Renewable Distributed Generation Research Articles

Combined DC-Link Fed Parallel-VSI-Based DSTATCOM for Power Quality Improvement of a Solar DG Integrated System

In present day power systems, Power Quality (PQ) issues are causing great concern owing to the increased use of power electronic controlled drives and fluctuating and other non-linear loads. This problem is further aggravated by a steady increase in the integration of renewable energy-based Distribution Generation (DG), employing power electronic converters to distribution systems. Custom power devices with suitable control strategies provide an effective solution to these power quality issues. In this work, a typical three-phase distribution system supplying non-linear load and with DG integration is considered. A shunt connected DSTATCOM at PCC of the system is employed to mitigate power quality concerns. Initially, a parallel-VSI based DSTATCOM configuration, employing individual DC-Link and working basically on the principle of current sharing, has been proposed. The analysis is carried out for variable load conditions for PQ enhancement making use of a more effective control theory viz. Instantaneous Real-Reactive Power (IRP) theory for the generation of suitable switching patterns to the individual VSIs of the parallel DSTATCOM. Further, an improvement over the above configuration viz. combined/common DC-Link-fed parallel DSTATCOM is proposed. This configuration has the advantages of minimized sensing elements, reliable operation and low-cost compensation. A similar analysis is carried out for PQ improvement, making use of the same IRP theory with some modifications (known as MIRP theory). The effectiveness of this configuration is established from the simulation results. In all the above cases, the analyses are carried out using MATLAB/Simulink platform and the simulation results are presented in detail. Thus, the proposed parallel VSIs-based DSTATCOM configurations employing suitable control strategies provide effective solutions for power quality issues under varying load conditions in conventional distribution systems.

A Review of Distributed Secondary Control Architectures in Islanded-Inverter-Based Microgrids

The increasing energy demand, the shortage of energy resources, and the environmental challenges faced by conventional power-generation systems are some of the ongoing challenges faced by modern power systems. Therefore, many efforts have been made by the scientific community to develop comprehensive solutions to overcome these issues. For instance, current technological advances have allowed the integration of distributed generators into the power systems, promoting the use of microgrids to overcome these issues. However, the use of renewable distributed generators have introduced new challenges to the traditional control system schemes. To overcome these challenges, a hierarchical control approach has been proposed for distributed renewable sources. In other words, the control scheme have been divided into three hierarchical levels, primary, secondary, and tertiary, to overcome the new challenges present in modern power systems. Due to extensiveness of this topic, this overview is focused on secondary control systems, mainly for AC isolated microgrids. To improve the power quality of modern systems, several secondary control schemes have been proposed to overcome the well-known problem of frequency and voltage deviation. Some of these schemes have also introduced adequate active/reactive power sharing techniques to optimize the utilization of resources. Additionally, other secondary control schemes have also focused on reducing the communication load, to lower the network cost and adding robustness against communication problems. This article presents an insight of the different control techniques used to overcome power quality and communication problems. A comprehensive overview of distributed secondary control techniques for islanded microgrids is presented. In addition, the implementation of these techniques is explained in an orderly and sequential manner.

Impact Analysis of Distributed Solar Photovoltaic Power Generation System Integration on Power Grid Voltage Stability Using Static Techniques

Recently, the rise in consumption of electrical energy and power transmission between various utilities has resulted in the emergence of anxieties about the power system's network voltage stability. Additionally, the necessity for power systems to perform in a secure condition has increased due to an increase in load demand globally. Therefore, the use of renewable energy-based distributed generation is growing quickly to help meet electrical demand and disrupt environmental issues caused by the use of fossil fuels. This type of generation can have a positive or negative influence on the stability of the power system. This paper analyzes the effects of distributed PV power integration on the power grid's voltage stability using static techniques. In order to improve efficacy and accuracy, give a complete and in-depth understanding of the problem of voltage stability, and identify the causes of instability, a combination of four different techniques is employed for analysis. Analysis methodologies include modal analysis, sensitivity analysis, PV curve, and QV curve. The analysis of voltage stability is carried out on an IEEE 14-bus system by using NEPLAN software. The simulation results showed that the integration of a renewable energy resource-based distributed solar PV power system into the test system led to a noticeable improvement in stability degree, a decrease in sensitivity of buses, a significant improvement in system MW loading, an enhancement in voltage profile, and a perceptible increase in reactive power margin

