Grid-connected Hybrid Renewable Energy Research Articles

Control strategies for grid-connected hybrid renewable energy systems: Integrating modified direct torque control based doubly fed induction generator and ANFIS based maximum power point tracking for solar PV generation

This research article introduces advanced control strategies for grid-connected hybrid renewable energy systems, focusing on a doubly fed induction machine (DFIM) based wind power plant and a photovoltaic based solar power plant. The proposed approach integrates Direct Torque Control (DTC) with modified filters and a fractional Proportional-Integral (PI) controller for the DFIM wind power plant. The modified DTC utilizes estimated torque and flux, employing a modified filter to minimize deviations, and a fractional PI controller for improved vector selection. This results in an enhanced duty cycle for the rotor side converter, optimizing power output to the grid. Additionally, an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based Maximum Power Point Tracking (MPPT) algorithm is implemented for the solar power plant, dynamically adjusting the duty cycle for increased power output compared to conventional MPPT methods. Simulation results in MATLAB and experimental verification demonstrates the stability and feasibility of the proposed controllers, showcasing superior performance compared to conventional counterparts under various operating conditions.

An innovative hybrid controller-based combined grid-connected hybrid renewable energy system

An innovative hybrid controller-based combined grid-connected hybrid renewable energy system

Sizing and energy management of grid-connected hybrid renewable energy systems based on techno-economic predictive technique

This study intends to construct and optimally run a grid-connected hybrid renewable energy system (HRES) powering a residential building. A special techno-economic multi-objective optimization technique is used for sizing the HRES. In addition, an energy management strategy (EMS) is established as a distinct multi-objective optimization problem to minimize degradation and operating costs while improving system performance. A Bi-level mixed integer non-linear programming (BMINLP) is the framework used to formulate the two-optimization problems. Sizing problem is characterized by the higher level, on contrast; the nested EMS problem within the constraints of the size problem is presented on the lower level. For this investigation, the problem is executed via the MATLAB program. The global optimization toolbox is applied via the Multi-Objective Genetic Algorithm (MOGA) to solve the sizing optimization. While the EMS is executed using the "Intlinprg" mixed integer linear programming (MILP) solver. The technical and economic performance parameters such as degradation, renewable energy fraction (REF), operating, maintenance, and investment costs are evaluated in this study. The primary results reveal that the summer week encounters the lowest total cost and the highest REF, at roughly 99484 $ and 60%, respectively. Furthermore, the investigation shows that the lowest degradation value attained in the same week with approximately 50.

Optimal Design of Grid-Connected Hybrid Renewable Energy System Considering Electric Vehicle Station Using Improved Multi-Objective Optimization: Techno-Economic Perspectives

Electric vehicle charging stations (EVCSs) and renewable energy sources (RESs) have been widely integrated into distribution systems. Electric vehicles (EVs) offer advantages for distribution systems, such as increasing reliability and efficiency, reducing pollutant emissions, and decreasing dependence on non-endogenous resources. In addition, vehicle-to-grid (V2G) technology has made EVs a potential form of portable energy storage, alleviating the random fluctuation of renewable energy power. This paper simulates the optimal design of a photovoltaic/wind/battery hybrid energy system as a power system combined with an electric vehicle charging station (EVCS) using V2G technology in a grid-connected system. The rule-based energy management strategy (RB-EMS) is used to control and observe the proposed system power flow. A multi-objective improved arithmetic optimization algorithm (MOIAOA) concept is proposed to analyze the optimal sizing of the proposed system components by calculating the optimal values of the three conflicting objectives: grid contribution factor (GCF), levelled cost of electricity (LCOE), and energy sold to the grid (ESOLD). This research uses a collection of meteorological data such as solar radiation, temperature, and wind speed captured every ten minutes for one year for a government building in Al-Najaf Governorate, Iraq. The results indicated that the optimal configuration of the proposed system using the MOIAOA method consists of eight photovoltaic modules, two wind turbines, and thirty-three storage batteries, while the fitness value is equal to 0.1522, the LCOE is equal to 2.66 × 10−2 USD/kWh, the GCF is equal to 7.34 × 10−5 kWh, and the ESOLD is equal to 0.8409 kWh. The integration of RESs with an EV-based grid-connected system is considered the best choice for real applications, owing to their remarkable performance and techno-economic development.

