Voltage Profile Improvement Research Articles

A Proportional and Weight Based Decentralized Charge Controller of Electric Vehicles for the Improvement of Local Voltage Profile

A Proportional and Weight Based Decentralized Charge Controller of Electric Vehicles for the Improvement of Local Voltage Profile

Modelling smart energy consumption with hybrid demand management in off-grid electrical system considering techno-economic indices

This study proposes day-ahead power scheduling for electrical systems in off-grid mode, emphasizing consumer involvement. Bi-Demand Side Management (DSM) approaches like strategic conversion and demand shifting are proposed for consumer involvement. Multiple objectives are modelled to voltage profile improvement and reduce the operation energy cost. The non-dominated solutions of the voltage of buses and operation energy cost are generated by enhanced epsilon-constraint technique, simultaneously. The General Algebraic Modeling System (GAMS) software is proposed for solving optimization problems. A combination of decision-making methods like weight sum and fuzzy procedures are implemented for finding optimal solution non-dominated solutions. The proposed method’s effectiveness is confirmed through numerical simulations carried out on several case studies that utilize the 33-bus electrical system. The findings illustrate the substantial effectiveness of demand-side participation in improving power dispatch and the optimal rate of multiple objectives. By using DSM, operation cost is reduced by 21.58% and the voltage index is improved by 13.36% than the lack of implementing DSM.

Control strategy of battery inverter for voltage profile improvement in low voltage networks with high PV penetration level

Control strategy of battery inverter for voltage profile improvement in low voltage networks with high PV penetration level

Active and Reactive Power loss Minimization Along with Voltage profile Improvement for Distribution Reconfiguration

Optimal distribution network reconfiguration (DNR), distributed generations location and sizing (DGs-LS), tap changer adjustment (TCA), and capacitors bank location and sizing (CAs-SL) are different methodologies used to reduce loss and enhance the voltage profile of distribution systems. DNR is the process of changing the network topography by changing both sectionalized and tie switch states. The optimal location looks to find the optimal setting of the DG and CA within the distribution network. Optimal size seeks to find the optimal output generation of both DG and CA. The TCA looks to find the optimal position for TC. These methods are challenging optimization problems and resort to meta-heuristic techniques to find a globally optimal solution. This paper presents a new methodology with which to simultaneously solve the problem of DNR, DGs-LS, TCA, and CAs-SL in distribution networks. This work aims to minimize active and reactive power losses, including voltage profile improvement using a multi-objective decision approach. The firefly algorithm (FA) and analytic hierarchy process (AHP) are used to optimize the fitness function and determine the function weight factors through the use of MATLAB software. Several scenarios were considered on the IEEE 69-bus network. In terms of active power and reactive losses, reductions in the test system of 96.16% and 92.7%, respectively, were achieved, evidencing the positive impact of the proposed methodology on distribution networks.

AVALIAÇÃO DA INFLUÊNCIA DA INSERÇÃO DA GERAÇÃO DISTRIBUÍDA EM SISTEMAS DE DISTRIBUIÇÃO DE ENERGIA ELÉTRICA

This paper seeks to evaluate the impacts arising from the insertion of distributed generation (DG) in electrical power distribution systems. In this circumstance, using the OpenDSS computational tool, simulations of four different scenarios were carried out, varying the DG penetration levels as a function of the total feeder load, considering a specific point of operation. Finally, the same feeder was simulated with photovoltaic generating sources distributed in bars next to the loads, in order to analyze the temporal characteristic of solar generation as a function of demand. Through the simulations, it was possible to analyze, interpret and highlight the impacts that the insertion of DG produces in the electrical power distribution systems. It was evident that the increase in DG penetration led to an improvement in the feeder voltage profile, power flow inversion and reduction of electrical losses in the feeder. It should be noted that the insertion of DG from renewable sources is a Brazilian reality and a path to be followed, since the diversification of the energy matrix in line with the use of new technologies, such as smart grids, will provide electrical power systems with greater safety, operational efficiency and quality in the product delivered to consumers.

Analysis of Voltage Profiles, Unbalance Voltages and Phase Balance Optimization of Single-Phase Customer and Photovoltaic Connection at Real Low Voltage Feeder

Abstract Voltage unbalance is common issue encountered in low voltage distribution networks, caused by uneven allocation of single-phase customers among phases. This paper analyses part of real low voltage distribution network in Bosnia and Herzegovina. The impact of single-phase customers and single-phase connected micro photovoltaic power plants (MPPP-s) were analysed. To reduce unbalance and improve voltage profiles, Phase Balance Optimization toolbox in DIgSILENT PowerFactory software was performed in six scenarios with different distribution of customers and different percentage of penetration of MPPS-s. The aim was to find method with least number of changes in customer and photovoltaic phase connection that fits within defined limits of voltage variations and voltage unbalance of European standard for power quality (EN 50160). Conclusion is that MPPP-s cause voltage increases in the network, as well as an increase in voltage unbalance, but these effects can be mitigated by proper distribution of customer loads and MPPS-s among phases.

