Grid-connected Hybrid Renewable Energy Research Articles

Optimal operation of a hybrid multisource energy system considering grid load shedding

On-site grid-connected hybrid renewable energy systems are extensively used in the mitigation of scheduled grid load shedding in commercial buildings. This paper proposes an optimal operation of grid-connected hybrid PV-battery-Diesel generator (DG) energy system under scheduled grid load shedding for a commercial building. A mathematical model for an optimal operation of a grid-connected PV-Battery-DG energy system that has a potential of mitigating the scheduled load shedding is developed and implemented. The impact assessment of scheduled load shedding on commercial consumers is also assessed on the cost saving as compared to the baseline without load shedding. Results showcase the potential of the proposed grid-connected hybrid PV-Battery-DG to mitigate scheduled grid load shedding in commercial buildings. Scheduled grid load shedding impacts differently on commercial consumers depending on the scheduled time of a day.

Techno-Economic Analysis and Optimisation of Campus Grid-Connected Hybrid Renewable Energy System Using HOMER Grid

This study aimed to conduct a techno-economic performance and optimisation analysis of grid-connected PV, wind turbines, and battery packs for Syiah Kuala University, situated at the tip of Sumatra island in the tsunami-affected region. The simulation software Hybrid Optimisation Model for Electric Renewables (HOMER) was used to analyse and optimise the renewable energy required by the institution. The methodology began with the location specification, average electric load demand, daily radiation, clearness index, location daily temperature, and system architecture. The results revealed that the energy storage system was initially included in the simulation, but it was later removed in order to save money and optimise the share of renewable energy. Based on the optimisation results, two types of energy sources were chosen for the system, solar PV and wind turbine, which contributed 62% and 20%, respectively. Apart from the renewable energy faction, another reason for the system selection is cost of energy (CoE), which decreased to $0.0446/kWh from $0.060/kWh. In conclusion, the study found that by connecting solar PV and wind turbines to the local grid, this renewable energy system is able to contribute up to 82% of the electricity required. However, the obstacle to implementing renewable energy in Indonesia is the cheap electricity price that is mainly generated using cheap coal, which is abundantly available in the country.

Optimal design, techno-economic and sensitivity analysis of a grid-connected hybrid renewable energy system: a case study

Abstract Integrating renewable resources with existing power system are rapidly increasing day by day, becoming an effective way to rural electrification where distribution system extension is not economically feasible. This research aims to design such an optimal grid-connected hybrid renewable energy system (HRES) modelled using solar, wind energy, diesel generator, battery storage, thermal loads, thermal load controller, and boiler. This system is designed to meet the load demand requirement of chintalayapalle village, Andhra Pradesh, India. The techno-economic, sensitivity analysis and cost-effective optimal configuration of this system have been performed using HOMER software. Totally eight configurations have been designed here and the optimal configuration have been identified based on the minimum net present cost (NPC), lowest cost of energy (COE), and the highest renewable fraction (RF). Results obtained shows that the optimally configured system is more environmentally friendly because of less carbon emission. Also, it would be more cost-effective when wind power becomes the main energy source and combined with moderate capacity of solar photovoltaic and battery.

Reactive Power Compensation in a Hybrid Renewable Energy System through Fuzzy Based Boost Converter

The reactive power compensation is essential during hybrid grid connected system, because the overall power factor of the power systems is reduced due to DC energy fed to the grid using electronic energy inverters. Increased load on the grid due to poor power factor triggers losses in the grid. The main objective of the work related to control the Reactive Power flow in grid connected Hybrid Renewable Energy System (PV-wind-battery). The objectives of the work were achieved by satisfying the load demand, injecting the reactive power from hybrid sources to the grid. First, the proposed technique with fuzzy based boost converter is implemented. It reduced power conversion stages, decreases the losses compared to existing Hybrid Grid-connected systems. The most significant result of the work is the conclusion that the fuzzy based boost converter should increase the Maximum power from solar PV Panel, The speed control of wind energy system is control by speed controller-fuzzy rule, and it created with low speed to high speed. The significance of the obtained results is that the used methodology allowed maximum energy utilized by hybrid renewable energy system to grid. The reactive power is maintained at zero level in order to ensure the unity power factor operation. But rather significantly enhances the small voltage fluctuation in the grid. In addition, to reduces the current total harmonic distortion to 1.9 %, which is good lower than the requirement for network operation. The proposed method is verified using MATLAB/Simulink. The simulation results were supported experimentally.

