Grid Connected Hybrid Power System Research Articles

A Techno-Economic Analysis of a Hybrid Microgrid System in a Residential Area of Bangladesh: Optimizing Renewable Energy

In the face of a significant power crisis, Bangladesh is turning towards renewable energy solutions, a move supported by the government’s initiatives. This article presents the findings of a study conducted in a residential area of Pabna, Bangladesh, using HOMER (Hybrid Optimization of Multiple Energy Resources) Pro software version 3.14.2. The study investigates the feasibility and efficiency of a grid-connected hybrid power system, combining photovoltaics (PV), a biomass generator, and wind energy. The simulation produced six competing solutions, each featuring a distinct combination of energy sources. Among the configurations analyzed, the grid-connected PV–biomass generator system emerged as the most cost-effective, exhibiting the lowest COE at USD 0.0232, a total net present cost (NPC) of USD 321,798.00, and an annual operating cost of USD 6060.59. The system presents a simple payback period of 9.25 years, highlighting its economic viability. Moreover, this hybrid model significantly reduces CO2 emissions to 78,721 kg/year, compared to the 257,093 kg/year emissions from a solely grid-connected system, highlighting its environmental benefits. Sensitivity analyses further reveal that the system’s performance is highly dependent on solar irradiance, indicating that slight variations in solar input can significantly impact the system’s output. This study underscores the potential of integrating multiple renewable energy sources to address the power crisis in Bangladesh, offering a sustainable and economically viable solution while also mitigating environmental impacts.

Enhancing PI controller performance in grid-connected hybrid power systems

The optimal operation of a microgrid was buildup of both uncontrollable (solar, wind) and controllable (batteries, diesel generators) electrical energy sources are enclosed in this paper. By replacing controllers, the variations in wavering power supply caused by load fluctuations are managed. The objective of the research paper is to optimize these controller gain settings for effective use of electrical energy. In this paper integral time square error principle is combined along with the Cuckoo search algorithm (CSA) and particle swarm algorithm (PSA) to obtain the accurate, precise and appropriate results. It enhances the microgrid's steady-state sensitive responsiveness in comparison to trial-and-error techniques, assuring a stable supply of electricity to the load.

Improving Power Quality in a Grid-Connected Hybrid Power System through the Implementation of a Fuzzy Logic Controller

The examination of modeling and designing grid-connected hybrid power systems with efficient control strategies is the focus of this study. Integration of wind and photovoltaic systems into the ac-bus bar system is a common practice in enhancing operational performance. Utilization of Matlab Simulink software is employed for the design of this hybrid system, incorporating efficient MPPT control algorithms to optimize power generation from solar and wind sources under varying climatic conditions. Analysis of the maximum power point tracking mechanism and control methods of the hybrid power system is conducted, particularly in response to changes in weather conditions such as wind speed and solar radiation. Maintaining grid voltages and Unity Power Factor (UPF) while feeding currents into the grid is essential for the hybrid system. The employment of Proportional Integral (PI) control instead of Fuzzy Logic Controller (FLC) in the voltage-oriented control approach is explored to enhance power quality.

The effect of electric vehicle charging demand variability on optimal hybrid power systems with second-life lithium-ion or fresh Na–S batteries considering power quality

Second-life batteries (SLB) in energy storage systems (ESS) can provide an economical solution to hybrid power systems (HPS) by reducing environmental concerns in battery production. Could Na–S batteries be a suitable alternative for ESS applications if the toxicity problem can be solved? This article performs the optimal sizing and feasibility analysis of an electric vehicle charging station with a minimum cost objective under daily, hourly, and hybrid demand variability with multi-year sensitivity analyses for both ESS technologies. Moreover, the scope is deepened with sensitivity analyses based on solar horizontal irradiation, wind speed, and electricity selling prices. Due to the HPS connection to the distribution busbar, power quality issues are included in the cost-based optimization framework, and the effects of power quality issues on the sizing and feasibility outputs are compared at higher demand variability. The results show that using SLB at wind speeds lower than 4.7 m/s and irradiances lower than 3 kWh/m2/day or above 0.035 $/kWh electric sale price is not economical. Grid-connected HPSs can increase current and voltage harmonics at the distribution busbar by up to 55.3 % and 4.3 %, reduce the power factor by up to 46.8 %, and extend the payback period by up to 1 year.

