Voltage Profile Improvement Research Articles

A Mayfly Algorithm-Based Optimal Placement of Capacitor for the Minimization of Losses and Improvement of Voltage Profile in a Microgrid

In this work, an algorithm based on mayfly is presented towards the optimal capacitor placement for the minimization of losses and improvement of the voltage profile. It employs the concept of fixed and switched capacitor with the former serves as an alternative to later. A factor based on loss sensitivity was employed in locating a candidate bus, this helps in search space reduction and optimal sizing and placement of capacitor were realized using the mayfly algorithm. The effectiveness of this technique was tested on the standard 10 bus and 15 bus radial distribution system which upon comparison the result surpassed that of the previous method .

Optimal allocation of multiple distributed generation units in power distribution networks for voltage profile improvement and power losses minimization

Optimal allocation of multiple distributed generation units in power distribution networks for voltage profile improvement and power losses minimization

Optimal sizing and placement of shunt capacitors on the distribution system using Whale Optimization Algorithm

This paper aims at power loss minimization and reduction of cost due to losses in the distribution network as well as improvement of the network voltage stability and profile via optimal shunt capacitor allocation. The optimal shunt capacitor allocation was obtained using Whale Optimization Algorithm considering technical (real power loss and VSI) and economic objective functions as sub-optimal allocation may result in undesired effects on the network. The obtained optimal sizes of the shunt capacitors were placed on the obtained location of the distribution networks to ascertain the behavior of the networks before and after their placements taking power loss, cost due to losses, and voltage stability index as the performance metrics. A comparison of these performance metrics under four cases, namely base case (case one), installation of one SC (case two), installation of two SCs (case three), and installation of three SCs (case four) were demonstrated using standard IEEE 33-bus and Dada 46-bus distribution networks. The results gave a percentage loss reduction of 33.74% with 27.60% annual net saving for the IEEE 33-bus network and 22.24% loss reduction with 25.60% annual net saving for the Dada 46-bus network. Hence, reduction in the total power losses and costs. Also, the voltage profile and voltage stability index were significantly improved.

BONMIN solver-based coordination of distributed FACTS compensators and distributed generation units in modern distribution networks

The problems of increasing electricity consumption and atmospheric pollutants emissions are targeted as critical challenges for power transfer in modern distribution networks. In order to tackle this issue, many researchers have proposed the incorporation of Distributed Generator (DG) units, as well as different types of reactive power compensation devices, which will contribute to the increase of networks efficiency through loss minimization, voltage profile improvement, or even increasing transmission line’s capacity. This paper addresses the optimal allocation/coordination of DG, Distributed Static VAR Compensator (D-SVC), and Distributed Thyristor-Controlled Series Compensator (D-TCSC) to reduce total power loss in the distribution network. The allocation problem is formulated as a mixed-integer nonlinear programming (MINLP) and is solved using a basic open-source MINLP (BONMIN) solver embedded in GAMS. The proposed method was tested in IEEE 16-bus and 33-bus distribution test systems, where two cases were considered. Firstly, BONMIN solver is used for allocation of D-SVC, and D-TCSC, respectively, where the results showed that incorporation of these devices leads to reduction of the active power losses, while the minimal losses and highest efficiency increase for both test networks occurred in the case where 3 D-TCSCs allocated. Secondly, a coordinated allocation of DGs and D-SVCs, as well as DGs and D-TCSCs, is presented, where it was shown that coordination of these devices leads to even greater loss reduction, i.e. increased efficiency. Also, it was concluded that DG and D-TCSC coordination is better suited for loss reduction in the 16-bus system, while DG and D-SVC coordination leads to greater loss reduction for the 33-bus system. Furthermore, the comparison between BONMIN and metaheuristic methods was performed for DG allocation and DG and D-TCSC coordination in IEEE 33-bus system, where it was concluded that BONMIN performs better in terms of minimal power loss, compared to the results which were presented in the available literature. Finally, the BONMIN solver’s performance is evaluated using three parameters: number of nodes, number of iterations, and total execution time, where the numerical analysis showed that BONMIN is efficient in solving the addressed problems.

