Optimal Reactive Power Compensation Research Articles

Using Advanced Metering Infrastructure Data from MV/LV Substations to Minimize Reactive Energy Supply Cost to Final Consumers

This article presents an original methodology to determine the optimal level of reactive energy transmission to low-voltage consumers supplied from MV/LV substations that guarantees the lowest total costs of reactive energy transmission through the DSO network and its generation in receiving installations within the reactive power compensation process. The average value of the optimal factor tgφ to be maintained by customers depends on the efficiency of the network, the characteristics of the load, and the market costs of energy losses due to the transmission of reactive energy through the network that are covered by the DSO and the costs of reactive energy generation in receiving installations. The results presented for real MV/LV substations operating in the Polish distribution network demonstrate the application of annual measurements of active and reactive energy consumed and generated registered by AMI systems to calculate the optimal reactive power compensation level. They can be applied to verify the permissible levels of reactive energy compensation applied by the DSOs until now within the yearly tariffs for customers.

Northern goshawk optimization for optimal reactive power compensation in photovoltaic low-voltage radial distribution networks

In recent years, photovoltaic systems (PVs) have been increasingly integrated into radial distribution networks (RDNs). However, network operators experience significant issues because they are sporadic. To reduce the load on the main grid and improve the network performance, capacitor banks (CBs) are frequently employed for power factor correction and VAr compensation. However, a large number of CBs must be switched at once in accordance with variations in load and PV generation to maintain feeder voltage regulation and improve its performance. This study's optimization strategy for CB control considers a variety of goals. Using seasonal load profiles and PV generation patterns, a novel and efficient northern goshawk optimization (NGO) was created to determine the appropriate control of CBs. By resolving the typical CBs allocation problem in EDNs and comparing the findings with those in the literature, the effectiveness of NGO was initially cross-verified. In the second stage, an NGO is used to maximize annual net savings while maintaining the best possible control over CBs. Considering the PVs and CBs of the network, a modified IEEE 33-bus test system was used to evaluate the effectiveness of the suggested methodology.

Currents’-Physical-Component-Based Reactive Power Compensation Optimization in Three-Phase, Four-Wire Systems

In this paper, we aim to address the limited capacity of compensation devices by enhancing their utilization rate by applying the currents’ physical component (CPC) theory for reactive power optimization in three-phase four-wire systems. When reactive currents cannot be fully compensated for, we propose using CPC theory to generate reference currents for the compensation devices. Weight coefficients associated with different reactive current components are introduced, enabling flexible combinations of these independent current components. The maximum output amplitude of the three-phase current from the compensation device serves as a constraint condition, allowing for the calculation of reference currents under various compensation targets. Additionally, a reactive current optimization compensation scheme focusing on loss reduction is selected. The simulated annealing–particle swarm optimization (SA-PSO) hybrid algorithm is employed to solve the optimization mathematical model. The discussed calculations, current waveforms, and voltage waveforms are generated using the constructed mathematical model and then used for a theoretical explanation. The simulation verifies the feasibility of the proposed method.

Multi Objective Optimization Framework to Provide Reactive Power Support to the Local Distribution Grid Using a Heuristic Approach.

Reactive power support to the local distribution grid becomes mandatory as it highly impacts the network's voltage profile and active power loss. Reactive power support improves the performance and efficiency of the grid. However, higher compensation to the line increases losses, deteriorates the voltage profile, and occupies the investment cost. The location of these reactive power compensators (RPC) also influences the network's performance. This paper presents a multi-objective strategy for optimal reactive power compensation to get techno-economic benefits. An objective function, which includes technical and economic criteria, has been formulated. The proposed MOF includes weighted distributed objectives that are minimized to get a trade-off solution. The proposed MOF has been minimized using three different heuristic algorithms, i.e. TLBO, GA and PSO. The proposed strategy has been tested on 56 buses 11 KV Gurukul distribution network located at Bhavnagar, Gujarat, India. NR load flow has been utilized to investigate losses and bus voltages.