Optimization Model of Hybrid Renewable Energy Generation for Electric Bus Charging Stations

This paper introduces a comprehensive approach for sizing grid-connected hybrid renewable energy systems tailored for electric bus fleet operations. The study involves two main steps. First, a mathematical model that optimizes the configuration of such systems by considering daily electric bus consumption, solar irradiance, wind speed, and biomass potential is formulated. The model utilizes Pareto frontier multi-objective optimization to minimize the net present cost, the cost of energy, and greenhouse gas emissions. Second, the model is rigorously applied and tested in a real-world case study in Fez, Morocco, using HOMER Pro; the case study centers on the daily energy requirements of the buses, estimated at 2.5 megawatt hours per day, with a peak demand of 345 kilowatts. Two scenarios are explored, revealing a discernible trade-off dilemma between the full hybrid renewable energy scenario (Scenario 1) and the grid-connected hybrid renewable energy scenario (Scenario 2). In Scenario 2, the grid-connected hybrid renewable energy system demonstrates a notable 42.8% reduction in the net present cost, totaling USD 984,624. Similarly, the levelized cost of energy experiences a significant decrease, reaching approximately 0.08 USD/kWh, marking a 38.1% reduction. However, this apparent economic advantage is juxtaposed with a critical consideration—an increase in greenhouse gas emissions from null to 330,418 kg/year.

Investment-based optimisation of energy storage design parameters in a grid-connected hybrid renewable energy system

Grid-connected hybrid renewable power systems with energy storage can reduce the intermittency of renewable power supply. However, emerging energy storage technologies need improvement to compete with lithium-ion batteries and reduce the cost of energy. Identifying and optimising the most valuable improvement path of these technologies is challenging due to the non-linearity of the energy system model when considering parameters as independent variables. To overcome this challenge, a novel investment-based optimisation method is proposed. The method involves linear optimisation of the hybrid renewable energy system and subsequent investment optimisation, accounting for diminishing improvements per investment. The results from applying the investment-based optimisation to thermal energy, pumped thermal energy, molten salt, and adiabatic compressed air energy storage technologies, show that improving the discharge efficiency is the most valuable for all technologies. The second most important parameters are the costs of discharge capacity and energy storage capacity, and the least important parameters are the charge capacity cost and charge efficiency. The study provides detailed improvement pathways for each technology under various operational conditions, assisting developers in resource allocation. Overall, the investment-based optimisation method and findings contribute to enhancing the competitiveness of emerging energy storage technologies and reducing reliance on batteries in renewable energy systems.

Economic And Environmental Analysis of Grid-Connected Hybrid Renewable Energy System with Homer: Case of İzmir Industrial Region

Bu çalışma kapsamında İzmir ilinde bulunan endüstriyel bölgenin elektrik ihtiyacının karşılanması için şebeke bağlantılı hibrit enerji sistemi tasarımı yapılmıştır. Yapılan tasarımla, seçilen endüstriyel bölgenin enerji talebinin karşılanması, birim elektrik maliyetinin minimize edilmesi ve elektrik üretiminden kaynaklanan karbon emisyonunun azaltılması amaçlanmıştır. Bölgenin meteorolojik verileri incelendiğinde yıllık güneş radyasyon miktarı ve rüzgâr hızının yenilebilir enerji santralleri kurulumu açısından yeterli olduğu görülmüştür. Çalışmada enerji potansiyeli yüksek olan İzmir ilinde şebeke bağlantılı ve yenilebilir enerji sistemlerinden oluşan beş farklı senaryo tasarlanmıştır. Senaryoların oluşturduğu santrallerde kullanılan bileşenler; güneş paneli, rüzgâr türbini, dönüştürücü ve bataryadan oluşmaktadır. HOMER yazılımı kullanılarak alınan simülasyon sonuçlarında birim enerji maliyeti, net şimdiki maliyeti, başlangıç maliyeti ve yıllık emisyon değerleri karşılaştırılmıştır. Özellikle yıllık emisyon değeri ve birim elektrik maliyet kriterleri göz önüne alındığında en verimli sistemin bataryalı hibrit enerji sistem tasarımı olduğu sonucuna varılmıştır. Bu sistem tasarımında birim elektrik maliyeti 0,0730 $ seviyesine düşürülmüş ve elektrik tüketiminden kaynaklanan yıllık emisyon değerleri %82 azaltılmıştır.

