Energy System For Remote Area Research Articles

The improved aquila optimization approach for cost-effective design of hybrid renewable energy systems

The growing demand for renewable energy systems is driven by climate change concerns, government support, technological advancements, economic viability, and energy security. These factors combine to create a strong momentum towards a clean and sustainable energy future. Governments, governments, and individuals are increasingly aware of the environmental impacts of traditional energy sources and adopting renewable energy solutions. Hybrid Renewable Energy Systems (HRES) are developed as an effective way of meeting the energy demands in remote locations. The complexity of the system components and the fluctuation of renewable energy sources make it difficult to design an economical and effective HRES. In this study, the Improved Aquila Optimization (IAO) approach has been suggested as a powerful tool to optimize the HRES design. The study addresses the implementation of the IAO approach in the design of HRES and emphasizes its advantages over other optimization techniques. Through extensive simulations and analyses, our findings demonstrate the superior performance of the IAO algorithm in improving the efficiency and cost-effectiveness of HRES. The optimization process using IAO resulted in a significant reduction in overall system costs, achieving an estimated Net Present Cost (NPC) of $201,973. It translates to a cost reduction of 25% compared to conventional optimization techniques. Furthermore, our analysis reveals that the IAO approach enhances the utilization of renewable energy sources, leading to a 15% increase in overall energy generation efficiency. These results highlight the effectiveness of the IAO approach in addressing the challenges associated with designing HRES. By significantly reducing costs and improving efficiency, it facilitates the adoption of sustainable energy systems in remote areas. The outcomes of this study emphasize the importance of utilizing advanced optimization techniques, such as IAO, to ensure the economic viability and environmental sustainability of HRES.

A multi-approach framework for developing feasible, viable, and sustainable hybrid energy systems in remote areas: The case of Con Dao island in Vietnam

In remote communities, hybrid energy systems are increasingly used to improve the reliability and renewability of power supply. The techno-economic analysis is often used to develop these promising energy systems, ignoring some performance indicators and environmental factors. This study proposes a multi-approach framework for developing operationally feasible, economically viable, and environmentally sustainable hybrid energy systems in remote areas. A case study is conducted on Con Dao Island in Vietnam to supply its electricity demand using six on-grid and off-grid hybrid energy systems. After finding the best techno-economic configurations of the six developed systems, they are subjected to multi-approach analysis and exhaustive comparison using a set of performance, economic, and environmental indicators. An off-grid hybrid energy system comprising photovoltaics, wind turbines, lead-acid batteries, and diesel generators has the lowest net present cost (109.7 million USD) to supply the predicted island's electricity consumption (with a total on-site electricity generation of 184.1 GWh/yr). However, this off-grid system indicates the highest excess energy fraction (55%), while the on-grid systems with the ability to export excess energy to the grid have no excess energy fraction. In terms of eco-friendliness, an on-grid hybrid energy system consisting of a high level of photovoltaics and wind turbines shows the best results, with a negative total environmental impact and CO2-eq emissions. This on-grid system shows the best cost of energy (0.1 USD/kWh) with approximately 450% less total environmental impact than the best off-grid system investigated, offsetting about 48.2 kilotonnes of CO2-eq/yr by exporting net emission-free electricity. Overall, the proposed framework can assist decision-makers in finding feasible, viable, and sustainable hybrid energy systems.

Green and renewable resources: an assessment of sustainable energy solution for Far North Queensland, Australia

Remote communities, which do not have a connection to the national grid in Far North Queensland (FNQ), depend on dirty and costly diesel generators to meet their energy demands. The cost of power generation is considerable in those areas, because the diesel fuel must be carried by truck or ship and a fuel reserve must be held on-site in case of expected demand or weather closure. Moreover, Australia has an energy security issue in relation to liquid fuels. Australia is reliant on imported fuel such as diesel to fill the shortage, as domestic production and supply are unable to fulfil domestic demand. As a result, by deploying hybrid integrated renewable energy systems in remote areas, isolated communities may lower their power prices, enjoy a more secure and dependable source of electricity and minimise their carbon footprint by eliminating or reducing the usage of diesel. In this study, an extensive literature review has been conducted focussing on renewable resources for Australia and Far North Queensland, different hybrid energy systems including energy storage, and finally highlights the alternative clean and renewable energy options for Far North Queensland (FNQ) remote communities. In addition, this study has performed an assessment of renewable energy available from solar and wind resources considering climatic, geographical and economic aspects for FNQ. The literature review and the assessment show that solar and wind resources including hydrogen storage have significant potential for energy solution of FNQ. The assessment results indicate that selected regions of FNQ have suitable land area of 142,294.86 km2 (55.94% of total selected areas) for solar and 144,563.80 km2 (56.83% of total selected areas) for wind. The total calculated potential power can be 14,448 GW from solar PV and 1040.97 GW from wind energy. This study provides a significant pathway for parties interested in investing in renewable energy in FNQ. Moreover, knowing a land’s suitability will increase confidence and hence speed up the renewable energy investment.

Multicriteria assessment of biomass gasification‐based hybrid energy systems in remote areas

AbstractThis study proposes an approach to multicriteria assessment of biomass gasification‐based hybrid energy systems in remote areas using the modified SMARTS method. This approach involves comparing two groups of hybrid energy systems: those based on biomass gasification and those based on diesel generation, which is already widely used in remote areas. The hybrid energy system configurations are developed using the HOMER software in terms of the maintenance schedule of biomass gasifiers. Alternatives are compared according to the criteria of economic, technical, environmental and social efficiency. The proposed modification of the SMARTS method uses both crisp and interval weights of criteria and criteria estimates for decision making under uncertainty of the preferences and input data, especially in terms of initial capital and operating costs, feedstock and diesel fuel prices. The final choice of a hybrid energy system is based on the relative dominance indicator. Two case studies of isolated rural settlements show that biomass gasifiers when supplemented with diesel generation and other renewable energy sources are the best sustainable solution as compared with other feasible alternatives. These conclusions are robust to sufficiently significant changes in preferences and input data. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd.