Economic and environmental analysis of a grid-connected hybrid power system for a University Campus

BackgroundThe generation of clean and affordable energy by 2030 is a challenging task, necessitating the integration of renewable energy sources to reduce greenhouse gas emissions associated with coal, crude oil, and natural gas. This study examines the optimization and performance analysis of a hybrid microgrid for a university campus as a potential solution to achieve this goal. The primary objective is to decrease the cost of energy and reduce CO2 emissions on the campus using a hybrid approach.ResultsThe Howard college campus of the University of KwaZulu Natal (UKZN) was used as a case study, with meteorological data obtained from NASA and real hourly electrical load data for 2019 from the university smart meters. HOMER, an optimization software, was employed to model and simulate the case study. The results demonstrated significant savings of R15.7 million (approximately $ 820 000) in annual utility bills, a 51% reduction in CO2 emissions, a return on investment of 20%, and a payback period of 4 years.ConclusionThe study's findings suggest that universities can become self-sustaining during load shedding periods, as recently experienced in South Africa. The implementation of a hybrid microgrid system on a university campus offers considerable economic and environmental benefits, providing a potential blueprint for other large institutions seeking to achieve similar sustainability goals.

Energy management of photovoltaic-battery system connected with the grid

Managing a sustainable hybrid system may be accomplished in a variety of ways, including sizing, obtaining maximum power, or balancing multiple energy sources. The rapid growth and attractiveness of renewable energy technology require the development of an Energy Management System (EMS) architecture that integrates a PV-battery system into the grid. In the present study, a grid-connected hybrid power system to manage energy production, grid interaction, and energy storage is installed and experimentally investigated. The PV-battery system is connected to the grid and employs an optimal EMS algorithm, which has been validated using both virtual simulation and lab experiments to ensure serving the demand load while minimizing grid consumption. Simulation results show that the grid consumption over an entire year is minimized to represent 59.5 % of the whole consumption. According to simulation and laboratory results, the proposed EMS algorithm saves at least 40 % of the grid's energy use with the intended PV-battery system, while also aiding in the management of solar and grid instability by guaranteeing that electricity is accessible at all times.

Multi-objective generation scheduling towards grid-connected hydro–solar–wind power system based the coordination of economy, management, society, environment: A case study from China

The rapid development of solar and wind power, with their inherent uncertainties and intermittency, pose huge challenges to system stability. In this paper, a grid-connected hybrid power system that fully utilizes the complementarity characteristics in hydro, solar and wind power sources is proposed, which is capable of realizing an economic, managerial, social and environmental equilibrium in daily generation scheduling. A multi-objective optimization model is then proposed to determine the best possible solutions under nine typical scheduling scenarios, with ɛ-constraint method and fuzzy satisfying approach applied. A real case from the large-scale demonstration project in Qinghai, China clearly proved that the grid-connected hydro–solar–wind power system can provide significant comprehensive benefits. Specifically, on sunny days of normal season, the highest economic benefits can reach 1205820 ×104CNY, consumer surplus is up to 6760 ×104CNY, and the carbon emissions are as low as 159 ×103tonnes. Meanwhile, hydropower, preferred as a flexible renewable power source, can effectively conduct the peak regulation, making the residual loads deviation lowest of 740.447 MWh. Future studies can focus on the long-term perspectives, further analyze the storage technology, demand response and carbon taxes.

Design of support vector machine controller for hybrid power system automatic generation control

ABSTRACT This paper describes an online adaptive tuning methodology for Automatic Generation Control (AGC) of grid-connected wind-diesel hybrid power systems using the Support Vector Machine (SVM) controller. Using the Simulink design optimization tool/MATLAB, an optimized PID controller is first designed. To acquire system uncertainty, the SVM controller is trained using the input-output data set of an optimized PID controller obtained by varying the system nominal parameters by 40%. Simulations are carried out for conventional power generating units of various control areas integrated with hybrid wind-diesel power system. Outcomes are presented in the form of frequency aberration response, deviation in tie-line power exchange, and variation in mechanical power, and the efficacy of the proposed controller is presented in view of settling time, undershoot and overshoot. The impact of the hybrid power system on the thermal generating system is noted, and the usefulness of the developed SVM controller in keeping frequency and tie-line power exchange deviations within the stipulated limits is explored. The proposed SVM controller diminishes the settling time of frequency deviation response from 19.24 seconds to 14.36 seconds, and the undershoot and overshoots are reduced from 4.42% to 2.83% and 0.85% to 0.28%, respectively, for a three area three machine power structure. Further, the stability of the power systems under study is studied using bode-plot analysis with the designed controllers. As a result, the results indicated the robustness of the proposed SVM controller in minimizing system frequency and tie-line power variations caused by generation and load mismatch, as well as enhancing system stability.