Hierarchically Coordinated Voltage Control in Seaport Microgrids Considering Optimal Voyage Navigation of All-Electric Ships

The uncoordinated scheduling and control of all-electric ships (AESs) will impose great challenges on voltage profiles in seaport microgrids. This article proposes a three-stage hierarchically coordinated voltage control strategy in seaport microgrids considering the optimal voyage navigation and scheduling of AES. In stage one, we first propose an arrival time estimation method for AES to reduce the potential voltage violation risk in different seaport microgrids. The optimal power flow (OPF) is then performed in each microgrid to determine the day-ahead dispatch of on-load tap changer (OLTC) and inverter-based renewable energy resources (RESs). In stage two, the optimal route planning is carried out based on the sea states and the Dijkstra algorithm. The voyage and generation scheduling of AES are formulated as optimization problems and solved by CPLEX solvers. In stage three, a real-time local voltage control strategy is performed to mitigate fast voltage violations. To fully exploit the voltage support capability of energy storage systems (ESSs) on berthed-in AES, both constant charging mode and voltage control mode are designed to regulate voltages while ensuring sufficient SOC levels of ESS when leaving the seaport. The simulation results verify the effectiveness of the proposed method both in saving the generation cost of AES and improving voltage profiles in seaport microgrids.

Combined Approach for Power Loss Minimization in Distribution Networks in the Presence of Gridable Electric Vehicles and Dispersed Generation

Increased electric vehicles (EVs) penetration into the distribution network burdens the system during the charging process. But the same turns out to be advantageous if the EVs are used to support the utility based on the requirement. In this work, an attempt is made to efficiently schedule both the grid-to-vehicle and vehicle-to-grid operational modes of EVs with the objective of reducing power loss in the distribution system in presence of distributed generation (DG). The EVs are modeled by considering the dominating factors, such as EV State of Charge (SoC), trip conditions, EV battery capacity, charging/discharging levels. An improvement to the existing grasshopper optimization technique is also suggested in this article, which enhances the exploring capability of the metaheuristic algorithm. The presented methodology is a combination of smart charging method, voltage stability index, and enhanced grasshopper optimization algorithm (EGOA), which decides the size of DGs to be placed in the system. The proposed hybrid approach tries to schedule both the EVs and DGs so as to achieve reduced power loss and improved voltage profile. In order to test the robustness of the proposed strategy, various analyses considering uncertainty in EVs and load conditions are performed.

Optimal Location and Sizing of BESS for Performance Improvement of Distribution Systems with High DG Penetration

This work proposes an optimal location and sizing of battery energy storage system (BESS) installation for performance improvement of distribution systems with high distributed generation (DG) penetration level where the DGs comprise photovoltaics (PV) and wind turbines (WT). The installation of the BESS can reduce costs incurred in the systems, alleviate reverse power flow when the systems are in the high DG penetration level, and also achieve peak shaving during high demand. To find the optimal location and sizing of the BESS, three optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), and salp swarm algorithm (SSA), are applied, and their performances are compared. The considered objective function is the system costs consisting of transmission loss cost, peak power cost, and voltage deviation cost. The system performance improvement is compared in terms of transmission loss, peak demand, and voltage regulation reductions. IEEE 33- and 69-bus distribution systems with high DG penetration are tested to investigate the performance improvement of the BESS installation. The results found that the installation of the BESS could successfully decrease system cost, improve voltage profile, reduce power losses, alleviate reverse power flow, and achieve peak shaving where PSO and SSA are found to be the best competitive algorithms. So, the proposed method can be further applied to find the optimal location and sizing of the BESS to improve the performance of practical systems in the future.