Techno-Economic Analysis of Grid-Connected Hybrid Renewable Energy System for Remote Areas Electrification Using Homer Pro

Techno-Economic Analysis of Grid-Connected Hybrid Renewable Energy System for Remote Areas Electrification Using Homer Pro

Optimal sizing for a grid-connected hybrid renewable energy system: A case study of the residential sector in Durban, South Africa

Many countries, including South Africa, have introduced policies and incentives to increase their renewable energy capacities in order to address environmental concerns and reduce pollutant emissions into the atmosphere. In addition, consumers in South Africa have faced the ever-increasing price of electricity and unreliability of the grid since 2007 due to the lack of sufficient electricity production. As a result, employing hybrid renewable energy systems (HRESs) have gained popularity. This research focuses on grid-connected HRESs based on solar photovoltaic (PV) panels and wind turbines as a potential way of reducing the dependency of residential sector consumers on the grid. It aims to identify the optimal sizing of renewable energy sources to be cost-effective for consumers over a certain period of time, using Durban as a case study. Two artificial intelligence methods have been used to obtain the optimal sizing for the available PV panels, wind turbines and inverters. The results shown that the combination of PV panels and battery storage can be a profitable option. A system using higher rated power PV panels can start to become profitable in a shorter lifetime, but employing batteries can only be cost-effective if a long enough lifetime is considered.

Optimising Electrical Power Supply Sustainability Using a Grid-Connected Hybrid Renewable Energy System—An NHS Hospital Case Study

This study focuses on improving the sustainability of electrical supply in the healthcare system in the UK, to contribute to current efforts made towards the 2050 net-zero carbon target. As a case study, we propose a grid-connected hybrid renewable energy system (HRES) for a hospital in the south-east of England. Electrical consumption data were gathered from five wards in the hospital for a period of one year. PV-battery-grid system architecture was selected to ensure practical execution through the installation of PV arrays on the roof of the facility. Selection of the optimal system was conducted through a novel methodology combining multi-objective optimisation and data forecasting. The optimisation was conducted using a genetic algorithm with two objectives (1) minimisation of the levelised cost of energy and (2) CO2 emissions. Advanced data forecasting was used to forecast grid emissions and other cost parameters at two year intervals (2023 and 2025). Several optimisation simulations were carried out using the actual and forecasted parameters to improve decision making. The results show that incorporating forecasted parameters into the optimisation allows to identify the subset of optimal solutions that will become sub-optimal in the future and, therefore, should be avoided. Finally, a framework for choosing the most suitable subset of optimal solutions was presented.

Optimization and Comparative Economic Analysis of Standalone and Grid-Connected Hybrid Renewable Energy System for Remote Location

Due to rising population growth and economic development, there is indeed a growing demand for electricity. Both in aspects of generation and transmission, conventional power firms are striving to manage these demands. Moreover, the ubiquitous utilization of electricity and other power generators, which are mainly driven from fossil fuels, seems to have some limitations, like declining performance and restricted energy production. As a result, use of renewable energy sources is incredibly important. Decentralized power generation in remote regions has become the primary requirement of society, based on renewable energy. Particularly in comparison with the electrification of urban areas, rural electrification is quite expensive. Microgrid’s development utilizing hybrid power is a potential solution for the electrification of rural regions where the transmission chain of network’s extension is unfeasible or inefficient. This research aims to structure a power generation model associated with different HRES combinations using a HOMER software application at a location in India. In the findings of this research, it has been observed that NPC, O&M, COEs, and RF of on-grid energy systems are better than off-grid energy systems. In the study, between eight hybrid system combinations, the lowest COE of 0.034 $/kWh is obtained with the PV-WT-MH-GRID-CT system in the on-grid scenario. This analysis shows NPC, COE, O&M, and renewable fraction are sensitive to the variation in all the considered sensitivity parameters1,2,3,4.

Corrigendum

Yazid Berkani, Nabil Taib "Dual Input Z-source Indirect Matrix Converter for Grid Connected Hybrid Renewable Energy Systems", 65(3), pp. 218–226, 2021. (in this issue)https://doi.org/10.3311/PPee.18031When the above article was first published online Fig. 12 was incorrect. This has now been corrected in the online version.The correct version of Fig. 12 is published here.

SLDB controller based 31 level MLI for grid-connected hybrid renewable energy sources

SLDB controller based 31 level MLI for grid-connected hybrid renewable energy sources

A Grid-connected Hybrid Renewable Energy System Using High-frequency Multi-winding Transformer and Phase Shift Modulation Technique

This paper presents a topology of multi-port phase-shift converter for integration of a PV system, a wind-turbine generator and a battery to supply a grid-connected domestic load. The main advantage of the topology is using a multi-winding high-frequency transformer to couple the input and outputs of the system. This simplifies the power flow control and provides isolation between the converter ports. Detailed operation of the proposed topology and the control system analysis are discussed. A numerical simulation of the proposed system is carried out to confirm the system operation and control technique.

