Distributed Generation Systems Research Articles

An Efficient Archerfish Hunting Optimizer (AHO)-Based Power Quality Improvement in Distribution System Connected UPQC

These days, because power quality (PQ) issues are costing industrial customers a lot of money, both electrical utilities and end-users are paying a lot of attention to them. The most significant and frequent PQ concerns for sensitive loads are voltage sag and swell. This manuscript proposes an optimization technique for enhancing the control system of a unified power quality conditioner (UPQC) connected solar photovoltaic system in the distributed generation system. The proposed strategy is the archerfish hunting optimizer (AHO). The objective of the AHO approach is to optimizing UPQC operation in distribution systems, focusing on targeted power quality enhancement. The optimal control pulses are produced by the series active power filter and the shunt active power filter, depending on the load-side and source circumstances. During the load variation states the AHO technique manages the power loss, total harmonic distortion (THD), and voltage instability issue respectively. The performance of the AHO methodology is carried out on the MATLAB platform and compared with existing methods, like particle swarm optimization (PSO), latent semantic analysis (LSA), and ant-lion optimizer (ALO). The existing methods THD are 6.35%, 7.85%, and 9.19%. The proposed method of THD is 4.22%. From the outcome, it concluded that the proposed method based on the THD is low contracted to present techniques.

Variable frequency interharmonic domain methodology for transient analysis and simulation of distributed generation systems

As the integration of renewable energy resources into the power grid increases, accurate modeling of variable frequency distributed generation systems becomes essential for ensuring grid stability, reliability, and optimal operation. Existing models often fail in effectively capturing the frequency dynamics of these systems, particularly when dealing with variable frequency sources. This gap hinders comprehensive analysis and the development of effective planning, control, and mitigation strategies.To address this challenge, this paper introduces a novel modeling methodology named here as the variable frequency interharmonic domain (VFID), which is based on the flexible extended harmonic domain (FEHD) approach. VFID dynamically adjusts the set of pre-selected frequencies within the state-space system to reflect changes in variable frequency sources. This method eliminates the need for post-processing routines, accurately representing both instantaneous values and frequency evolution of time-varying harmonics and interharmonics.Key results demonstrate that VFID offers significant improvements in simulation accuracy over conventional FEHD and PSCAD methods, making it a valuable tool for analyzing and simulating modern distributed generation systems. This advancement not only fills a critical research gap but also contributes to the development of more resilient and sustainable energy infrastructures.

Optimization of shared energy storage configuration for village-level photovoltaic systems considering vehicle charging management

Distributed renewable energy is more abundant in rural areas, and a large amount of distributed photovoltaic grid-connected power brings challenges to the stable of the power grid. How to promote the self-generation and self-consumption of distributed renewable energy has become an urgent problem. In this paper, a village-level distributed photovoltaic power generation system including energy storage and electric vehicles is constructed. With the goal of minimizing the photovoltaic grid-connected power and maximizing the annual comprehensive revenue, the planning model of energy storage capacity allocation for village-level distributed power generation system is constructed. Considering the charging management for different numbers of electric vehicles, the optimal energy storage capacity allocation strategy is solved using the improved particle swarm algorithm.Five scenarios are set up as examples to be analyzed.The conclusions are:(1)After the configuration of a reasonable energy storage,the grid-connected generation of the system is significantly reduced,and the annual comprehensive revenue of the system is significantly increased.(2)After considering charging management for different numbers of electric vehicles, the capacity and power of the energy storage configuration can be significantly reduced, thus reducing the energy storage investment cost and operation and maintenance cost, and further significantly improving the annual comprehensive revenue of this system.