System-Based Testing of Protection for Center-Tapped Shunt Capacitor Banks

In power systems, capacitor banks play a significant role in improving voltage profiles, reducing losses, and adjusting power factors. Security measures must be implemented quickly and reliably to protect them from a wide range of threats. As a consequence of capacitor bank failures, finding and fixing the damaged units/elements is more difficult, which may lead to voltage control difficulties or the loss of any of these benefits. The paper shows the application of system-based testing methods for protection systems using RelaySimTest software, which works with OMICRON injection test sets. System-based testing methods are applied to test voltage differential protection for center-tapped shunt capacitor banks. The use of system-based testing methods has many advantages over conventional testing methods, which include distributed testing, transient state conditions testing, etc., which in turn result in cost savings during the commissioning and testing phase. The impact of external faults on bank installation has been tested successfully.

Review of Different Methods for Siting and Sizing Distributed Generator

Distributed generator has been confirmed to be a means by which installation of a new centralized generator can be delayed or postponed in the era of deregulation. It helps to minimize line losses and improve voltage profile. the benefits associated with distributed generator can be greatly harnessed when DG is optimally sited and sized within power system network. In this study, different methods used by previous researchers were extensively reviewed. The summary of the methodologies from previous works were itemized one after the other. This was done under the impact of distributed generator in a network. These methodologies are summaries under three categories namely; analytical, meta-heuristic and hybrid optimization methods. All the methods are based on solving non-linear load flow solution except the Inherent Structural Network Topology. In this review work, the inherent structural network topology is recommended for further studies to solve power system problems.

Optimization of On-Grid Hybrid Renewable Energy System: A Case Study on Azad Jammu and Kashmir

Expansion of modern power systems due to increasing energy demands face the challenges of grid reinforcement cost, size and complexity, transmission losses, and environmental factors. Placement of renewable energy sources (RES) based generation systems addresses these challenges. However, the size and placement location of RES-based system require optimization of installation and operational cost with better return on investment and reduction of greenhouse gas emissions. This paper presents an optimized solution for RES-based generation system to be installed with the existing power system of Azad Jammu and Kashmir (AJK) region that is facing power shortfall and load shedding. The weather and climate data from NASA and National Renewable Energy Laboratory (NREL) have been used and various models of on-grid hybrid renewable energy system (HRES) are compared to highlight their techno-economic benefits. An optimal hybrid photovoltaic, wind, and hydroelectric energy-based generation system is proposed with a significant reduction in cost of energy, net present cost, initial costs, and GHG emissions. Installation of the proposed hybrid RES-based generation system guarantees reduction in system power losses and line flows with an improved voltage profile of the system.

Optimal planning of uncertain renewable energy sources in unbalanced distribution systems by a multi‐objective hybrid PSO–SCO algorithm

High penetration of Renewable Energy Sources into unbalanced distribution systems faces many challenges due to the uncertainty nature of both Renewable Energy Sources and loads as well as the unbalance degree of the distribution systems. This paper proposes the planning of Renewable Energy Sources in unbalanced distribution systems. Different types of Renewable Energy Sources, photo-voltaic and Wind are considered. A multi-objective optimisation problem is formulated using non-dominated sort and crowing distance for multi objective hybrid algorithm that combines the merits of Particle Swarm Optimisation and Sine Cosine Optimisation algorithms. Three objectives, improving voltage profile, power losses minimisation, and minimisation of voltage unbalance, are considered. The proposed method determines the optimal Renewable Energy Sources' specifications such as site/size/type of distributed generators, number of photo-voltaic modules or wind turbines in each distributed generator and their power factor and connection phases. Also, it determines the optimal setting of substation tap changer and system voltage regulators. Moreover, both Renewable Energy Sources and loads uncertainty are considered and modelled using Monte Carlo simulations. An improved matrix-based backward–forward load flow method is developed by using coefficient matrices. The proposed procedure is conducted on IEEE 13-node, 37-node, and 123-node unbalanced distribution systems. The proposed algorithm results compared with individual optimisers show significant performance improvements. The optimal plans resulted by using the proposed hybrid algorithm achieve a reduction in power losses that reached 89% in some cases. Also, the system unbalance index is reduced with a ratio reached 34%. Large improvement in the system voltages profile all over the year is achieved as the system voltage profile index is reduced by a ratio reached 70%.