Dynamic Reactive Power Allocation Method of Power Grid with High-Permeability PV Considering Transient Voltage Stability

Dynamic Reactive Power Allocation Method of Power Grid with High-Permeability PV Considering Transient Voltage Stability

Data Mining Approach to Select Parameters of Swarm Intelligence Algorithms for Optimal Placement Reactive Power Compensation

This study considers the problem of the parameter’s selection of the Particle swarm optimization algorithm. To find effective values of the algorithm parameters, the regression analysis, and rule-based classification have been applied. The regression analysis has allowed creating the model of dependency between values of the algorithm parameters and efficiency of solutions achieved. The classifier has approved allocating areas of the most effective values of the parameters. The areas obtained were used as the areas of possible values when searching extremum of regression curves per each of parameters. The effectiveness of parameters obtained has been compared with the parameters recommended by other researchers. It was found out that using the regression analysis and rule-based classifier allowed to select values of Particle swarm optimization algorithm parameters successfully. An example of using the method to solve the problem of optimal placement of reactive power compensation units in the electrical network is given.

Optimal Scheduling Strategy of Microgrid Based on Reactive Power Compensation of Electric Vehicles

This paper proposes a microgrid optimal scheduling strategy based on the reactive power compensation of electric vehicles to address the issue of interactive fluctuation of voltage and power resulting from a high proportion of new energy integration into the grid. Firstly, for accurate prediction of electric vehicle charging and discharging behavior, the Monte Carlo simulation method was employed for day-ahead prediction. Secondly, an optimization method for reactive power compensation was developed, considering distributed sources such as wind turbines, photovoltaics, and electric vehicles, with the objective of minimizing network loss and power generation costs. Additionally, user-side prices and electric vehicle charging prices were taken into consideration. Finally, utilizing the IEEE14 bus simulation, a comparison was made between the microgrid with and without electric vehicle reactive support capacity. Results demonstrated that, while maintaining a power factor greater than 0.95, the proposed method reduced the average daily generation cost by 0.35%, average daily network loss by 7.0%, average daily bus voltage fluctuation by 48.60%, average electricity price by 2.88%, and EV user charging cost by 21.29%. These findings illustrate that the proposed reactive power compensation optimization method effectively mitigates voltage and power fluctuations resulting from new energy integration, ensuring system safety, reliability, and economic efficiency.

Dynamic Reactive Power Compensation Optimization Strategy for Distribution Networks with Distributed Generators and Energy Storage Systems

To balance the output and load dynamic changes of distributed power generators (DG) and energy storage systems (ESS), a demand-side response-based dynamic reactive power optimization (RPO) strategy for distribution networks (DN) is proposed. This strategy adopts a phased optimization method to coordinate and optimize different types of reactive variables within the same period. By adjusting the states of parallel capacitor banks (SCBs) on load voltage transformers (OLTC), DGs, and ESS inverters, the RPO of the DN is carried out. Based on the characteristics of the model, an improved particle swarm optimization algorithm (IPSO) is used to solve different types of variables, and an IPSO based on tent chaotic mapping and levy flight strategy is proposed to improve the efficiency of collaborative solving. The simulation results show that the proposed strategy, considering the change of new energy output and demand side response, can reduce the solution scale while obtaining high satisfaction RPO results.

Critical Issues of Optimal Reactive Power Compensation Based on an HVAC Transmission System for an Offshore Wind Farm

The reactive power (RP) control of the high voltage alternating current transmission system (HVAC TS) for offshore wind farms (OWFs) is a crucial task to assure the consistent and efficient operation of the system. The importance of RP compensation (RPC) in power system operation is to maintain voltage stability and reduce power losses. Offshore wind farms present unique challenges for power system operation due to their distance from the onshore grid, variable wind conditions, and complex electrical infrastructure. The HVAC TS is common for OWFs as it is well-suited for transmitting large amounts of power over long distances. In this paper, a literature-based analysis helps in improving the operation and reliability of OWFs, ultimately leading to greater renewable energy utilization. This paper concludes that optimal RPC is a critical task for ensuring the stable and efficient operation of HVAC TSs for OWFs. Advanced control and optimization techniques can help achieve an optimal RPC, thereby minimizing TLS and improving the overall system efficiency. Furthermore, the study investigates the possible benefits of incorporating novel technologies and approaches, such as RESs, into the power compensation process. By offering insightful information on how to optimize HVAC TSs for OWFs, for example, subsea power cables with multiple layers must be used to carry electricity from large offshore wind farms, the development of more sustainable and effective energy solutions is possible. The research concludes by stating that ensuring the steady and effective operation of HVAC TSs for OWFs is a crucial responsibility. Advanced optimization and control solutions can reduce TLS and increase system efficiency by assisting in achieving the optimal RPC.