English

English

Sliding Mode Observer-Based Phase-Locking Strategy for Current Source Inverter in Weak Grids

The current source inverter (CSI) has become the main grid-connected interface of distributed generation systems due to its advantages, such as boost capability, current controllability, and short-circuit protection capability. However, in weak grids, the grid-connected CSI that uses a phase-locked loop to achieve grid voltage synchronization has problems, such as instability in the fundamental positive-sequence voltage phase detection at the point of common coupling and instability in the current loop control, which seriously hamper the promotion and application of the CSI and its interconnected systems. For this reason, this paper proposes a sliding mode observer-based phase-locking strategy for the CSI. The strategy proposes a sliding mode observer for grid voltage phase detection, so that the grid current can directly follow the grid voltage, solving the problem of inconsistency or distortion between the voltage phase of the point of common coupling and the grid voltage phase in weak grids. On this basis, the grid impedance is regarded as part of the CL filter, and a robust parameter design method is proposed for the grid current closed-loop control in weak grids, which achieves robust operation of a CSI in weak grids. Finally, an experimental platform for a single-phase grid-connected CSI is built to verify the effectiveness and feasibility of the proposed scheme.

A novel method of steady-state modeling for self-excited induction generators in distributed generation system based on transient space-vector model

Abstract The paper proposes a novel mathematic model for steady states represented by the complex-domain transient space vectors of SEIGs in the stationary coordinate system, where the physical systems are extended to be analyzed by applying the previous approach of holistic analysis based on the stability theorem of Lyapunov. The motion analysis of mechanisms gives analytical formulas of operating points at steady states by solving the novel steady-state model analytically. Good agreement between former numerically computed results and analytically computed results by the analytic formulas proves the validity and effectiveness of the proposed novel model, with extensive engineering referenced and applicable value.

Improved Harmonic Mitigation and Power Injection Technique for Solar-fed DG System Using GA and PSO

This paper deals with Distributed Generation (DG) system requiring power quality features such as current harmonics, reactive power compensation, and power factor improvement in grid tied operation. The motivation is to combine DG system with the capabilities of shunt active filter to perform real power injection, current harmonics mitigation and power factor improvement. The control algorithm employed in this setup utilizes a reference current generator based on p-q theory together with a pulse width modulation controller for switching pulse generation. The control strategy utilizes PI controller with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for finding optimal PI controller parameters. The effectiveness of the proposed method is verified using MATLAB/Simulink and experimental model developed for 3kWp inverter. The PI-PSO controller injects 0.588kW active power into the grid results in sharing 54% of load power demand and the current harmonics is reduced from 23.70% to 1.63%. The obtained results demonstrate that the grid tied inverter maintains harmonic standards in accordance with the IEEE-519 standard while injecting maximum possible active power to the line.

Converter-based multi-frequency power transfer system for efficient energy packet transmission in the energy internet

The energy internet concept involves the transmission of energy in discrete packets, akin to the information internet's principle. The energy internet must adopt a decentralized configuration and enable bidirectional and simultaneous power transfer. This raises the problem of congestions during the energy packet dispatching process. To address potential congestion issues, we propose a three-phase multi-frequency power transfer system (MFPTS) where the positive-sequence fundamental frequency component is supplemented with the zero-sequence third and the negative-sequence fifth harmonic components. By using such signals with proper amplitudes, the harmonics are added to the voltage without changing the peak amplitude but increasing the rms value. To exert complete control over the different frequencies employed within the MFPTS, a decoupling method is necessary to separate these frequencies in the control system. This leads to creating three independent channels of power transfer by three frequencies without changing the existing infrastructure as these powers can be transferred within the same lines. This paper explores the feasibility of three-phase three-frequency power transfer by using three parallel power transfer channels, achieved through the utilization of three-phase grid-forming and grid-feeding converters. Using power converters provides the advantage of bidirectional power transfer and facilitates decentralization by serving as an interface between distributed power generation systems and the utility grid. These properties are essential for achieving optimal energy internet performance. The simulation and practical results prove that the proposed MFPTS could solve the energy packet dispatching congestion problem to have a reliable energy internet for the future.

Retraction Note: An ANN-based harmonic mitigation and power injection technique for solar-fed distributed generation system

Retraction Note: An ANN-based harmonic mitigation and power injection technique for solar-fed distributed generation system

Integration of Distributed Generations and electric vehicles in the distribution system