An Overview of Soft Open Points in Electricity Distribution Networks

Soft open points (SOPs) are power electronic devices that are usually placed at normally open points of electricity distribution networks to provide flexible power control to the networks. This paper gives a comprehensive overview of both academic research and industrial practice on SOPs in electricity distribution networks. The topologies of SOPs as multi-functional power electronic devices are identified and compared, which include back-to-back voltage source converters, multi-terminal voltage source converters, unified power flow controllers, and direct AC-to-AC modular multilevel converters. The academic research is reviewed in three aspects, i.e., benefit quantification, control, and optimal siting and sizing of SOPs. The benefit quantification indices are categorized into feeder load balancing, voltage profile improvement, power losses reduction, three-phase balancing and DG hosting capacity enhancement. The control of SOPs is summarized as a three-level control structure, where the system-level and converter-level control are further discussed. For optimal siting and sizing of SOPs, problem formulation and solution methods are analyzed. Besides the academic research, practical industrial projects of SOPs worldwide are also summarized. Finally, opportunities of research and industrial application of SOPs are discussed.

Intelligent transformer tap controller for harmonic elimination in photovoltaic interfaced micro-grid network

The photovoltaic (PV) system is interfaced to the microgrid through an on-load tap changer (OLTC) transformer. Pulse width modulation (PWM) AC choppers are used to control these OLTC but create harmonics owing to their non-optimal firing angles. In this paper, Differential Evolution (DE) and Grey Wolf Optimizer (GWO) techniques are used for optimal control of an AC chopper to keep the harmonic distortion of voltage and current within limits. An IEEE-13 node network is adapted as a micro-grid with PV integration through transformers. The simulated results are validated by a laboratory set-up. A dSPACE experimental set-up is used for the real-time implementation of optimization algorithms. The results show that the DE gives firing angles that improve power quality, particularly a reduction in total harmonic distortion and improvement in the root mean square voltage profile. The research is particularly useful for the on-line power quality improvement in PV interfaced microgrid networks.

Sizing and Allocation of DGs in A Passive Distribution Network Under Various Loading Scenarios

Integration of renewable energies in distribution system networks has grown significantly over the years. Finding the optimal location and precise capacity of distributed generations (DGs) in various load conditions is a profound challenge. This article proposes an analytical approach to find the optimal location and capacity of different characteristic DGs in a passive distribution network (PDN). Real-life scenario of power consumption is considered by using different load scenarios. Key benefits include loss reduction and improved voltage profile of the PDN. Special attention is paid for the role of DGs to provide active/reactive power in different load scenarios. Monetary benefits are calculated for optimized installed generators. Extensive case studies have been performed over IEEE-33 and 69 bus system to verify the benefits of the proposed methodology.

Optimal Sitting and Sizing of Distributed Generators using Pareto-Based Multi-Objective Particle Swarm Optimization for Improving Power System Operation

Utilization of distributed generation (DG) in the distribution network has become trending ever since it has been introduced with proven benefits. DG plays a significant role in improving the quality and quantity as well as the efficiency of the power transmission and distribution system. By allowing smaller generating units to operate in parallel with the main grid, a continuous reliable power supply with lower power loss and higher power output can be achieved. However, improper placement and inappropriate sizing of DG leads to a moderate level performance in terms of power loss and voltage profile. Limited studies have been conducted on mitigating these problems in order to maximize the benefits from DG’s application. To solve this problem, a research is proposed which mainly aims in determining the location and size of DG as well as improving the voltage profile and efficiency of the distribution system significantly. A metaheuristic algorithm called Multi-Objective Particle Swarm Optimization (MOPSO) method is used to simultaneously determine the optimal size and location of DG. To assist the proposed method, Pareto analysis is incorporated to handle conflicting objectives. This method is then tested on the IEEE 14-bus and 33-bus distribution systems under two different conditions which is before and after optimization. The percentage of power loss reduction is calculated and the voltage profile is drawn to compare the output of both conditions. Evaluations from the tests have proven that by using the Pareto-Based MOPSO method, the most optimal size and location of DG in producing an improved voltage profile with lower power loss is identified.