Coupled thermo-electrical dispatch strategy with AI forecasting for optimal sizing of grid-connected hybrid renewable energy systems

In multi-energy systems the full utilisation of the generated energy is a challenge. Integrating heat and electricity supply at the system level design could provide an opportunity to address this challenge. In this paper we introduce and examine two coupled thermal-electrical dispatch strategies for grid-connected hybrid multi-energy systems supplying electrical and thermal demand loads. The dispatch strategy employs forecasting of energy resources and demand loads to prioritise supplying the thermal load in times of renewable surplus. Four forecasting algorithms, namely, baseline forecast, Facebook Prophet (FBP), Neural Prophet (NP), and Long Short-Term Memory model (LSTM) are implemented and used to generate annual forecast data for solar irradiance, wind speed, and thermal and electrical demand loads. To integrate forecast data within the dispatch strategy, new parameters are proposed to quantify the expected available energy within the forecast time horizon. A building complex for the Department of Education in the UK is used for conducting a system design case study. A genetic algorithm-based multi-objective optimisation with the levelised costs of electricity and heat as two objectives is conducted. The results show that the proposed dispatch algorithm produces systems with reduced levelised costs compared to the base case of using utility gas and electricity. Forecasting is particularly useful in reducing cost of heat, as it can prioritise supplying the thermal load in times of renewable surplus. LSTM proved to be the most accurate forecasting algorithm for this case, where the data has strong seasonality and trends. The main contribution of this work is to propose and demonstrate the effectiveness of tightly coupling thermo-electrical dispatch algorithms of HRES from the design stage, and how to effectively integrate forecast data within such algorithms.

Techno-economic study and the optimal hybrid renewable energy system design for a hotel building with net zero energy and net zero carbon emissions

The tourism sector is a key source of national income, and the use of renewable energy resources promotes green and sustainable tourism. In addition, ensuring a reliable supply and efficient use of clean energy is a primary objective of Egypt's Vision 2030, as it has a significant impact on the sustainable development and growth of the tourism sector in Egypt. Net-zero energy buildings (NZEBs) are a promising decarbonization effort as they reduce energy consumption while increasing the share of renewable energy. Therefore, it is worth investigatingthe opportunities for NZEBs applications in tourism sector. This paper presents an optimization analysis of a hotel’s grid-connected hybrid renewable energy system (HRES) based on its technical, economical, and environmental prospects. Seven scenarios are considered for on-site generation to match the energy requirements of the specific hotel building. The proposed hybrid systems incorporate photovoltaic (PV), wind turbine (WT), and biogas generators into a grid-connected system for supplying power to a tourist hotel. The size of the microgrid system is optimized to decrease the net present cost (NPC) and levelized cost of electricity (LCOE). The results reveal that the PV/wind grid-connected system, with renewable energy generators consisting of 143 kW of photovoltaic modules and one 20 kW wind turbine with a hub height of 18 m, has the lowest NPC and LCOE. This hybrid energy system has a net present cost of 388 k$, which is significantly lower compared to the electricity grid's cost of 873 k$. The electricity price of the proposed HRES, at 2.1 ¢/kWh, is highly competitive with Egypt's retail electricity prices of 6.9 ¢/kWh. Moreover, grid-connected HRES can lower the pressure on the electricity grid arising from the feed-in of electricity from HRES. Furthermore, the proposed HRES will help slow climate change by reducing GHG emissions and fossil fuel usage. Finally, this study will provide valuable guidance for the practical application of NZEBs in Egypt as well as similar global zones.

Techno-economic analysis of grid-connected hybrid renewable energy system adapting hybrid demand response program and novel energy management strategy

Over the last two decades, there has been a significant interest in developing solutions to improve the efficiency of power systems, such as optimal energy consumption and management. The demand response programs (DRP) have long been one of the most effective strategies to encourage consumers to change their consumption behavior. In this paper, a novel hybrid DRP has been implemented by combining the time of use (TOU) and incentive-based (IB) DRP methods. To meet the load demand, a PV-WT-BESS hybrid renewable energy system (HRES) has been proposed in this work. Further, to analyze the impact of hybrid DRP on the capacity allocation of different system components, optimal sizing has been performed in two scenarios, one with the actual load and the second with the load after considering the hybrid DRP. The optimization has been carried out by using an improved search space reduction (ISSR) algorithm. To demonstrate the effectiveness of the ISSR algorithm, the obtained results are compared with other algorithms such as particle swarm optimization (PSO), grey wolf optimization (GWO), teaching-learning based algorithm (TLBO), seagull optimization algorithm (SOA), and sine cosine algorithm (SCA). Finally, a novel energy management strategy (EMS) is also proposed in this work on the supply side of the HRES, which intelligently uses the variations in the grid tariff to charge the BESS when the tariff is low. To demonstrate the proposed DRP and EMS-based sizing, a case study has been performed for a grid-connected PV-WT-BESS for the location of Kanyakumari, India. From the results obtained, it has been concluded that the hybrid DRP reduces the peak demand up to 5%, which reduces the levelized cost of energy (LCE) by 22%. Furthermore, the proposed novel EMS reduces the LCE further by 5%. The overall cost reduction of up to 25% has been achieved by using both the proposed hybrid DRP and EMS, while satisfying all necessary constraints.