Performance analysis of voltage profile improvement in AVR system using zebra optimization algorithms based on PID controller

Many problems are associated with dynamic changes in the power system, mainly because the number of switching loads has increased. These loads induce ineffective system behaviour, reduce the system voltage profile, and lead to improper voltage regulation. The proposed Automatic Voltage Regulator (AVR) system is intended to eliminate the above problem and preserve the system voltage at the generator terminal within the allowable range. In this work, Proportional-Integral-Derivative (PID) controllers are applied to enhance the dynamic behaviour of the AVR system. The Zebra Optimization Algorithm (ZOA) and Osprey Optimization Algorithm (OOA) algorithms are implemented to optimize the system's transient response by modifying the gain of PID controller parameters, which include proportional, integral, and derivative parameters, to preserve a stable voltage profile. To achieve an optimal solution, the mathematical model of the proposed system is realized in the Internet of Things (IoT). The connected loads in the system can operate at the nominal voltage level through PID controller tuning using ZOA and OOA. The proposed system's performance is evaluated and verified with MATLAB R2023a. ZOA showed an improvement of 18.5 % with a peak overshoot of 0.01 % during the system-transient condition. Compared to conventional optimization algorithms implemented in AVR systems, ZOA provides faster responsiveness and enhanced system stability.

Multi-objective Adaptive Fuzzy Campus Placement based Optimization Algorithm for optimal integration of DERs and DSTATCOMs

The novel Adaptive Fuzzy Campus Placement based Optimization Algorithm (AFCPOA) presented in this paper is expected to solve the issue of single objective and multi objective optimal optimization problems. AFCPOA’s performance was evaluated on 25 benchmark optimization test functions and compared to other existing methods. Optimal location and sizing of Distributed Generation (DG), Distribution STATtic COMpensator (DSTATCOM), DGs and DSTATCOMs, Battery Energy Storage Systems (BESS) in the presence of PVDGs, and BESS in the presence of PVDGs and DSTATCOMs were integrated into Radial Distribution System (RDS) to fulfil the objectives. Technical advantages of DG include active power losses reduction and control of voltage dips. DSTATCOM functions as a capacitor, injecting reactive power to improve the consistency and quality of power flow and sustain voltage against any imbalance and distortion on load side or supply side. The appropriate location and capacity for BESS present a significant barrier for the integration of BESS and renewable DGs with distribution networks. The objective functions in this problem are to minimize total real power losses, reactive power losses, and voltage deviation. Additionally, the improvement of voltage profile was taken into consideration as a constraint while choosing the best location. Finally, the suggested algorithm is evaluated on IEEE 33 bus RDS and PG & E 69 bus RDS. Simulation results show the proposed method’s excellent performance and applicability.

Recursive Secondary Controller for Voltage Profile Improvement Based on Primary Virtual Admittance Control

This paper proposes a recursive, virtual admittance based, secondary controller for DG units that improves the voltage profile in distribution networks. First, the adaptation of the virtual admittance concept for the goal of voltage regulation is explained. Then, a recursive secondary controller is developed to periodically update the virtual admittance gains. The controller is formulated as an optimization problem with current and stability limitations as constraints. Measurements across the grid, transmitted through low-bandwidth communications, are used to simplify the calculations, resulting in a recursive algorithm. Weight vectors are included in the objective function to allow participation flexibility of each converter. Results show that the primary virtual admittance controller is able to mitigate over- and under-voltages in steady state and under transient conditions. Subsequently, the secondary controller is shown to further improve the voltage profiles across the grid. Experimental results obtained from a laboratory environment, comprising three DG units and a grid emulator, validate the functionality of the complete control structure.