Comparative assessment of techno-economic and environmental benefits in optimal allocation of distributed generators in distribution networks

Integration of Distributed Generation (DG) into power systems, especially at the distribution end, is one of the verified approaches that has been utilized to reduce power loss, enhanced reliable electricity supply, and promote environmental sustainability by reducing Greenhouse Gas (GHG) emissions. In this study, an approach for solving an optimal DG allocation problem in distribution network with the objective function of maximizing the financial Techno-Economic and Environmental Benefits (TEEBs) of the grid is discussed. The TEEBs analysis of the DG planning problem is uniquely modeled as financial cost-benefit due to reduced power purchased and reduced Penalty Emission Cost (PEC) arising from the reduction of GHG emission in the network. A comprehensive and comparative analysis was carried out for the four classes of DG technology types to identify the environmental impact of integrating renewable and non-renewable DGs into the distribution system. Furthermore, The DG planning problem is solved using the Black Widow Optimizer (BWO) technique. The study implemented the proposed methodology on the standard IEEE 69-bus and Nigerian Shasa 59-bus distribution systems. The results show that renewable DGs’ optimal integration yielded higher TEEBs than non-renewable DGs despite the high capital cost of renewable DGs. Furthermore, the study affirmed the viability and efficiency of the proposed method by comparing the results of power loss obtained for the various DG types with that of techniques in open works of literature.

Optimal allocation of electric vehicle charging stations and renewable distributed generation with battery energy storage in radial distribution system considering time sequence characteristics of generation and load demand

The addition of electric vehicle (EV) charging station (EVCS)/EV battery swapping stations (EVBSSs) in radial distribution system (RDS) draws extra real power from the distribution substation. This paper proffers a novel strategy for obtaining the best location of EVCS/EVBSSs in the RDS. Further, the EV charger has been modeled as constant current load and the influence of EVCS/EVBSSs demand on the voltage profile, real power loss, total voltage deviation, energy loss cost and overall operating cost of the RDS have been investigated considering constant power (CP), industrial (IL), residential (RES) and commercial (COM) load models. In order to make the network more self-sustainable and reliable, it is obligatory to assimilate the distributed generations (DGs) of optimal size and at proper location in the RDS to diminish the impact of EVCS/EVBSS(s) load. In addition, non-dispatchable solar photovoltaic (SPV) and wind turbine (WT) units are converted into a dispactable SPV and WT units with a combination of battery energy storage (BES) (i.e., SPV-BES and WT-BES). This research work suggests a novel chaotic student psychology based optimization (SPBO) (CSPBO) algorithm to acquire the optimal size and site of SPV-BES, WT-BES and biomass in IEEE 33-bus and practical Brazil 136-bus RDS for CP, IL, RES and COM load models considering the average hourly load demand profile and the average hourly variation in generation profile of SPV and WT. The obtained results based on benchmark test problems reveals that chaotic maps are proficient to enhance the performance of the SPBO algorithm significantly in terms of local optima circumvention and faster convergence mobility. The obtained outcomes show that the attained size and site of renewable DGs in the RDS may be feasible ones. The attained outcomes of the proffered CSPBO algorithm are contrasted to SPBO and Harris hawk's optimization algorithm. The yielded results will definitely help the EV and distribution industry in improving the reliability and the efficiency of the system.