Power quality challenges are a major problem these days because of the significant increase in load demand and the existence of various reasons for disruptions in the distribution system. A voltage sag or a decrease in the magnitude of the line voltage can be brought on by rapid fluctuations in load or distribution system issues. Enhancing the grid current profile, reducing grid voltage sag, and improving other performances can all be achieved through the combination of electric vehicles with distribution generation systems. In this paper, the integration of Distributed Generation with Electric Vehicles in the distribution system has been done to enhance system performances such as true power loss index, imaginary power loss index, voltage deviation index, short circuit current index, cost function, and environmental impact reduction index for 16 bus distribution system in constant impedance, constant current, and constant power load models, or ZIP load models through proper location, sizing, coordinated controlling, and types of Distributed Generation and Electric Vehicle pairs for both charging and discharging modes by adopting Hybrid Genetic Algorithm - Monte Carlo Simulation optimization methodologies. This study's primary goal is to determine the optimal distribution generation and electric vehicle pairing to improve the aforementioned parameters, which will assist researchers in their future planning. Researchers, industry professionals, scientists, and individuals working with Distributed Generation and Electric vehicles in the smart grid will find this statement to be of great use.

Distributed generation powered by smart grids

Smart grids are conceived as a system to optimally manage the set of means that are part of the electricity grid to achieve adequate performance in the distributed generation system in the supply of quality electricity. The objective of this study was to analyze the importance of smart grids in distributed generation and how the elements that make it up allow the implementation of this technological innovation. The methodology was based on the mixed approach, of experimental design with descriptive scope and documentary support, the experimental method was applied for programming with the use of Homer Pro software. The results were obtained by simulation, carried out for a distributed generation system with a consumption of 197.78 kWh/day, obtaining important data such as the amount of kW of electricity generation supplied in a year, with a value of 98,114 kWh/year.

Decentralized Retrofit Model Predictive Control of Inverter-Interfaced Small-Scale Microgrids

In recent years, small-scale microgrids have become popular in the power system industry because they provide an efficient electrical power generation platform to guarantee autonomy and independence from the power grid, which is a critical feature in cases of catastrophic events or remote areas. On the other hand, due to the short distances among multiple distribution generation systems in small-scale microgrids, the interconnection couplings among them increase significantly, which jeopardizes the stability of the entire system. Therefore, this work proposes a novel method to design decentralized robust controllers based on a retrofit model predictive control scheme to tackle the issue of instability due to the short distances among generation systems. In this approach, the retrofit model predictive controller receives the measured feedback signal from the interconnection current and generates a control command signal to limit the interconnection current to prevent instability. To design a retrofit controller, only the model of a robust closed-loop system, as well as an interconnection line, is required. The model predictive control signal is added in parallel to the control signal from the existing robust voltage source inverter controller. Simulation results demonstrate the superior performance of the proposed technique as compared with the virtual impedance and retrofit linear quadratic regulator techniques (benchmarks) with respect to peak-load demand, plug-and-play capability, nonlinear load, and inverter efficiency.

Analysis of the Behavior of the Electromagnetic Frequency Regulator (EFR) Used in Hybrid Wind-Solar Photovoltaic Generation Systems

Within the context of integrating renewable energy sources, the Electromagnetic Frequency Regulator (EFR) presents a promising technology, particularly in hybrid distributed generation systems. This paper conducts a comprehensive analysis of pole pair configurations for both the EFR and the induction generator within such systems to enhance overall performance. An algorithm developed in Scilab is utilized for steady-state analyses considering various configurations. The methodology involves repetitive computations to evaluate the angular velocity of both the EFR and the generator, as well as the transformation ratios of the speed multiplier for different pole pairs. Scenarios with varying combinations of pole numbers are explored, demonstrating the impact on EFR velocity and the drive frequency of the EFR. Results showcase the efficacy of the proposed algorithm, providing insights into the selection of the most appropriate pole pairs to improve system performance.

The Optimal Selection of Renewable Energy Systems Based on MILP for Two Zones in Mexico