Dual Input Z-source Indirect Matrix Converter for Grid Connected Hybrid Renewable Energy Systems

This paper presents a new converter topology for grid connected Hybrid Renewable Energy System (HRES). The proposed topology named Dual Input Z-source Indirect Matrix Converter (DIZIMC) consists of an Ultra Sparse Z-source Matrix Converter (USZMC) interfacing PV and Wind Turbine (WT) to the grid. The DC link of the proposed converter is replaced by Interconnection Sources System (ISS). The ISS operates according to whether the sources produce energy or not. It allows connecting the sources individually or simultaneously and even isolates them if necessary. In the other hand, the DIZIMC provides several advantages such as reduced number of IGBTs and compact size inherited from USZMC, the use of Z-sources instead of conventional DC/DC converters keep the matrix configuration of the global structure. The global model of the proposed system was tested by simulation under Matlab/Simpowersys environment. The obtained results show clearly freedom in connecting the operational sources, also a better quality of energy injected to the grid.

Design of PID Controller with Grid Connected Hybrid Renewable Energy System Using Optimization Algorithms

Design of PID Controller with Grid Connected Hybrid Renewable Energy System Using Optimization Algorithms

Hybrid renewable energy system optimum design and smart dispatch for nearly Zero Energy Ports

Climate change mitigation has become a ports' emergency; they endeavour to improve their energy efficiency and diminish their carbon footprint. The optimisation analysis of a seaport grid-connected hybrid renewable energy system is presented, comparing the impact of two dispatch strategies and three energy storage systems. Seventeen scenarios have been examined regarding the possible combinations of the most mature renewable and energy storage systems according to the Levelised Cost of Energy, environmental footprint, and future employability. Vanadium Redox Flow Battery based Hybrid Renewable Energy System employed offering 10-h port services' autonomy. For the grid-connected net metering and 24-h port autonomy, the optimal Levelised Cost of Energy is 12.9 c€/kWh. The overall optimum was 8.0 c€/kWh, incorporating 10-h port services' autonomy. All the alternative cases proved much lower of the Levelised Cost of Energy could be much lower than the current grid's tariff. Peak shaving strategy is proven to be more efficient for seaports than cycle charging, resulting in improved energy management and lower energy billing costs by setting peak monthly demand limits. The emissions are diminished to zero, as the net grid purchases are zero, incorporating totally green infrastructure. The nearly Zero Energy Port concept proved to be a viable and feasible solution for ports towards sustainability.

Anovel power management strategies inPV‐wind‐based grid connected hybrid renewable energy system using proportional distribution algorithm

<scp>A</scp>novel power management strategies in<scp>PV‐wind</scp>‐based grid connected hybrid renewable energy system using proportional distribution algorithm

Integrated arrangement of advanced power electronics through hybrid smart grid system

As an enabler component for renewable energy integration, power electronics (PE) technology in smart grid system is one of the most important issues of development the electrification, decentralization and information-technology/operation-technology (IT/OT) digitization within the electrical energy transmission and distribution systems. The arrangement of PE may different along the feeder either for grid-connected photovoltaic (PV), wind turbine, fuel cells, wave energy system and battery storage unit, respectively.This is due to the electric voltage that might need to be converted from alternating current (AC) to direct current (DC) and vice versa. For that reason, this paper proposed a concept of advanced PE as an integrated arrangement of several AC/DC/AC-and DC/AC- converters in such ways that support thepreviously mentioned grid-connected hybrid renewable energy sources and distributed generators (DGs) along the distribution feeder. Additionally, for the system that supported by battery storage unit, then this hybrid smart grid concept might become the answer for future utility needs.

Techno-Economic Feasibility Analysis of a Hybrid Renewable Energy Supply Options for University Buildings in Saudi Arabia