Performance Analysis of a Hybrid Renewable-Energy System for Green Buildings to Improve Efficiency and Reduce GHG Emissions with Multiple Scenarios

A hybrid system, such as solar and wind, may be more successful than nonhybrid systems in accelerating the transition from conventional to renewable power sources. However, these new energy sources have several challenges, such as intermittency, storage capacity, and grid stability. This paper presents a complete analysis and study of a hybrid renewable-energy system (HRES) to convert a facility into a green building and reduce its dependence on conventional energy by generating clean energy with near-zero greenhouse-gas (GHG) emissions. The proposed system aims to reduce the energy bill of a hotel in Petra, Jordan, by considering different sustainable energy resource configurations in a grid-connected hybrid renewable energy system (GHRES). The hybrid optimization of multiple energy resources (HOMER) grid software was utilized on the hybrid systems to study ways to improve their overall efficiency and mitigate GHG emissions from an economic perspective. The hybrid system components included in the simulation were a solar photovoltaic (PV) system, a wind turbine (WT) system, a diesel generator (DG), and a converter. Five scenarios (PV–Converter–DG–Grid, PV–Converter–Battery–DG–Grid, WT–DG–Grid, PV–WT–Converter–Battery–DG–Grid, PV–WT–Converter–DG–Grid) were considered. The optimal configuration had a USD 1.16 M total net present cost, USD 0.0415/kWh cost of energy, 15.8% effective internal rate of return, and an approximately 77% reduction in carbon emissions compared to the base case.

Design and feasibility analysis of grid-connected hybrid renewable energy system: perspective of commercial buildings

Design and feasibility analysis of grid-connected hybrid renewable energy system: perspective of commercial buildings

Energy Management Strategies and Control of a Hybrid Grid-Connected Renewable Energy System with Three Modes Controlled DFIG based Wind Turbine

This paper deals with three novel Energy Management Strategies (EMS) for a Grid-Connected Hybrid Renewable Energy System (GCHRES) that utilizes a photovoltaic solar generator (PVG) and three modes controlled Wind Turbine system based on DFIG, along with a storage system based on battery. The CCP serves as the connection point between the Utility Grid (UG) and a residential AC load, primarily powered by the Renewable Energy Sources (RES). The UG acts as a backup source, and to limit the subscription power exceeding, the battery is designed to perform the peak shaving. Given the high vulnerability of batteries, the primary goal of all proposed EMSs is to maintain a continuous power supply while also protecting the battery from overcharging and deep discharge. Additionally, these EMSs are designed to lower the monthly energy bill for UG customers. The specific features of these EMSs vary depending on the metering types. And to maintain balance within the system, All components powers are controlled. The performances of the GCHRES were evaluated using simulation in MATLAB/SIMULINK environment. Results concerning the continuous ability to meet demand, stability of the system, tracking of references, and also wind turbine system control are discussed in this article. Keywords—Control and regulation, DFIG, Energy Management Strategies, Grid-Connected, Peak shaving, Photovoltaic,Pitch control, Renewable Energy, Wind Turbine

Grid-connected hybrid renewable energy systems for supermarkets with electric vehicle charging platforms: Optimization and sensitivity analyses

Coupling energy and transport sectors is critical for optimum utilization of renewable energy. The present work proposes a grid-connected photovoltaic/wind/battery hybrid power system to generate electricity for supermarkets. The supermarkets are located at three geographically distinct cities in Morocco and integrate electric vehicle (EV) charging stations in their parking areas. HOMER grid software is used for the optimal design of the proposed hybrid renewable energy system (HRES) with an accurate utility tariff corresponding to the Moroccan scenario. Dakhla, which is a high windy site, is found to be the best implementation site with maximum renewable energy fraction (REF), minimum COE and operating costs of 71.66%, 0.0841 $/kWh, and 0.124 M$/year, respectively. The optimal grid-connected system consisted of 107 kW p of PV, 300 kW of wind, 12 batteries, and 65 kW capacity inverter for Dakhla site. The next identified best site is Casablanca while Fez remained at third place based on COE and annual operating costs. At all of these sites, the EV charging process is achieved, almost completely, with 7300 charging sessions annually. A series of sensitivity analyses is performed based on supermarket energy intensity, renewable energy availability, and carbon pricing and impact on the viability of HRES was evidenced.