Markov-Based Reliability Assessment for Distribution Systems Considering Failure Rates

Switches (SWs) and renewable distributed generations (RDG) are subject to failure as well as other components of a system that are usually presumed fully reliable in the literature. It can lead to an overestimation of their contribution to reliability enhancement disregarding their dysfunction. This study considers the failure rate of SWs and RDGs to assess their impact on the reliability cost of the system and their effect on the optimal placement using a Markov-based approach. The optimal placement of SWs and RDGs in radial distribution systems is carried out simultaneously aim at minimizing the overall cost including investment, maintenance of SWs, and RDGs alongside the interruption cost. The performance of the model is verified through different scenarios and tested on RBTS bus 2. The results show that high values of the failure rates lead to fewer allocations to prevent plummeting the reliability of the system and increasing the capacity of the RDG results in fewer SWs allocation.

An Innovative Converterless Solar PV Control Strategy for a Grid Connected Hybrid PV/Wind/Fuel-Cell System Coupled With Battery Energy Storage

The proposed work addresses the modeling, control, energy management and operation of hybrid grid connected system with wind-PV-Battery Energy Storage System (BESS) integrated with Fuel Cell (FC) and Electrolyzer. A hybrid PV-Wind-FC with electrolyzer consisting of BESS with the least number of control loops and converters has been proposed. The proposed hybrid system presents a cost efficient solution for integrating PV into a hybrid system by eliminating the PV converter. This includes the design of controllers for grid-connected hybrid systems with a renewable distributed generator (Wind and PV) as a primary source, BESS as a secondary source and FC with Electrolyzer as a tertiary source. In addition, the lead compensator along with integrator is used for obtaining enough phase margin and removing steady state error completely. It increases the stability of the controller and adds phase shift φ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>s</i></sub> at a cross gain frequency (ω <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>cut</i></sub> ). The Grid Side Controller (GSC) is capable of providing frequency support to the utility grid, when it is linked to the grid. In the proposed configuration, PV power is maximized and injected into grid through GSC. Rotor Side Converter (RSC) and GSC ensure the support for sharing the burden of the grid station. Moreover, the proposed controller of BESS with coordination of FC eliminates the effect of intermittency of power generated from wind and PV. Excess power production by renewable distribution generation is used by Electrolyzer to generate hydrogen. This hydrogen is further used by FC when there is not enough power generation due to unfavorable weather conditions. The energy management has been presented to fulfill the load profile, avoid BESS overcharging and to minimize the intermittency and fluctuation of Wind and PV sources. This method guarantees steady power flow and service continuity. The Simulink model of the proposed system results validate the efficiency of the proposed hybrid system as compared to the conventional hybrid system reported in the literature. The modeling of the proposed system and analysis has been demonstrated using the MATLAB Simulink model. Lastly, the energy management of the system has also been examined and compared with the conventional power system.

Two-stage Optimal Dispatching of AC/DC Hybrid Active Distribution Systems Considering Network Flexibility

The increasing flexibility of active distribution systems (ADSs) coupled with the high penetration of renewable distributed generators (RDGs) leads to the increase of the complexity. It is of practical significance to achieve the largest amount of RDG penetration in ADSs and maintain the optimal operation. This study establishes an alternating current (AC)/direct current (DC) hybrid ADS model that considers the dynamic thermal rating, soft open point, and distribution network reconfiguration (DNR). Moreover, it transforms the optimal dispatching into a second-order cone programming problem. Considering the different control time scales of dispatchable resources, the following two-stage dispatching framework is proposed. ① The day-ahead dispatch uses hourly input data with the goal of minimizing the grid loss and RDG dropout. It obtains the optimal 24-hour schedule to determine the dispatching plans for DNR and the energy storage system. ② The intraday dispatch uses 15 min of input data for 1-hour rolling-plan dispatch but only executes the first 15 min of dispatching. To eliminate error between the actual operation and dispatching plan, the first 15 min is divided into three 5-min step-by-step executions. The goal of each step is to trace the tie-line power of the intraday rolling-plan dispatch to the greatest extent at the minimum cost. The measured data are used as feedback input for the rolling-plan dispatch after each step is executed. A case study shows that the comprehensive cooperative ADS model can release the line capacity, reduce losses, and improve the penetration rate of RDGs. Further, the two-stage dispatching frame-work can handle source-load fluctuations and enhance system stability.