Reactive Power compensation Optimization of Distribution Network with Distributed Power Supply

In recent years, distributed generation has been fully developed, and its permeability is rising, which also brings great challenges to the reactive power regulation of the power distribution network. By analyzing the output characteristics of active power and reactive power of distributed power supply, in this article, a multi-objective optimization mathematical model of reactive power compensation is established, which takes the economy and security of the power distribution network into consideration. The results indicate that the reactive power compensation optimization model and the solution algorithm in this paper have good effectiveness and superiority. This thesis will provide the theoretical foundation and technology support for the design and realization of the DG reactive power compensation scheme.

Optimal dynamic reactive power compensation in power systems: Case study of Ecuador-Perú interconnection

Dynamic reactive compensation using Flexible AC Transmission Systems (FACTS) in power systems allows for regulation of the voltage within limits defined by the grid operator. Optimization algorithms that solve the optimal power flow (OPF) problem can be used to determine the operating range of a FACTS device. In this paper, we compare, in terms of total solve time, the solutions of two optimization algorithms for dynamic reactive power compensation, using the Branch Flow Model (BFM) and the Bus Injection Model (BIM) to represent the power flow equations. The algorithms to solve both problems have been compared using four cases: the adapted IEEE 14-Bus System, New England IEEE 39-Bus System, IEEE 118-Bus Test System, and the authors' proposed 20-Bus SNI-500 kV Ecuadorian System. The results allow us to identify that the convergence of BFM is achieved in less solve-time concerning BIM. Furthermore, both algorithms were applied to the case study of the future Ecuador-Perú 500 kV Interconnection, obtaining that the operating range of the SVC to be installed on the Peruvian side should supply between 58 MVAr and 209 MVAr.

Efficient Integration of Fixed-Step Capacitor Banks and D-STATCOMs in Radial and Meshed Distribution Networks Considering Daily Operation Curves

The problem regarding the optimal integration of efficient reactive power compensation in radial and meshed distribution networks using fixed-step capacitor banks and distribution static compensators (D-STATCOMs) is addressed in this research paper by proposing a master–slave optimization methodology. Radial and meshed distribution topologies are considered for the grid structure while including variable active and reactive demand curves. An economic analysis is performed, considering the net present value of the optimization plan, as well as the costs of energy losses and the capacitor banks’ acquisition, installation, and operation. In the case of the D-STATCOMs, an annualized costs analysis is presented. In the master stage, the discrete version of the generalized normal distribution optimization (GNDO) algorithm selects the nodes and the sizes of the capacitor banks. In the slave stage, the successive approximations power flow approach is implemented. Numerical results in the IEEE 33-bus grid (with both radial and meshed topologies) and the IEEE 85-bus grid (with a radial configuration) demonstrated the proposed master–slave optimization’s effectiveness in minimizing the project’s expected net present value for a planning period of five years. Moreover, a simulation in the IEEE 69-bus grid under peak operation conditions showed that the GNDO approach is an excellent optimization technique to solve the studied problem when compared to combinatorial and exact optimization methods. In addition, numerical validations considering D-STATCOMs in the IEEE 85-bus grid confirmed the effectiveness and robustness of the GNDO approach in addressing problems associated with optimal reactive power compensation in medium-voltage distribution systems.

Achieving Optimal Reactive Power Compensation in Distribution Grids by Using Industrial Compensation Systems

This paper presents a method for integrating industrial consumers owning compensation systems as alternative reactive power sources into grid operating processes. In remuneration, they receive a market-based provision of reactive power. The aim is to analyze the potential of reactive power compensation systems of industrial companies connected to medium-voltage (10 kV–30 kV) AC grids in order to increase the reactive power ability of distribution grids. Measurement methods and reactive power potential results of six industrial companies are presented to characterize the amount and temporal availability of their reactive power potential. The presented approach for using the decentralized reactive power potential is a centralized reactive power control method and is based on optimal power flow (OPF) calculations. An optimization algorithm based on linear programming is used to coordinate a reactive power retrieval tuned to the actual demand. The influencing quantities are the current grid status (voltage and load flow capacity reserves at grid nodes and power lines) and the current reactive power potential of the reactive power sources. The compensation impact of six measured industrial companies on an exemplary medium-voltage grid is shown by an application example.

