factor correction (PFC) capacitor banks in the distribution network. At the same time, more and more renewable energy-based distributed generation (DG) units are being installed in the residential area. These DG systems can be used as an effective way to mitigate the harmonic related power quality problems introduced by the nonlinear residential loads. In literature, very limited work has been done to identify harmonic compensation priorities that should be assigned to different DGs operating at different locations of the distribution system for improved compensation performance. This issue is addressed in this paper. A selective harmonic compensation scheme based on modal analysis is developed to assign compensation priorities on DGs operating at different distribution system nodes for improved compensation performance. A modeled residential distribution system containing distribution components such as distribution line, PFC capacitors, transformers, and household appliances along with DG units is used to verify the improvement of compensation performance. Experimental verification of the proposed method is also provided.

The integration of Distributed Generation (DG) in electric power systems has brought about the need for the improvement of the existing protective relaying principles used in distribution systems. This is because the integration of DG transforms the conventional single-source radial distribution system to a bidirectional multisource distribution system. Therefore, it is necessary to analyse the new short circuit fault current level, the general requirements for the integration of DG units, the requirement under abnormal conditions, power quality requirements, and the protection requirements. This chapter presents the impact of DG units on the short circuit current level and protective relaying in distribution systems. An overview of protection in conventional distribution system is first described. Afterwards, the impact of DG on the short circuit fault current and the protection of a distribution system integrated with DG are presented. Also, case studies and simulation examples on protective relaying in a distribution system integrated with DG are presented. Furthermore, some emerging technologies that can be applied to improve the protective relaying schemes in a DG-integrated distribution system are highlighted.

Distributed generations (DG) can be used to enhance power generation systems and improve distribution system efficiency. However, the installation of DG units at non-appropriate location and sizing can result in negative impacts such as an increasing in power losses and violations of system constraints. In this paper, a new DG allocation planning tool is developed for determining the optimal location and sizing of DG in practical distribution systems. The proposed planning tool is developed by writing DIgSILENT Programming Language (DPL) script in DIgSILENT PowerFactory software. The optimally placed optimal power flow (OPF) with DG is formulated as a minimization of energy losses function and a maximization of benefit to cost ratio, subjected to system constraints including real and reactive power generation, line and transformer loading, voltage profile, step voltage change, reverse power, energy losses, short circuit level, and DG operating limits. All possible locations and sizes of DG installations are evaluated and then the optimal solution is selected from the best objective function value obtained. Test results on the practical 9-bus and 437-bus distribution systems taken from Provincial Electricity Authority (PEA) of Thailand indicate that the proposed planning tool can be used to determine the optimal DG allocation without violation of system constraints.

With high penetration of power electronics-based distributed generation (DG) units, the decentralized control strategy based on droop control with virtual impedance has been widely studied in recent years. But the conventional virtual impedance cannot properly deal with the massively increasing of nonlinear loads. Therefore, an improved virtual impedance method based on second-order general-integrator (SOGI) is presented. Besides, a further value correction of reactive power in droop control is also proposed in this paper. The proposed approaches have been applied and verified in a parallel system formed by two DG units connected with nonlinear loads. The form of SOGI and derivative formula of corresponding virtual impedance in the system has been analyzed in detail. The obtained experimental results show the proposed approaches can achieve less output voltage and current distortion of DG units with nonlinear loads, and also realize good performance of power sharing.

A hybrid evolutionary algorithm for secure multi-objective distribution feeder reconfiguration

With ever increasing penetration of renewable distributed generation (DG) in distribution systems, power restoration of remote distribution feeders under emergency conditions tends to be carried out with the support of renewable DG units. The available power from the renewable DG units ensures restoration of more number of affected customers, thus, improving overall system reliability. In this paper, a probabilistic based analytical method is developed to assess system reliability in terms of system average interruption duration index and system average interruption frequency index for distribution feeders containing dispatchable and nondispatchable renewable DG units. The proposed method has been developed by implementing DG side restoration with comprehensive technical considerations, including possible failures of DG units, time-dependent patterns of load demand and DG power output, and single-stage and two-stage restoration. The proposed analytical method is validated by comparing with the Monte Carlo simulation and results are presented.