Reliability Comparison of Rural & Urban LVDS Networks with Corresponding HVDS Networks Including Substation Reliability

This paper mainly determines the comparison of reliability of an existing rural area & urban area LVDS (low voltage distribution system) with their respective proposed high voltage distribution system (HVDS) and also including their 33/11 kV Substation. Ring main substation and single bus bar substation configuration are considered for urban and rural distribution systems respectively. The reliability of ring bus substation used in urban area is more as compared to single bus substation used in rural area. The load point reliability indices are calculated considering both substation reliability indices and radial feeder indices. The substation failure rate is calculated by considering overlapping outages approach and whereas the radial feeder indices are calculated by using cut set approach. Further, the LVDS Network is converted into the HVDS Network by replacing a high rating distribution transformer (DTR) supplying to a group of customers with Large in number with multiple small rating distribution transformers near to consumer terminals with less number of customers in each group. This conversion leads to Minimum length of LT Lines in HVDS Which results in improving voltage profile, reliability and efficiency. In this paper the disconnecting switches and alternative supply are also considered on both LVDS and HVDS Networks in the calculation of the reliability of to assess the reliability of the radial distribution system (FMEA)Failure mode effect analysis is used. This study uses a LVDS and HVDS system, and uses an alternative power source and disconnectors, to determine reliability indices of the rural area network and urban area network distribution system. In this paper the important distribution reliability indices to reduce system average interruption durations (SAIDI), Energy Not Supplied (ENS) and ASAI for LVDS and corresponding HVDS are calculated. The research idea is proposed on a Indian practical networks.

Enhancing power quality and loss optimization in distorted distribution networks utilizing capacitors and active power filters: A simultaneous approach

The importance of Power Quality (PQ) issues in modern power systems has been growing in the last years. Capacitors are employed for optimizing network losses and increasing the voltage profile. However, in harmonic polluted networks, the placement of capacitors at their economic optimal locations may not be feasible due to harmonic constraints. Under such conditions, harmonic filters can mitigate harmonic pollution and enable capacitors to be optimally placed. This paper presents a novel approach for simultaneously optimizing the allocation of Active Power Filters (APFs) and capacitors, to improve the harmonic condition, network losses, and voltage profile of distribution networks. The method models APFs as harmonic sources in the Harmonic Power Flow (HPF) procedure, while capacitors are modelled as their corresponding harmonic admittance. Furthermore, a modified Particle Swarm Optimization (PSO) algorithm is presented as the optimization tool. Three case studies were conducted on the IEEE 18-bus test system. In the first study, optimal capacitor placement was performed with no regard to harmonic constraints, reducing network losses by 326 kW. The harmonic limits were then considered and satisfied by optimal APF placement. The total cost resulted in $241,983. The second study considered harmonic limits in the procedure of optimal capacitor placement, improving voltage profiles and network losses, but exceeding some harmonic constraints, which were subsequently satisfied by APF placement. The solution yielded the total cost of $264,942. The third study introduced simultaneous allocation of capacitors and APFs, proving to be the most cost-effective strategy ($225,417 total cost), promising enhanced network performance and efficiency, and adding valuable insights for future power system optimization.

Strategic planning of distribution network integrated with EV charging stations using fuzzy pareto optimality for performance improvement and grid-side emission reduction benefits

The increasing penetration of electric vehicles (EVs) in distribution systems requires efficient charging load management techniques for delivering high-quality power to consumers. In this paper, we proposed a strategic planning approach for distribution systems integrated with EV charging stations, employing fuzzy Pareto optimality to enhance system performance and minimize carbon emissions. Our approach involves a fuzzy Pareto heuristic network reconfiguration to minimize real power loss and improve voltage profiles. Additionally, Time of Use (ToU) pricing-based EV charging load scheduling is developed to minimize the annual energy cost. These objectives aim to improve minimum node voltage, reduce power losses, and maintain branch current constraints. To simulate the impact of EV charging loads, we aggregate residential, commercial, and industrial loads, along with EV charging loads at charging stations based on customer choice time and ToU pricing methods. The proposed reconfiguration approach is tested on 33 and 69-bus distribution systems with integrated EV charging stations, distributed generations (DGs), and shunt capacitors (SCs). The simulation results demonstrate the advantages of the reconfiguration algorithm in enhancing the performance of the distribution network in the presence of EV loads. Furthermore, we compare ToU pricing-based EV charging time zones with customer comfort-based EV charging, showcasing the advantages of the former in reducing emissions through real power loss reduction. Overall, our strategic planning approach not only improves distribution system performance but also offers economic benefits while minimizing carbon dioxide emissions.