Optimal Reactive Power Compensation via D-STATCOMs in Electrical Distribution Systems by Applying the Generalized Normal Distribution Optimizer

This research deals with the problem regarding the optimal siting and sizing of distribution static compensators (D-STATCOMs) via the application of a master–slave optimization technique. The master stage determines the nodes where the D-STATCOMs must be located and their nominal rates by applying the generalized normal distribution optimizer (GNDO) with a discrete–continuous codification. In the slave stage, the successive approximations power flow method is implemented in order to establish the technical feasibility of the solution provided by the master stage, i.e., voltage regulation and device capabilities, among other features. The main goal of the proposed master–slave optimizer is to minimize the expected annual operating costs of the distribution grid, which includes the energy loss and investment costs of the D-STATCOMs. With the purpose of improving the effectiveness of reactive power compensation during the daily operation of the distribution grid, an optimal reactive power flow (ORPF) approach is used that considers the nodes where D-STATCOMs are located as inputs in order to obtain their daily expected dynamical behavior with regard to reactive power injection to obtain additional net profits. The GNDO approach and the power flow method are implemented in the MATLAB programming environment, and the ORPF approach is implemented in the GAMS software using a test feeder comprising 33 nodes with both radial and meshed configurations. A complete comparative analysis with the Salp Swarm Algorithm is presented in order to demonstrate the effectiveness of the proposed two-stage optimization approach in the fixed operation scenario regarding the final objective function values. In addition, different tests considering the possibility of hourly power injection using D-STATCOMs through the ORPF solution demonstrate that additional gains can be obtained in the expected annual operative costs of the grid.

Optimal Phase-Balancing in Three-Phase Distribution Networks Considering Shunt Reactive Power Compensation with Fixed-Step Capacitor Banks

The black hole optimization (BHO) method is applied in this research to solve the problem of the optimal reactive power compensation with fixed-step capacitor banks in three-phase networks considering the phase-balancing problem simultaneously. A master–slave optimization approach based on the BHO in the master stage considers a discrete codification and the successive approximation power flow method in the slave stage. Two different evaluations are proposed to measure the impact of the shunt reactive power compensation and the phase-balancing strategies. These evaluations include a cascade solution methodology (CSM) approach and a simultaneous solution methodology (SSM). The CSM approach solves the phase-balancing problem in the first stage. This solution is implemented in the distribution network to determine the fixed-step capacitor banks installed in the second stage. In the SSM, both problems are solved using a unique codification vector. Numerical results in the IEEE 8- and IEEE 27-bus systems demonstrate the effectiveness of the proposed solution methodology, where the SSM presents the better numerical results in both test feeders with reductions of about 32.27% and 33.52%, respectively, when compared with the CSM. To validate all the numerical achievements in the MATLAB programming environment, the DIgSILENT software was used for making cross-validations. Note that the selection of the DIgISLENT software is based on its wide recognition in the scientific literature and industry for making quasi-experimental validations as a previous stage to the physical implementation of any grid intervention in power and distribution networks.

Optimal Reactive Power Compensation in Distribution Networks with Radial and Meshed Structures Using D-STATCOMs: A Mixed-Integer Convex Approach.

This paper deals with the problem regarding the optimal siting and sizing of distribution static compensators (D-STATCOMs) in electrical distribution networks to minimize the expected total annual operating costs. These costs are associated with the investments made in D-STATCOMs and expected energy losses costs. To represent the electrical behavior of the distribution networks, a power flow formulation is used which includes voltages, currents, and power as variables via incidence matrix representation. This formulation generates a mixed-integer nonlinear programming (MINLP) model that accurately represents the studied problem. However, in light of the complexities involved in solving this MINLP model efficiently, this research proposes a mixed-integer convex reformulation. Numerical results regarding the final annual operating costs of the network demonstrate that the proposed mixed-integer convex model is efficient for selecting and locating D-STATCOMs in distribution networks, with the main advantage that it is applicable to radial and meshed distribution grid configurations. A comparative analysis with respect to metaheuristic optimizers and convex approximations confirms the robustness of the proposed formulation. All numerical validations were conducted in the MATLAB programming environment with our own scripts (in the case of metaheuristics) and the CVX convex disciplined tool via the Gurobi solver. In addition, the exact MINLP model is solved using the GAMS software.