A MIQP Approach Based on Demand Response in Distribution Networks to Improve the Multi-Objective Function in the Presence of Renewable Energy Resources and Batteries to the Subway Systems

The increasing expansion of devices such as electric vehicle charging stations, renewable energy resources, and electric subways, will cause an imbalance between load and production in the distribution network, which will lead to an increase in power losses, a decrease or increase in voltage and ultimately impose more costs on the independent system operator (ISO). In this paper, we have presented a mixed integer quadratic programming (MIQP) optimization model to improve the distribution network performance in the presence of these devices. The proposed model is a mixed integer model including demand side management modeling, energy storage system, battery to subway (B2S) system, optimal control of on-load tap changer (OLTC), step voltage regulator (SVR), fossil generation resources, renewable energy and capacitors, and shunt reactors. The considered multi-objective function is a scenario-based stochastic model, which accurately models the uncertainties in renewable energy resources. Paying attention to the nature of the proposed model will guarantee globally optimal solutions. The proposed model runs on the standard network of 33 buses, and the simulation results guarantee the optimal and accurate performance of the proposed model. The simulation results demonstrate that the outage of three distributed generation units from the network causes an average increase of 55% in energy losses, and the outage of three renewable units leads to an increase in emissions of about 40%. Another point received from the results illustrated that with the implementation of the proposed model under any load level of the network, as well as the outage of fossil and renewable distributed generation (DG) resources, no load shedding will occur in the network during the 24 hours. Finally, due to the short execution run time, the proposed model can be used for real and online grids.

Load flow investigations for regionalized islanded microgrid considering frequency regulation with high renewable penetration

• An algorithm for power flow analysis considering high renewable penetration. • Regionalization of distribution system into conventional & renewable dominant regions. • Load flow investigations for both type of regions. • Minimization of power losses and less computational burden are major benefits. To harmonize the operation of renewable and conventional generation, an approach of regionalized microgrid is proposed. Regionalization has been adopted for islanded microgrid in which the distribution system has been sectionalized into conventional generation-based regions (CGRs) operating with droop control and renewable generation-based regions (RGRs) operating with constant frequency de-coupled PQ control method. Back-to-back converters have been installed between the regions for bi-directional power exchange. In this paper, a novel load flow algorithm has been proposed for a regionalized microgrid in an islanded mode that aims to solve the power flow problem for both types of the regions. The algorithm considers the uncertainty of renewable distributed generators (RDGs) and loads. The approach focuses on the frequency regulation in both types of regions. Case studies have been carried out for IEEE 15, 33 and 69-bus distribution systems by converting them into regionalized microgrids (RMG). Results have demonstrated the strength of proposed load flow approach with a fast convergence speed. Graphical Abstract

An overview of AC and DC microgrid energy management systems

&lt;abstract&gt; &lt;p&gt;In 2022, the global electricity consumption was 4,027 billion kWh, steadily increasing over the previous fifty years. Microgrids are required to integrate distributed energy sources (DES) into the utility power grid. They support renewable and nonrenewable distributed generation technologies and provide alternating current (AC) and direct current (DC) power through separate power connections. This paper presents a unified energy management system (EMS) paradigm with protection and control mechanisms, reactive power compensation, and frequency regulation for AC/DC microgrids. Microgrids link local loads to geographically dispersed power sources, allowing them to operate with or without the utility grid. Between 2021 and 2028, the expansion of the world's leading manufacturers will be driven by their commitment to technological advancements, infrastructure improvements, and a stable and secure global power supply. This article discusses iterative, linear, mixed integer linear, stochastic, and predictive microgrid EMS programming techniques. Iterative algorithms minimize the footprints of standalone systems, whereas linear programming optimizes energy management in freestanding hybrid systems with photovoltaic (PV). Mixed-integers linear programming (MILP) is useful for energy management modeling. Management of microgrid energy employs stochastic and robust optimization. Control and predictive modeling (MPC) generates energy management plans for microgrids. Future microgrids may use several AC/DC voltage standards to reduce power conversion stages and improve efficiency. Research into EMS interaction may be intriguing.&lt;/p&gt; &lt;/abstract&gt;