This paper presents a series of enhancements to a previously proposed mixed-integer linear programming (MILP) model for investment decisions and operational planning in distributed generation (DG) systems. The main contribution of this study consists of integrating a wind generation system and multiple loads at different buses in a network. The model considers dynamic weather data, energy prices, costs related to photovoltaic and wind systems, storage systems, operational and maintenance costs, and other pertinent factors, such as efficiencies, geographical locations, resource availability, and different load profiles. The simulation results obtained through implementation in Julia’s programming language illustrate that the MILP formulation maximizes the net present value, and four configurations for hybrid power generation systems in Mexico are analyzed. The objective is to enable profitability assessment for investments in large-capacity DG systems in two strategic zones of Mexico. The results show that the configurations in the NE zone, especially in Tamaulipas, are the most cost-effective. Case 1 stands out for its highest net present value and shortest payback time, while Case 2 offers the highest energy savings. In addition, Cases 3 and 4, which incorporate storage systems, exhibit the longest payback periods and the lowest savings, indicating less favorable economic performance compared with Cases 1 and 2. Moreover, the sales of two case studies, one without a storage system and the other with a storage system, are shown. The model also incorporates instruments for buying or selling energy in the wholesale electricity market, including variables that depict the injected energy into the electrical grid. This comprehensive approach provides a detailed overview of optimal energy management.

ANFIS-based power management and islanding detection utilizing permeation rate(γ) and relaxation parameter(ζ) for optimal operation of multiple grid-connected microgrids

Microgrid(s) integration into distribution networks and the growing use of Distributed Generation Systems necessitate the switch from traditional fossil fuel-based power generation methods to renewable resource-based ones. To achieve optimal power delivery, an adaptive method for solving power quality delivery problems posed by this transition is required. Unexpected islanding is an important power security concern that can lead to equipment damage, electrical risks, and decrease in power quality delivery. To address this problem, ANFIS-Based power management and islanding detection utilizing permeation rate(γ) and relaxation parameter(ζ) is proposed in this paper based on a rate of change of output voltage(ROCOV) of power sources at the point of common coupling in a 34-bus distribution network. Modeling of the distribution network, distributed generators, ANFIS training, and simulations was done using MATLAB/Simulink software. Results show that a 0.3 and 1.01 value indicates permeation rate of Microgrid(s) in a grid-tied mode whereas a 0 value indicates relaxation parameter of Microgrid(s) disconnected from the main distribution network. Islanding detection time of 0.02 sec was recorded when all Microgrids were disconnected during disturbances, and a 0.04 sec islanding detection time for disconnecting individual power sources at a time was recorded respectively. In general, islanding causes a system nominal voltage(400 V) deviation of 7 %. However, this was quickly restored without causing network voltage fluctuations due to the adaptive nature of ANFIS. Comprehensive simulations were used to validate the suggested method. The outcomes demonstrated that the proposed approach effectively distinguishes between islanding and non-islanding events and can quickly and accurately identify islanding as compared to other related works.

A novel hardware implementation approach to enhanced stable island operation of hybrid distributed generation using superconducting fault current limiters

In this research study, we have explored the transformative potential of integrating Superconducting Fault Current Limiters (SFCLs) and Superconducting Magnetic Energy Storage (SMEC) systems in hybrid distributed generation setups. Through a meticulous series of experiments, simulations, and detailed analyses, we have delved into the dynamic responses of these advanced technologies amidst various grid disturbances and fault scenarios. Our investigations encompassed a spectrum of grid disturbance scenarios, including voltage sags, frequency variations, and short circuits, revealing the crucial role that SFCLs and SMEC play in maintaining stable islanded operation. The numerical results showcased in this study demonstrate the pivotal role of SFCLs and SMEC in swiftly responding to grid disturbances, effectively limiting fault impacts and ensuring a continuous and uninterrupted power supply to critical loads. For instance, SFCLs reduced fault currents by up to 60 % within 15 ms during short circuit events at Node A, while voltage sags of 20 % were mitigated within 75 ms, showcasing a fault clearing time of 45 ms. Additionally, the SMES system's energy capacity of 10 kWh played a significant role in voltage and frequency stabilization, reducing fault impacts by over 50 % during various fault scenarios. Furthermore, our detailed analyses provide valuable insights into the SFCL performance, including activation times and fault current reduction capabilities. The transient responses of the system exemplify the remarkable ability of SFCLs to expedite fault recovery and stabilize microgrids. This study presents a novel hardware implementation approach aimed at enhancing the stable island operation of hybrid distributed generation systems through the integration of SFCLs and SMEC. The research addresses the pressing need for innovative solutions to ensure grid stability and reliability amidst the increasing penetration of renewable energy sources. Through hardware simulations, the effectiveness of SFCLs in limiting fault currents and improving system stability is demonstrated. Moreover, a quantitative comparison with existing solutions highlights the superiority of the integrated SFCL-SMES system in enhancing stable island operation, with fault tolerance improvements of up to 56 % compared to traditional methods. Overall, this research contributes to advancing the field of hybrid distributed generation and fault management, offering valuable insights into the practical implementation of SFCLs and SMES for grid resilience and reliable renewable energy integration.