Research and Application of Combined Reactive Power Compensation Device Based on SVG+SC in Wind Power Gathering Area

With the increasing proportion of wind power access year by year, it brings many challenges to the voltage stability of power systems. In order to maintain the stability of the voltage in the power grid, it is impossible to take into account the regulation ability and economy when a single reactive power compensation device is installed. In this paper, a combined reactive power compensation device was installed, which is composed of a static var generator (SVG) and a parallel capacitor bank. The SVG has the characteristics of fast and smooth adjustment, and the application of the capacitor bank reduces the overall investment cost and has a great economy. The modal analysis method was used to find the optimal installation position for the reactive power compensation device. The improved particle swarm algorithm was used to optimize the capacity of the optimal reactive power compensation device to ensure the best performance of the compensation device. Finally, by formulating the control strategy of the combined reactive power compensation system, the reliable switching of the compensation device is controlled. The PSCAD simulation software was used to model the power grid in the Hami area, and six different configuration programs were set for static voltage stability simulation verification and three different configurations. The program was simulated and verified for transient voltage stability, and comparative analysis showed that the proposed method was correct, which strongly supports the voltage stability of the region and meets the demand of reactive power compensation of the power grid. This provides a good reference program for other wind power gathering areas.

Application of the SSA for Optimal Reactive Power Compensation in Radial and Meshed Distribution Using D-STATCOMs

This paper deals with the problem regarding the optimal placement and sizing of distribution static compensators (D-STATCOMs) in radial and meshed distribution networks. These grids consider industrial, residential, and commercial loads within a daily operation scenario. The optimal reactive power flow compensation problem is formulated through a mixed-integer nonlinear programming (MINLP) model. The objective function is associated with the minimization of the expected energy losses costs for a year of operation by considering the investment costs of D-STATCOMs. To solve the MINLP model, the application of a master–slave optimization approach is proposed, which combines the salp swarm algorithm (SSA) in the master stage and the matricial backward/forward power flow method in the slave stage. The master stage is entrusted with defining the optimal nodal location and sizes of the D-STATCOMs, while the slave stage deals with the power flow solution to determine the expected annual energy losses costs for each combination of nodes and sizes for the D-STATCOMs as provided by the SSA. To validate the effectiveness of the proposed master–slave optimizer, the IEEE 33-bus grid was selected as a test feeder. Numerical comparisons were made against the exact solution of the MINLP model with different solvers in the general algebraic modeling system (GAMS) software. All the simulations of the master–slave approach were implemented in the MATLAB programming environment (version 2021b). Numerical results showed that the SSA can provide multiple possible solutions for the studied problem, with small variations in the final objective function, which makes the proposed approach an efficient tool for decision-making in distribution companies.

A Critical Analysis of Modeling Aspects of D-STATCOMs for Optimal Reactive Power Compensation in Power Distribution Networks

Distribution static compensators (D-STATCOMs) can enhance the technical performance of the power distribution network by providing rapid and continuous reactive power support to the connected bus. Accurate modeling and efficient utilization of D-STATCOMs can maximize their utility. In this regard, this article offers a novel current-injection-based D-STATCOM model under the power control mode of operation for the reactive power compensation of the power distribution network. The versatility of the proposed D-STATCOM model is demonstrated by combining it with two of the most established distribution load flow techniques, viz., the forward–backward sweep load flow and the BIBC–BCBV-matrix-based direct load flow. Further, the allocation of the proposed D-STATCOM model is carried out under a multiobjective mathematical formulation consisting of various technical and economic indices such as the active power loss reduction index, voltage variation minimization index, voltage stability improvement index and annual expenditure index. A novel parameter-free metaheuristic algorithm, namely a student-psychology-based optimization algorithm, is proposed to determine the optimal assignment of the different number of D-STATCOM units under the multiobjective framework. The proposed allocation scheme is implemented on a standard 33-bus test system and on a practical 51-bus rural distribution feeder. The obtained results demonstrate that the proposed D-STATCOM model can be efficiently integrated into the distribution load flow algorithms. The student-psychology-based optimization algorithm is found to be robust and efficient in solving the optimal allocation of D-STATCOMs as it yields minimum power loss compared to other established approaches for 33-bus PDNs. Further, the economic analysis carried out in this work can guide network operators in deciding on the number of D-STATCOMs to be augmented depending on the investment costs and the resulting savings.

Reactive power compensation optimization of high voltage transmission network based on artificial bee colony algorithm

In order to reduce the network loss and operating cost of the transmission network, an optimization method for reactive power compensation of the high-voltage transmission network based on the artificial bee colony algorithm is proposed. The optimal model of reactive power compensation for transmission network is established by calculating the power flow to determine the state of power network. After the artificial bee colony algorithm is improved by the general learning strategy, the reactive power compensation optimization scheme is obtained by solving the model with the algorithm. In the simulation experiment, the global optimization speed of the improved artificial bee colony algorithm is improved, and the loss of the electric network is reduced by about 53.07% after the application of the compensation optimization method.