Optimization Planning Method of Renewable distributed Generation in Radial Distribution Systems

Optimization Planning Method of Renewable distributed Generation in Radial Distribution Systems

Closed-Loop Interconnected Model of Multi-Inverter-Paralleled System and its Application to Impact Assessment of Interactions on Damping Characteristics

The influence of parameters on the damping characteristics in a multi-inverter-paralleled system is different from that in a single-inverter system, because of inverter interactions in a nonideal grid. To quantify the interaction degree and assess its impact on damping characteristics, this paper proposes a closed-loop interconnected model for multi-inverter-paralleled systems. The model can explain the impact mechanism of inverter interactions on system stability. Capacity expansion of inverter-based renewable distributed generation is taken as the background in this paper, and then, the proposed model is applied to assessing the influence of the collecting line length of the newly installed inverters on the overall system stability. The conclusion is that the damping of a multi-paralleled-inverter system in the medium frequency range degrades with the approaching of the lengths of the newly added line and the existing line. Therefore, to avoid damping degradation in capacity expansion scenarios, the length of the newly added line should be different from the length of existing lines or the parameters of new inverters should be readjusted. Simulation results are presented to verify the effectiveness of the proposed model and stability enhancement approaches.

Robust Coordinated Optimization With Adaptive Uncertainty Set for a Multi-Energy Microgrid

With the increasing integration of the multi-energy microgrid (MEM) with the distribution network (DN), the distributed coordination between MEM and DN becomes critical. This paper proposes a distributed scheduling method for the coupled MEM-DN under operational uncertainties. First, a worst-expectation min-max-max-min robust optimization model is formulated for MEM considering the uncertainties of renewable distributed generation (wind and photovoltaic) as well as its class probability. Second, the column and constraint generation algorithm with an alternating iteration strategy (C&CG-AIS) is proposed to accelerate the solution by decoupling the subproblems. Third, the multi-interval convex hull uncertainty set (MCHUS) is proposed to reduce the conservatism of robust optimization by decreasing the low-probability scenarios. Furthermore, the Bregman alternating direction method with multipliers (BADMM) is combined with the alternating optimization procedure (AOP) to overcome the convergence difficulty in the nonconvex distributed MEM-DN model. Finally, the effectiveness of the proposed model and method is verified by simulation tests based on IEEE-33 node DN and a park-level MEM.

Control-Centric Living Laboratory for Management of Distributed Energy Resources

Variability and uncertainty of renewable distributed generation increase power grid complexity, necessitating the development of advanced control strategies. demonstrates a real-world testbed and the implementation of control strategies on it to mitigate the challenges associated with variability and uncertainty of renewable distributed generation. This control-centric testbed includes 4.6 MW of controllable building loads, a 1 MW solar array, and a 125 kW / 130 kWh battery energy storage system (BESS). The capabilities of the testbed are illustrated by highlighting the implementation of three specific scenarios relevant to future smart grid infrastructures. In the first scenario, photovoltaic output variability is mitigated with the BESS using adaptive moving average and adaptive state of charge control methods. The second and third scenarios demonstrate peak load management and load following control to manage uncertainty using the Intelligent Load Control (ILC) algorithm. The ILC modifies controllable loads using a prioritization matrix and an analytical hierarchy process. The three scenarios all operate at a different time-constant, and are each effectively addressed, demonstrating the versatility and flexibility of the presented testbed. This demonstrated ability to rapidly test the efficacy of alternate control algorithms on a real system is crucial to the maturation of future smart-grid.