A quasi-static time-series approach to assess the impact of high distributed energy resources penetration on transmission system expansion planning

Due to advancements in solar cell fabrication and inverter-based technology, as well as decreasing acquisition costs, solar distributed generation systems have emerged as a promising renewable source. Furthermore, electrification of the transportation system is an alternative promoted by many governments to mitigate the dependency on fossil fuels and achieve the goals of decarbonizing the economy. However, interconnecting a large quantity of distributed energy resources (DERs) to the power system reveals technical problems affecting the entire system. Planning coordinators and grid operators need to understand the full-spectrum impact of DERs on the power system to ensure secure and reliable grid planning and operations. The operation of a Hydro-Québec transmission system planned for 2030 is simulated in quasi-static time series mode with a massive integration of 1 million of electric vehicles and 1000 – 3000 MW of distributed photovoltaics. This paper provided findings on assessment of high DER penetrations impacts on the transmission system in terms of voltage control, mitigation means used, MVAR availability and consumption margin, generating unit optimal operation, and switching actions of several equipment.

Temporal Scenarios-based Assessment of Maximum Hosting Capacity of Renewable Generation in Distribution Systems Considering ANM Techniques

Abstract Incorporating large-scale renewable distributed generation (RDG) into the power grid introduces significant challenges associated with the indeterminacy of the power system, significantly impacting the comprehensive integration and efficient utilization of the distribution network. This underscores the imperative to investigate scientific evaluation methods and mechanisms for enhancing the RDG absorptive capacity within the distribution network. In light of the stochastic and temporal characteristics inherent to RDG, a novel approach for assessing the RDG hosting capacity within distribution networks is proposed, taking temporal scenarios into account. This method optimizes the RDG output probability distribution model based on its temporal fluctuation change rule, and constructs RDG temporal scenario model by using scenario reduction technology. Subsequently, a temporal scenarios-based RDG hosting capacity assessment model is established, taking into account active network management (ANM) techniques. The effectiveness of the proposed methodology is substantiated through simulation results conducted on a modified IEEE 33-bus system.

Robust Assessment of Hosting Capacity of Renewable Generation in Distribution Systems Considering the Active Network Management

Abstract As the penetration rate of renewable distributed generation (RDG) increases, its random fluctuation characteristics have brought many problems to the safe operation of the active distribution network (ADN), such as voltage over-limit, reverse flow, and deterioration of power quality. Therefore, it has effectively affected the new energy hosting capacity of the ADN. Therefore, the effective assessment of the new energy hosting capacity of the ADN is a key part of the distribution network planning. In order to cope with the random fluctuation characteristics of new energy, this paper presents a two-stage robust assessment method of RDG hosting capacity of distribution networks by considering active network management (ANM) techniques such as network reconfiguration, reactive power compensation and on-load voltage regulation. Finally, the improved IEEE-33 distribution system is used to verify the results. The proposed method has been shown to be effective for evaluating the ADN’s RDG hosting capacity.

Research on a new method of islanding detection based on lifting wavelet and neural network

Abstract At present, the commonly used active and passive islanding detection methods have their own shortcomings, and the islanding detection effect is difficult to meet the requirements. Therefore, a new detection method based on wavelet signal processing and artificial intelligence to identify islanding is proposed in this paper. In this method, the feature quantities required for islanding detection are obtained by wavelet transform and signal processing, and then the feature quantities are identified by neural network to determine whether the islanding is generated in distributed generation system. Wavelet transformation has a strong ability of signal feature extraction, while the neural network has strong learning and identification abilities, the combination of the both is beneficial to improve the success rate of islanding detection. Simulation verification shows that the new islanding detection method proposed in this paper can detect islanding quickly and accurately, and the performance of islanding detection has been significantly improved.