SMA-based optimal energy management study in a connected PV/MT/ DG/V2G/BESS/WT on IEEE-33 bus considering network losses and voltage deviations

The unpredictable nature of renewable energy resources (RERs) makes obtaining optimum operation and grid integration in today’s smart power distribution networks challenging. Thus, to mitigate the fluctuations in RERs, the penetration of diesel generators, batteries, and electric vehicles (EV) must be considered for an effective energy management study (EMS) in the IEEE-33 bus system. This paper addresses the energy management of a microgrid linked to the main power system under deterministic and probabilistic circumstances. Apart from economic considerations, modern distribution networks must maintain an acceptable range of system reliability indexes. Failure of reliability in the distribution network may result in irreversible harm to the distribution network. For multi-objective functions such as cost reduction, voltage profile improvement, and voltage stability improvement are the main objectives of this article. An efficient method known as a novel slime mould algorithm (SMA) is used to solve these issues and validate the performance with the existing evolutionary algorithms. However, the SMA can optimally address the grid-connected various types of RERs installed, which can significantly compensate network losses, voltage deviations and improve the system performance. Finally, the algorithm’s effectiveness on the EMS approach is verified under different algorithms through 2021a MATLAB/Simulink and the proposed methods prove the best results with the convergence of other algorithms also.

Optimal Service Restoration Scheme for Radial Distribution Network Using Teaching Learning Based Optimization

In the event of a fault isolation process, all loads located downstream from the faulted point become out of service, and as a consequence, the power interruption affects a greater portion of the radial distribution system. This paper proposes an optimal Service Restoration (SR) method that entails changing the network topology configuration via optimal tie-switch and section switch combinations. However, when the network topology configuration is performed, it results in increased load currents. As a result, some Protective Devices (PDs) can operate undesirably and some network branches may become unprotected. Therefore, it is essential to consider protection constraints in the SR problem to maintain service continuity during power interruptions. The proposed method aims at optimal SR with minimum out-of-service loads, minimum power loss, and improved voltage profiles and at the same time ensures PDs operate correctly during the normal and overloading conditions. The proposed method was carried out on the Debre Markos distribution networks, using the Teaching Learning Based Optimization (TLBO), Particle Swarm Optimization (PSO), and Differential Evolutionary (DEV) algorithms. The proposed SR was carried out considering and without considering protection constraints. The obtained SR topology was not feasible for SR without considering protection constraints, since some PDs fail to operate properly in normal loading conditions. After executing the proposed SR algorithms by considering protection constraints for a single fault case, the power loss reductions in TLBO, DEV, and PSO were 64.9073%, 45.9073%, and 55.358 %, respectively. The minimum voltage profiles obtained in each proposed TLBO, DEV, and PSO algorithm were 0.96%, 0.95%, and 0.96%, respectively. In each algorithm, except for the branch under fault, all healthy out-of-service branches were restored. When the protection constraints were considered in an optimal SR, load current did not exceed the rating of the fuses. The results show the importance of considering protection constraints during SR to prevent dysfunction of the PDs in the network. Comparative analyses were carried out on each algorithm and TLBO algorithms performed better than PSO and DEV for search functions.