Hybrid Energy Systems: Optimal Resource Determination and Cost Evaluation Using Homer Grid Software

This paper proposes a resource evaluation and validation study of a grid-connected hybrid power system whichtends to maximize the use of renewable energy generation with energy storage systems while minimizing thetotal system cost. The HOMER (Hybrid Optimization of Multiple Energy Resources) Grid software is adoptedin this study to find the optimal configuration of solar energy sources with battery storage systems to delivercomplementary electricity supply to satisfy AC primary load of 68.55 kWh/day with a 10.2 kW peak loaddemand to a building on a University campus premises located in the Niger Delta region of Nigeria. The resultsobtained from simulations showed a list of feasible resource configurations for the hybrid system. However,the most optimal/economical configuration is a grid-connected Solar PV-Gasoline system with a least cost ofenergy (COE) at ₦93.83/kWh and 6.7% renewable energy fraction.

A Student Psychology-Based Optimization Algorithm for Optimized Frequency Control of Isolated and Grid Connected Hybrid Power System

A Student Psychology-Based Optimization Algorithm for Optimized Frequency Control of Isolated and Grid Connected Hybrid Power System

Smart energy management for optimal economic operation in grid-connected hybrid power system

ABSTRACT This manuscript presents a hybrid method for smart energy management (EM) in grid connected microgrid (MG) system. The grid connected micro grid system consists of photovoltaic (PV), wind turbine (WT), micro turbine (MT), and battery. The proposed method is the combined execution of Radial Basis Function Neural Network (RBFNN) and Squirrel Search Algorithm (SSA), hence it is called RBFNN-SSA method. Here, the necessary load demand of grid-connected MG system is constantly monitored by AI strategy. SSA has developed the perfect combination of MG considering the forecast load demand. The major intention of the RBFNN-SSA method is fuel cost involvement, grid power hourly power variation, operation with maintenance cost of grid connected micro grid system. The constraints are the accessibility of renewable energy sources (RES), power requirement and state of charge (SoC) of storage elements. Batteries are used as an energy source, to stabilize and allow the renewable power system units for maintaining constant output power. The proposed method is activated in MATLAB/Simulink working site. Then, the efficiency is assessed with existing methods such as improved artificial bee colony (IABC), bacterial foraging optimizer and artificial neural network (BFOANN), ant lion optimizer (ALO), grasshopper optimization algorithm with particle swarm optimization including artificial neural network (GOAPSNN). The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean bias error (MBE) of proposed and existing methods under 50 and 100 count of trails are also analyzed. The proposed technique achieves the RMSE is 9.3, MAPE is 4.2, and MBE is 2 for 50 number of trails. For 100 count of trails, the proposed method achieves the RMSE is 13.5, MAPE is 3.9 and MBE is 5.7. The mean, median and standard deviation of RBFNN-SSA method achieves 0.9681, 0.9062 and 0.1099. The elapsed time of RBFNN-SSA method attains 30.15 s.

Artistic feasibility research on a standalone hybrid solar/wind system based on IncCond algorithm under variable load demands-a case study: South Algeria

<span lang="EN-US">The aim of this research study is to describe the hybrid renewable energy resources, the photovoltaic and the wind turbine are utilized to produce AC power for a Sahara Hassi R'Mel region in south of Algeria is optimally designed. Hybrid power generation systems are an operative solution for the variable generated power of renewable energy sources. In the new design, the ability circuit and the surveillance regulation of the presented grid-connected hybrid power system simulation is examined via MATLAB/Simulink. To detect the feasibility of the controlled system, this system is studied under various solar radiation and wind speed profiles. On the basis of the results, good tracking with a high accuracy rate is obtained after using filtering component by enhancing the different topology configurations in the expression of comparison voltage (V), and power (W). Overtime, the overall system efficiency is enhanced compared to the MPPT control system. The obtained simulation results for the incremental conductance PV/Wind MPPT controller have accomplished high effective system achievements. IncCond method is appropriate for working in vastly variable weather conditions with easy design, high tracking velocity, and minimum step count.</span>

A Capacitive Bridge-Type Superconducting Fault Current Limiter to Improve the Transient Performance of DFIG/PV/SG-Based Hybrid Power System

This paper proposes a capacitive bridge-type superconducting fault current limiter (CB-SFCL) to address the most concerning issue with the grid connected hybrid power system by improving the transient performance. The hybrid system incorporates a doubly fed induction generator (DFIG) based wind farm, a solar photovoltaic (PV) system and a synchronous generator (SG) based power system. The CB-SFCL incorporates a high temperature superconductor (HTS) along with a power capacitor to provide adequate reactive power support before and after the fault. The capacitor is kept inactive during normal operation by a control circuit to ensure seamless operation. During fault, the capacitor gets connected in series with the HTS and suppress the fault current. The performance of the CB-SFCL is investigated by proper graphical and mathematical analyses and conclusions are obtained by comparing them with that of the conventional bridge-type superconducting fault current limiter (BSFCL) and the capacitive bridge-type fault current limiter (CBFCL). The analyses support the theoretical superiority of the CB-SFCL over the BSFCL and the CBFCL by a satisfying margin.