Optimal renewable distributed generation planning: an up-to-date state-of-the-art review

Optimal renewable distributed generation planning: an up-to-date state-of-the-art review

Fast Solving Method for Two-Stage Multi-Period Robust Optimization of Active and Reactive Power Coordination in Active Distribution Networks

This paper considers constraints on the cycle number of energy storage systems (ESSs), travel distances of switchable capacitors reactors (SCRs), on load tap changers (OLTCs) and step voltage regulators (SVRs). The characteristics and operational constraints of these equipments are properly formulated with binaries and big-M method, obtaining desirable linear descriptions. The branch flow equations of distribution systems for active and reactive power coordination are constructed. Considering physical constraints, a multi-period mixed-integer deterministic second-order conic programming (SOCP) to minimize network losses is formulated. Then, considering uncertainties of loads and active power of renewable distributed generators (DGs), a two-stage robust model is developed. A directly iteratively solving method between the first and second stage models is proposed. In contrast to the traditional column-and-constraint generation (CCG) method, increases to variables and constraints are not needed to solve the first stage model. To solve the second stage multi-period model, only the model of each single period needs to be solved first. Then their objective function values are accumulated, and the worst scenarios of each period are concatenated. As a result, the solving complexity is greatly reduced. The capabilities of the proposed method are validated by three simulation cases. It is found that the computational rate using the proposed method is significantly enhanced with much less computer storage. Specifically, the simulation results of 4, 33 and 69-bus systems indicate that the computing rate of the proposed method is about 28 times higher than CCG method when 8 iterations are performed. Meanwhile, the precision of optimization results is also improved.

Potential of Renewable Energy Sources for Distributed Generations: An Overview

The universal energy predicament and the exhaustion of fossil fuel reserves necessitate the requirement for green and dependable source of energy. Renewable energies are produced from the natural processes that are replenished such as sunlight, wind, rain, tides, and geothermal heat. Furthermore, transmission of electricity which is tantamount to high cost and energy losses resulted to the integration technology of distributed generator (DG) during the past decade to supplements centralized generation. DGs are sustainable solution to provide electricity to customers at reliable and affordable price. This paper is an overview of renewable energy sources as used in distributed generation by presenting an updated data of the status of renewable energy resources. It also discusses impact of DG in distribution system, benefits of DG and its classification. Renewable DG technologies and factor hindering establishment of Distributed Generation were also highlighted.

A Comparative Study of Wind Energy Conversion System incorporating the Doubly Fed Induction Generator and the Permanent Magnet Synchronous Generator

The renewable energy power producer (RPP) sector is growing rapidly to become an important source of power in South Africa and in nations across the globe. Companies within this sector provide a variety of clean energy sources. Despite its ability to support the power system and conserve the environment that sustains life, the rising usage of renewable distributed generators (RDGs) poses power quality problems in the overall distribution network, such as the voltage instability at buses, the increase in voltage/current harmonic distortions, etc. Furthermore, RDGs are required to remain connected to the electrical power network during grid faults and provide system support by injecting reactive current when required, depending on the nature of the fault. This study provides a dynamic performance analysis of a doubly fed induction generator (DFIG) based wind energy conversion system (WECS), and permanent magnet synchronous generator (PMSG) based WECS. The potential fault ride-through capability solutions in grid code power generation and injection of reactive power are taken into account, and the application results of both systems are shown under similar working conditions. From the simulation results, it is found that the DFIG based WECS topology performed well compared to the PMSG based WECS topology.

Cutting-edge public policy proposal to maximize the long-term benefits of distributed energy resources

In the context of increasing integration and relevance of distributed energy resources, this paper proposes an advanced public policy to maximize their long-term benefits through optimal regulated electricity market management. More specifically, the focus is on renewable distributed generation and energy storage systems. The proposed policy arises from three models or techniques, i.e., the optimized tariff model (regulated electricity market model), Bass diffusion model (long-term forecasting of the integration of distributed energy resources), and random walk (risk assessment technique), along with a stochastic optimization problem. The policy leads to socioeconomic welfare maximization while ensuring fairness for all the market players and enhanced control by the regulatory agency on the integration of distributed energy resources. By applying the policy to a concession area located in northeastern Brazil, where photovoltaic distributed generation systems dominate the market share, results demonstrate that it is highly valuable as a 156 (MR$) mean socioeconomic welfare gain was achieved when optimizing the design variables (compared to a non-optimal solution).