A new approach for optimal photovoltaic resources in distribution networks with reconfiguration based on L_∞

PurposeIn the vast majority of published papers, the optimal allocation of photovoltaic distributed generation (PVDG) units and reconfiguration problems are proposed along with the number of PVDG used in the simulation. However, optimisation without selecting the number of PVDG units installed in the distribution grid is insufficient to achieve a better operational performance of power systems. Moreover, multi-objective installation of PVDG units and reconfiguration aims to simultaneously relieve congestion problems, improve voltage profile and minimise the active and reactive power losses. Therefore, this paper aims to propose a new modified camel algorithm (NMCA) to solve multi-objective problems considering radial distribution system to achieve secure and stable operation of electric power system with good performance.Design/methodology/approachIn this paper, the decision variables include the location and size of PVDG units with specific rang to determine the number of PVDG units needed to install and open network lines determined using NMCA based on the L_∞ technique. This also satisfies the operating and radial constraints. Furthermore, a benchmark comparison with different well known optimisation algorithms has been made to confirm the solutions. Finally, an analysis of the findings was conducted, and the feasibility of solutions was fully verified and discussed.FindingsTwo test systems – the institute of electrical and electronics engineers (IEEE) 33-bus and IEEE 69-bus, were used to examine the accuracy and effectiveness of the proposed algorithm. The findings obtained amply proved the efficiency and superiority of the NMCA algorithm over the other different optimisation algorithms.Originality/valueThe proposed approach is applied to solve the installation PVDG unit’s problem and reconfiguration problem in the radial distribution system, satisfying the operating and radial constraints. Also, it minimises active and reactive power losses and improves voltage profile.

Water, Energy and Food Algorithm with Optimal Allocation and Sizing of Renewable Distributed Generation for Power Loss Minimization in Distribution Systems (WEF)

Distributed generation (DG) plays a vital role in electrical power networks. However, power loss reduction, voltage profile improvement, friendly environment, and reliability are all benefits of DG units. In this research work, a worthwhile methodology is recommended for optimal allocation of traditional (gas turbine) and renewable energy sources that are based on distributed generators which include solar and wind in the distribution system. The major objective of the research paper is the minimization of real, reactive power losses and emissions produced during the application of these conventional sources. Originally, the best locations to place this DG are identified using the concept of water, energy, and food algorithm (WEFA). The number and sizes of these renewable energy sources selected (wind and solar) are determined by applying the concepts of the Dragonfly Algorithm. The Weibull and beta distribution functions are modeled to extract the exact position to fix our DGs to minimize losses within the distribution network. To assess the performance of WEF five different cases scenario considered are DG capacity, Location of Bus, voltage profile, maximum power loss as well as utilization rate. The proposed WEF Algorithm is tested on the IEEE standard 33-bus system. The simulated results were compared with others found in literature and found to be better in terms of power loss reductions.

Grid-connected photovoltaic system to mitigate momentary voltage dip based on the balance between the active and reactive powers

With a great potential yet to be explored in Brazil, the grid-connected photovoltaic system, besides supplying the active power, can also contribute to improve the voltage level grid providing reactive power. Therefore, this work proposes to use a Grid-Connected Photovoltaic System (GCPVS) equipped with a control that uses the automatic voltage regulator (AVR) to balance the injection of the active and reactive powers, thus softening the short-duration voltage variation, more specifically the momentary voltage dip. For this purpose, the GCPVS was connected in part of a real distribution grid that attend the block 1106 South of Palmas city, state of Tocantins, northern region of Brazil. It is shown that the active and reactive power delivered to the grid can be controlled to help the power quality of the main grid during a disturbance. During a short-circuit situation, the active power is reduced, freeing up space from the inverter capacity for maximum supply of reactive power, in this way, helping the main grid to return to an adequate voltage level. The simulation results show that such voltage profile improvement is possible. Therefore, they confirm that photovoltaic systems, even though considered small, can also provide ancillary services to the low voltage distribution grid during abnormal conditions, adding to the actions normally performed by conventional power plants