Optimal Probabilistic Allocation of Photovoltaic Distributed Generation: Proposing a Scenario-Based Stochastic Programming Model

The recent developments in the design, planning, and operation of distribution systems indicate the need for a modern integrated infrastructure in which participants are managed through the perceptions of a utility company in an economic network (e.g., energy loss reduction, restoration, etc.). The penetration of distributed generation units in power systems are growing due to their significant influence on the key attributes of power systems. As a result, the placement, type, and size of distributed generations have an essential role in reducing power loss and lowering costs. Power loss minimization, investment and cost reduction, and voltage profile improvement combine to form a conceivable goal function for distributed generation allocation in a constrained optimization problem, and they require a complex procedure to control them in the most appropriate way while satisfying network constraints. Such a complex decision-making procedure can be solved by adjusting the dynamic optimal power flow problem to the associated network. The purpose of the present work is to handle the distributed generation allocation problem for photovoltaic units, attempting to reduce energy and investment costs while accounting for generation unpredictability as well as load fluctuation. The problem is analyzed under various scenarios of solar radiation through a stochastic programming technique because of the intense uncertainty of solar energy resources. The formulation of photovoltaic distributed generation allocation is represented as a mixed-integer second-order conic programming problem. The IEEE 33-bus and real-world 136-bus distribution systems are tested. The findings illustrate the efficacy of the proposed mathematical model and the role of appropriate distributed generation allocation.

Performance analysis of SRFT based D-STATCOM for power quality improvement in distribution system under different loading conditions

Abstract Presently the term “Power Quality” is gaining more and more attention due to different kinds of non-linearities induced by various converters used in the industries. Power quality is all about assessing and maintaining optimal quality of power during various stages of the power system ranging from generation to distribution. This research intends to provide a better understanding to various researchers about the applications of the Distribution Static Compensator (D-STATCOM) in mitigating various power quality concerns typically focused on harmonics elimination and voltage profile improvement. D-STATCOM is designed and installed in the distribution network to maintain reactive power demand, harmonic mitigation, and power factor correction. A Synchronous Reference Frame Theory (SRFT) based control technique is adopted to extract reference current. The behavior of the system with and without D-STATCOM is analyzed in detail for various loads. As a result, this study presents various ideas, adjustments, and compensating methods for several loading conditions. Finally, it is found that the current THD has been considerably improved under various loading conditions.

Optimal location for an EVPL and capacitors in grid for voltage profile and power loss: FHO-SNN approach

In the context of a rapidly expanding electric vehicle market, this research investigates the ideal locations for Electric vehicle (EV) charging stations (EVCS) and capacitors in power grids to enhance voltage stability and reduce power losses, facilitating sustainable and efficient grid operation. Meeting the increasing demand for EV charging stations while simultaneously addressing grid reliability, voltage control, and power loss issues poses significant challenges. A hybrid approach for EV parking lot and optimal location of capacitors in voltage and power loss is proposed in this manuscript. The proposed hybrid method combines the Fire Hawk Optimizer and Spiking Neural Network, hence called the FHO-SNN technique. The objective of the proposed method is used to lessen the active-power-losses that improve system performance. The novelty of this proposed method is electric vehicle parking lot and optimal location of capacitors in voltage and lessens the power loss. The proposed system is done in the MATLAB, and it is validates their performance with existing methods, such as Arithmetic Optimization Algorithm (AOA), Seagull Optimization (SO), and Atomic Orbital Search (AOS). The proposed method shows low convergence time, which is 4 sec, number of feeders, and best function node is found compared with other existing methods. The optimization approach can enhance the stability and efficiency of electric grids by improving voltage profiles and reducing power losses. The implications of this research highlight the potential for optimizing the combination of electric vehicles and capacitors into the grid, resulting in a more sustainable, efficient, and resilient energy and transportation system.

Improvement of Voltage Profile in Photo Voltaic System using Dynamic Voltage Regulator

This examination centers around further developing the voltage profile in a crossover power framework with a PV association using a unique voltage restorer. The objective of this work is to raise the framework's power quality. Regardless of whether voltage hang and swell happen on both the transmission and appropriation sides, the issue is just fixed there. A calculated procedure is utilized, expecting the components expected to foster the framework. A powerful voltage restorer that is associated in series perceives voltage glimmering immediately and reestablishes high voltage to its unique levels. This model's plan effectively settle the voltage glimmering issue also. MATLAB Simulink is utilized to reenact the outcomes, which explained the framework's importance.