Abstract This study presents a detailed feasibility analysis of technical and financial assessment for grid-connected Hybrid Renewable Energy System (HRES) configurations by including grid-only, HRES-only and grid-HRES at four different provinces in the Kingdom of Saudi Arabia (KSA), namely; (Al Baha University, University of Jeddah, Prince Sattam Bin Abdulaziz University, and Tabuk University). The objective of this paper is to search the possibility of supplying the load demand with the optimum system that has the lowest net present cost (NPC) and greenhouse emission CO2. The simulation results show that NPC of a proposed grid/PV system, at the current grid’s tariff, is more sufficient than other configurations with a result in a renewable fraction of more than 50%, a payback time of 17 years, and 54.3% reduction in CO2. The results also show that the integration of 62 kW PV array with the main grid is the best configuration that leads to the minimum cost of energy (COE) of 0.0688 $/kWh and the sell back energy of 9.16% of total energy consumption at Al Baha University. Besides, optimization modeling addresses that HRES-only system can supply the full load demand without power shortage (&lt;0.1%) with a major contribution from solar PV by 78.5%, wind energy shares 11.3% of load demand, and 10.2% from battery banks. The developed analysis concludes that the objective function is feasible for the selected locations. The study has three novelties. Firstly, the required load at different locations of the university’s buildings at KSA is supplied by minimizing COE. The objective function is achieved by considering a combination of HRES. Then, it applies the sensitivity analysis for several cases such as payback time, gird’s tariff variation, and load demand change. Finally, the current analyses are applicable to any university at KSA and around the world.

Power flow management of grid connected HRES system using a CFANN technique

ABSTRACT This manuscript presents a hybrid technique-based power flow management of grid-connected Hybrid Renewable energy sources (HRES). HRES has Photovoltaic (PV), Wind Turbine (WT) as well as Diesel Generator (DG). The proposed hybrid technique is the combined implementation of Cuttlefish Algorithm (CFA) and artificial neural network (ANN) and commonly called CFANN technique. Atproposed technique, CFA is used to create the precise control signals for system and builds the control signal database off-line based on power range among source side and load side. Dataset made to operate ANN online and lead the control procedure at less implementation time. The behaviours of system are examined depend on objective function. To analyse power flow management, equality and inequality restrictions are distinct that specifies the renewable energy source availability and power demand. By this appropriate control, HRES can considerably improve the dynamic security of power system. The result shows that the energy sources of renewable energy system and its power converters are controlled and the error is reduced by 92.42%. At that time, proposed model is implemented on MATLAB/Simulink work platform and implementation is evaluated to existing methods.

Power generation cost minimization of the grid-connected hybrid renewable energy system through optimal sizing using the modified seagull optimization technique

A hybrid renewable power system is studied in this paper. This system is composed of PV panels, wind turbines, inverter, rectifier, electrolyzer, and fuel cell such that it prioritizes storing excess energy by converting it to hydrogen and using it later in the fuel cell. Additional extra generation power is sold to the main electricity network. The system generates power from clean sources and has zero emission. To achieve minimum power generation cost, the optimal size of each component is obtained using the proposed modified seagull optimization technique. The cooperative generation of wind and PV and energy storage mitigate the uncertain behavior of renewable energy sources. The proposed hybrid power system and optimization are implemented in a real-world case study in Qingdao, China. The consumption and meteorological data of the year 2018 are used as input to the system. To prove the superiority of the proposed optimization method in terms of accuracy and computation time, it is compared to two other optimization methods, namely original seagull optimization algorithm (SOA) and modified farmland fertility algorithm (MFFA), which are used in similar applications. The proposed method has achieved 2.02% and 2.78% better results and converged 69.36% and 47.07% faster compared to conventional SOA and MFFA methods, respectively. In addition, the hybrid system is able to operate with high reliability and loss of power supply probability well below the threshold of 8.96e20.

Optimal sizing of grid-connected hybrid renewable energy systems without storage: a generalized optimization model

ABSTRACT In this study, a weighted multi-objective mixed-integer linear programming (WMO-MILP) model considering both economic and environmental factors is proposed for the optimal sizing of the grid-connected hybrid renewable energy systems without storage (HRES-WS). The proposed model is capable of designing the system including several different types of renewable energy generation units to meet the demands of various consumption points. One of the significant values of the model is that it holistically combines the operational, technical, physical and/or capacity constraints which are rarely considered in an integrated way in the literature. Another contribution of the model is its ability to evaluate the tradeoff between the cost-related and CO2 related conflicting objectives by allocating them various weights resembling the decision-maker’s cost-based, environmental-based, or partially cost- and environmental-based priorities. A case study is utilized to demonstrate the value of the model. In order to take into consideration the stochastic nature of the modeling environment, the Monte Carlo simulation is used to predict weather data and load demand based on the historical data. The findings indicate that the combined effect of environmental and cost-related objectives influences the demand to be met by RES at acceptable cost and CO2 emission level. For example, focusing only on the environmental objective, the annual amount of CO2 emission decreases by 14% and the total installed capacity increases by 41%, and therefore the system cost increases by 205% as compared to the base case in which the weight of each objective function is assumed to be equal. The proposed model has the potential to significantly support decision-making process when evaluating a grid-connected HRES-WS both economically and environmentally.