Techno-Economic Comparative Analysis of Grid-Connected and Islanded Hybrid Renewable Energy Systems in 7 Climate Regions, Turkey

The aim of this study is to evaluate the economic, technical, and environmental performances of grid-tied and stand-alone hybrid renewable energy systems (HRESs) in 21 provinces in seven regions of Turkey, considering different regional solar radiation and wind speed diversity. HRES were designed and modeled using the Hybrid Optimization of Multiple Energy Resources software (HOMER PRO) to meet the daily load of 13.26 kWh/day of a household. The analysis results for each province were compared considering the cost of energy, net present cost (NPC), greenhouse gas emissions, renewable fraction (RF), and optimum system configuration. The findings demonstrated that the optimal system configurations are Grid/PV/WT and PV/WT/DG/BESS for grid-tied and stand-alone HRES, respectively. The value of NPC ranges from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\$ $ </tex-math></inline-formula> 2,540.00 to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\$ $ </tex-math></inline-formula> 8,951.00 for grid-tied HRES, while it varies from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\$ $ </tex-math></inline-formula> 23,372.00 to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\$ $ </tex-math></inline-formula> 40,858.00 for stand-alone HRES. The provinces of Çanakkale in the Marmara Region and Artvin in the Black Sea Coast Region have the lowest and highest NPC values, respectively, for all systems. The PV capital cost, WT capital cost, BESS capital cost, solar radiation, and wind speed are considered as sensitivity input parameters that might affect the economic output of the HRES in this study. According to the sensitivity analysis, the NPC value as an economic indicator input decreased for both on-grid and off-grid HRES as the wind speed and solar radiation increased. It was also found that when the capital cost of PV panels and WT were changed, the NPC of the stand-alone HRES was in the range of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\$ $ </tex-math></inline-formula> 21,402.27- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\$ $ </tex-math></inline-formula> 29,978.89 for the province of Çanakkale, while it was in the range of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\$ $ </tex-math></inline-formula> 37,518.11- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\$ $ </tex-math></inline-formula> 51,939.00 for the province of Artvin. Moreover, when solar radiation and wind speed were increased, the results showed that NPC and CO2 emissions decreased by 9.30% and 9.23%, respectively, for Çanakkale, and by 25.58% and 66.95%, respectively, for Artvin. Finally, the results indicated that the optimal system configuration changes depending on the PV and WT capital cost variations for the grid-tied HRES. This research can be useful for planning grid-tied and stand-alone HRES from different aspects in Turkey, as well as other countries around the world. It contributes to the literature by comparing grid-tied and stand-alone HRES to determine the optimum system configuration and to find the best optimization results in seven regions of Turkey under different climate conditions. In addition, most of the studies related to HRES for residential areas in the literature are reviewed in this research, which intends to serve as a guide for engineers and researchers.

A Technical Analysis of a Grid-Connected Hybrid Renewable Energy System under Meteorological Constraints for a Timely Energy Management

A Technical Analysis of a Grid-Connected Hybrid Renewable Energy System under Meteorological Constraints for a Timely Energy Management

Grid connected hybrid renewable energy systems for urban households in Djibouti: An economic evaluation

The cost of electricity produced by thermal power plants in Republic of Djibouti is relatively high at about $0.32/kWh. This is due to its dependence on imported oil coupled with fluctuating oil prices. Consequently, the customer pays a high electricity bill. However, Djibouti is endowed with indigenous renewable energy resources such as a good solar irradiance of 5.92 kWh/ m2 day, a potential geothermal energy estimated up to 1000 MW, and few sites with annual wind speed higher than 6 m/s. The goal of this paper is, therefore, to assess an economic evaluation of different grid connected hybrid renewable energy systems to a residential urban house located in Tadjourah city (11.7913° N, 42.8796° E) in the North-Eastern part of Djibouti to reduce the cost of electricity from the grid. To reach this objective, a powerful software tool called HOMER (Hybrid Optimization Model for Electric Renewables) has been used to find the optimum hybrid energy system using real wind and solar irradiation data. The results obtained from this study show that the best economical suited combination of hybrid renewable energy system is a PV-Wind grid connected system. This study shows also that potentially the indigenous renewable energy contribution, in Tadjourah, can be as much as 77 % with 47 % of solar and 30% of Wind energy. The Net Present Cost, the Levelized Cost of Energy, and the operating cost of the optimal HRES are $337, $0.002/kWh and $1,025/year, respectively. When compared with the average cost of grid-only connection of $0.32/kWh, the optimal hybrid renewable energy system is more economical and will save 51 % of the cost that the customer must pay when using only the electricity from the grid.

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.