Optimal Power Quality Enhancement using a Radial Distribution System with an Improved Unified Power Quality Conditioner

Massive electric power distribution over long distances with consequential Power Quality (PQ) challenges such as voltage sags and power losses are some of the significant attributes of a Radial Distribution Network (RDN). Deployment of Power Angle Regulated (PAR) based Unified Power Quality Conditioner (UPQC) in a distribution network is also securing attraction because of the latest recorded achievements and improvements in Voltage Source Inverter (VSI) built power electronic systems. However, optimal allocation of this kind of device to mitigate PQ problems remains a challenge for achieving set objectives. Consequently, this study considers the best possible allocation of PAR and Improved-UPQC know as I-UPQC in the distribution network to enhance power network performance. The identification of optimal location is achieved through the application of hybridization of the Genetic Algorithm and Improved Particle Swarm Optimization (GA & IPSO). The deterministic approach is based on the weight factor of various objective functions. The allocation is attained with a selection of reactive power control between inverter connected in parallel and series and control angle variables of the device through its dynamic involvement of total system loss derivatives. Performances of the I-UPQC based distribution system during diverse power transfers are observed. Convergence characteristic of deterministic approach at different disturbance percentages is analyzed and presented. Imaginary power circulation enhanced the voltage-associated challenges at the range of 0.949 to 0.9977. Hence, power dissipation minimized to 1.15 percent compared to the initial 3.35 percent, according to results of I-UPQC allocation in RDN utilizing mathematical and optimization technique. Additionally, the network losses, voltage dip, and minimum bus voltage profile all fall within the regulatory standards of less than 2%, 5%, and 5%, correspondingly. Also, the performance of the compensated network for both ordinary and optimized scenarios indicated the fitness of the projected method in accomplishing an operational optimization of RDN, specifically for voltage profile (VP) improvement and I-UPQC's series and shunt inverter share imaginary power.

Integration of distributed generations and static var compensators with static synchronous compensators to reduce power losses

The necessity of power is growing in response to today's growing population. In order to reduce both real and reactive power losses, three devices have been combined in this research. The distributed generations (DGs) and static var compensator (SVC) with static synchronous compensator (STATCOM) play important role for reduction of power losses (both real and reactive power) and improvement of voltage profile. The research outcome presented here outlines that presents genetic algorithm (GA) may be utilised to improve power system performance and voltage profile (VP) of distribution networks by integrating DG, SVC and STATCOM planning properly. On a 37-bus distribution network, the proposed methodology has been applied. The results of this study are helpful to those focusing on the functionality of viable and upcoming electrical grids, as well as those working in the disciplines of DG, SVC and STATCOM integration for improved system performance.

Distributed reactive power management in multi‐agent energy systems considering voltage profile improvement

AbstractIn recent years, distributed structures have been developed in distribution networks as a result of privatization as well as integration of independently operated distributed energy resources (DERs) into the grid. In this context, effective management techniques seem to be necessary to enable decentralized operation of systems that have been consisted of multiple agents. Accordingly, novel management schemes should be applied in such systems to enable the distributed reactive power management, which would finally improve voltage profile in the network. As a result, this paper develops a distributed algorithm for reactive power management in multi‐agent distribution systems with the aim of improving the voltage profile of the grid. Correspondingly, in the proposed framework, several cost functions are developed to model the effects of reactive power management on the system from the distribution system operator (DSO) as well as agents’ perspectives. Consequently, the proposed reactive power management algorithm would result in voltage profile improvement, while each agent of the system merely strives to maximize its own profits. Accordingly, the proposed scheme ensures the privacy of independent agents. Finally, the proposed scheme is applied on the modified IEEE‐37‐bus test system to investigate its effectiveness on Peer‐to‐Peer (P2P) reactive power management in multi‐agent systems.

YSA ve Bukalemun Optimizasyon Algoritmalarına Dayalı DER'lerde Tekno Ekonomik için Pratik Radyal Dağıtım Besleyicisi

Distributed energy resources (DERs) are a better choice to meet load demand close to load centers. Optimal DER placement and DER ratings lead to power loss reduction, voltage profile improvement, environmental friendliness, dependability, and postponement of system changes. This study uses artificial neural networks and the Chameleon Optimization Algorithm to analyze the best integration of renewable energy sources and electric vehicles in distribution feeders to reduce power loss, regulate voltage levels, and decrease the cost and emissions under unpredictable load demand. In this study, the generated output power of the models is compared to solar photovoltaic generation systems and wind turbine generation systems. As a result, a fitness function with several objectives has been developed to reduce total active power loss while also reducing total cost and emissions generation. The study took into account the influence of EV charging/discharging behavior on the distribution system. The 28-bus rural distribution network in feeders is used to test the suggested methodology. Final analysis of the numerical results showed that the Artificial Neural Network and Chameleon Optimization Algorithms outperformed in terms of power loss (440.94 kw) and average purchase of real power (2224 kw), but these parameters do not favor the other optimization algorithms. This showed that the proposed strategy is both viable and effective.