The primary goal of a power distribution system is to provide nominal voltages and power with minimal losses to meet consumer demands under various load conditions. In the distribution system, power loss and voltage uncertainty are the common challenges. However, these issues can be resolved by integrating distributed generation (DG) units into the distribution network, which improves the overall power quality of the network. If a DG unit with an appropriate size is not inserted at the appropriate location, it might have an adverse impact on the power system’s operation. Due to the arbitrary incorporation of DG units, some issues occur such as more fluctuations in voltage, power losses, and instability, which have been observed in power distribution networks (DNs). To address these problems, it is essential to optimize the placement and sizing of DG units to balance voltage variations, reduce power losses, and improve stability. An efficient and reliable strategy is always required for this purpose. Ensuring more stable, safer, and dependable power system operation requires careful examination of the optimal size and location of DG units when integrated into the network. As a result, DG should be integrated with power networks in the most efficient way possible to enhance power dependability, quality, and performance by reducing power losses and improving the voltage profile. In order to improve the performance of the distribution system by using optimal DG integration, there are several optimization techniques to take into consideration. Computational-intelligence-based optimization is one of the best options for finding the optimal solution. In this research work, a computational intelligence approach is proposed to find the appropriate sizes and optimal placements of newly introduced different types of DGs into a network with an optimized multi-objective framework. This framework prioritizes stability, minimizes power losses, and improves voltage profiles. This proposed method is simple, robust, and efficient, and converges faster than conventional techniques, making it a powerful tool of inspiration for efficient optimization. In order to check the validity of the proposed technique standard IEEE 14-bus and 30-bus benchmark test systems are considered, and the performance and feasibility of the proposed framework are analyzed and tested on them. Detailed simulations have been performed in “MATLAB”, and the results show that the proposed method enhances the performance of the power system more efficiently as compared to conventional methods.

To manage the microgrid effectively, it is important to get the power information among multiple distributed generation (DG) units. However, when the droop control method is adopted, as the corresponding DG units cannot be simply modeled as VF or PQ buses, the conventional power flow algorithm may become inapplicable. To solve this issue, a time domain iteration (TDI) based power flow algorithm is hereby proposed. Firstly, a microgrid model is prepared, containing a network model and several DG unit models. Then, the proposed TDI is executed for power flow calculation, which mimics the real-time operation of microgrids. In each iteration, the DG unit models input voltages and currents to the network model; then the network model changes its state accordingly and feeds related parameters back to those DG unit models. As the DG unit models simulate the behavior of actual DG units, the proposed algorithm is not limited to the droop control governed microgrids. Moreover, as the TDI has definite physical meaning, convergence problems can be avoided. Finally, the validity of the proposed power flow algorithm is verified through the Matlab simulation results from an 8-bus microgrid system.

Distributed generation (DG) significantly improves power system reliability and voltage profile, and reduces power losses. These benefits can be maximized by optimizing the DG utilization, which greatly depends on adequate number, size, and placement of DG. This study proposes a high-convergence optimization technique for optimal DG placement in distribution networks, aiming to reduce power losses and improve voltage profile and voltage stability index. The technique is tested on a 7-bus system before being verified on the IEEE 33-bus system. After validation, it is tested on a 71-bus distribution network (DN). The estimated ideal size for a single DG is used as a limit for determining the optimal placement and size of multiple DG units. The results show that there is a loss reduction of 70.09%, 61.43%, and 71.15% for the 7-bus, IEEE 33-bus, and 71-bus systems, respectively, from their base case loss. The average absolute error of voltage of the aforementioned buses also shows similar enhancement, decreasing from 0.0144, 0.0561, and 0.0527, to 0.0058, 0.0209, and 0.0184, respectively. The voltage stability index of each DN has increased significantly in comparison to the base case. The comparison demonstrates that the proposed technique can provide better results for any size of distribution network.