Power Quality Improvement in HRES Grid Connected System with FOPID Based Atom Search Optimization Technique

An intelligent control strategy is proposed in this paper which suggests the Optimum Power Quality Enhancement (OPQE) of grid-connected hybrid power systems with solar photovoltaic, wind turbines, and battery storage. Unified Power Quality Conditioner with Active and Reactive power (UPQC-PQ) is designed with Atom Search Optimization (ASO) based Fractional-order Proportional Integral Derivative (FOPID) controller in the proposed Hybrid Renewable Energy Sources (HRES) system. The main aim is to regulate voltage while reducing power loss and reducing Total Harmonic Distortion (THD). UPQC-PQ is used to mitigate the Power Quality (PQ) problems such as sag, swell, interruptions, real power, reactive power and THD reductions related to voltage/current by using ASO based FOPID controller. The developed technique is demonstrated in various modes: simultaneous to improve PQ reinforcement and RES power injection, PRES > 0, PRES = 0. The results are then compared to those obtained using previous literature methods such as PI controller, GSA, BBO, GWO, ESA, RFA, and GA and found the proposed approach is efficient. The MATLAB/Simulink work framework is used to create the model.

Legendre-wavelet embedded NeuroFuzzy feedback linearization based control scheme for PHEVs charging station in a microgrid

The immense emergence of plug-in hybrid electric vehicles (PHEVs) is envisioned in the future. The rapid proliferation of PHEVs and their charging triggers intense surges in the load during load peak hours. A sophisticated controlled charging station is developed for PHEVs to alleviate grid load during peak demand hours. A novel feedback linearization embedded full recurrent adaptive NeuroFuzzy Legendre wavelet control (FBL-FRANF-Leg-WC) technique is employed to control the charging of PHEVs. The antecedent part of the NeuroFuzzy framework is based on recurrent Gaussian membership function while the consequent part comprises of recurrent Legendre wavelet. The charging station is integrated into a grid-connected microgrid hybrid power system. The charging station consists of five different PHEVs with seven different modes of operation. The performance of the control scheme is tested for various power quality and power system stability parameters. The effectiveness of the suggested control scheme is validated through simulation results by comparing with adaptive NeuroFuzzy, adaptive PID, and conventional PID control scheme.

Comparative study of off-grid and grid-connected hybrid power system: issues, future prospects and policy framework

A sustainable energy system is of utmost importance for any significant development in any nation.This work identified some obstacles inhibiting rapid renewable energy growth in Nigeria and recommended some policy measures in overcoming them. Moreover, a comparative study of off-grid (OG) and grid-connected (GC) small hydro-solar photovoltaic-diesel hybrid system was carried out using Oyan river, Abeokuta, Nigeria as a case study. The hybrid components were modeled with and without the grid. The hydro solar resources data of the area were collected and analyzed using hybrid optimization model for electric renewable (HOMER) software. The simulation results proved that the GC hybrid power system is better than the OG hybrid power system in technical and economic terms depending on the location. This paper, therefore, proposed the use of OG hybrid power system for electrification of distant villages especially where extending the grid seems infeasible and the use of GC hybrid power system in the urban areas. The work will assist power sector stakeholders in making informed decisions towards the growth of hybrid power system technology in Nigeria.

Modelling and cost optimization of a community microgrid

With the increasing energy demand and promotion of usage of renewable energy resources to reduce the environmental effects, hybrid renewable energy system (HRES) has become very feasible and attractive. In this paper grid-connected hybrid power system model consisting of Solar PV and Wind turbine as HRES are considered to carry out the techno-economic feasibility study. The potential of wind and solar energies are estimated by collecting the data from various resources of a community Microgrid located at the geographical location with latitude of 14.135° N, longitude of 76.239° E in Chitradurga District, south Indian state of Karnataka. HOMER Pro software is used for simulation and promising results are obtained.

Design of Grid Connected Hybrid Power System

Design of Grid Connected Hybrid Power System

Size optimisation of RES-based grid connected hybrid power system using harmony search algorithm

In the present context, renewable energy sources are recognised as the best alternative of fossil fuels in order to fulfil the ever increasing demand with minimum harmful impact on environment. The combination of renewable energy sources can also be used in grid connected environment. This will help in reducing the burden of increasing demand on grid. Also, utility grid can supply deficit demand in case available generation from renewable energy sources becomes less than the demand. In the present paper, intelligent modelling of grid connected hybrid system has been carried out. Further, the total net present cost (NPC) of the considered system is optimised under the constraints of power reliability, storage limit on battery, etc. Finally, a comparative analysis has also been performed between the grid connected and standalone hybrid system based on the size and cost of components.

Size optimisation of RES-based grid connected hybrid power system using harmony search algorithm

Size optimisation of RES-based grid connected hybrid power system using harmony search algorithm