Optimum sizing and simulation of hybrid renewable energy system for remote area

In current scenario, people tend to move towards outskirts and like to settle in places that are close to nature. But, due to urban lifestyle and to fulfill the basic needs, demand of electricity remains the same as in urban areas. This demand of electricity can be only fulfilled by using hybrid renewable energy resources, which is easily available in outskirts. Renewable energy resources are unreliable and more expensive. Researchers are working to make, it more reliable and economic in terms of utilization. This article proposes a metaheuristic grasshopper optimization algorithm (GOA) for the optimal sizing of hybrid PV/wind/battery energy system located in remote areas. The proposed algorithm finds the optimal sizing and configuration of remote village load demand that includes house electricity and agriculture. The optimization problem is solved by minimization of total system cost at a desirable level of loss of power supply’s reliability index (LPSRI). The results of GOA are compared with particle swarm optimization (PSO), genetic algorithm (GA) and hybrid optimization of multiple energy resources (HOMER) software. In addition, results are also validated by modeling and simulation of the hybrid energy system and its configurations at different weather conditions-based results. Hybrid PV/wind/battery is found as an optimal system at remote areas and sizing are[Formula: see text] with cost of energy (COE) (0.3473$/kWh) and loss of power supplies reliability index (LPSRI) (0%). It is clear from the results that GOA based methods are more efficient for selection of optimal energy system configuration as compared to others algorithms.

Bi-level multi-objective optimization of design and subsidies for standalone hybrid renewable energy systems: A novel approach based on artificial neural network

Hybrid renewable energy systems (HRESs) draw considerable research interest because of their potential to reduce fuel consumption and greenhouse gas emissions. These factors limit the utilization of conventional energy systems in remote areas. To establish an equilibrium between the government and residents that achieves the lowest environment impacts and highest economic benefits of standalone HRESs, this study proposes a bi-level multi-objective optimization that simultaneously performs subsidy policy making at the upper level and energy system design at the lower level. A novel artificial neural network-based hybrid algorithm (ABHA) is developed to surrogate the optimization problem at the lower level to transform the bi-level optimization problem into a single level problem, so as to increase the calculation efficiency. The results indicate that (i) ABHA can achieve good accuracy, and significantly save the calculation time when compared with a conventional method. (ii) Under the optimal subsidy policy, most of the energy demands can be satisfied by solar energy in the proposed standalone HRES. (iii) Increasing subsidies would increase the scale of Photovoltaic array and decrease the carbon emission; however, the design and operation of the HRES would not be further impacted if the subsidy goes beyond a certain limit.

Optimal Design and Practical Implementation of Hybrid Renewable Energy Systems in Remote Areas: Case Study

Optimal Design and Practical Implementation of Hybrid Renewable Energy Systems in Remote Areas: Case Study

Optimum Implementation Renewable Energy Systems in Remote Areas

The growth in energy consumption and the lack of access to the electricity network in remote areas, rising fossil fuel prices, the importance of using renewable energy in these areas is increasing. The integration of these resources to provide local loads has introduced a concept called microgrid. Optimal utilization of renewable energy systems is one of their most important issues. Due to the high price of equipment such as wind turbine, solar panels and batteries, capacity sizing of the equipment is vital. In this paper, presents an algorithm based on techno-economic for assessment optimum design of a renewable energy system including photovoltaic system, batteries and wind turbine is presented.

Techno-economic optimization analysis of stand-alone renewable energy system for remote areas

Hybrid renewable energy systems (HRES) are becoming popular as stand-alone power systems for providing electricity in remote areas due to the advancement in renewable energy technologies and subsequent rise in the prices of conventional fuels. A hybrid energy system, or hybrid power, usually consists of two or more renewable energy sources used together to provide increased system efficiency as well as greater balance in energy supply. Therefore, this paper aims at the design optimization of the hybrid renewable energy systems to meet the specific daily residential load profile for remote areas. The optimization problem regarding the design of a hybrid renewable energy system has been solved using Homer Pro Software depending on demand-side management during peak and off-peak hours. Four cases are used to evaluate the performance of the proposed design scheme. The simulation results have shown that the proposed design scheme is suitable for remote areas in comparison to the earlier proposed systems depicted in four cases. In addition, a properly planned hybrid system with demand-side management will reduce the overall system cost and increase the system efficiency by reducing carbon emissions, balancing power system by managing overloading and reduction in load shedding as well as less complex design and easy implementation in remote areas.

Optimum design of hybrid wind/PV energy system for remote area

Abstract The current paper introduces a realistic solution for energy demand in Makadi Bay, Red-Sea, Hurgada, Egypt using energy system crossbred of Renewable Wind Energy System (WES) and Photovoltaic System (PVS) in the presence of Battery Energy Storage (BES). A real measurement for wind speed was recorded through a year of 2017. Also, the sun irradiance and temperature were recorded through the same period, to be considered for the output power calculations from the proposed crossbred renewable energy system. The demand load data for the city was recoded as well as through the same period for evaluating the feasibility of the system if it can cover the city loads. Linear TORSCHE optimization technique has utilized to reach an optimum solution of the proposed crossbred renewable energy system. Individual configuration of PVS & WES in presence of BES have been studied and compared with the hybrid PV/WT. Furthermore, economic analysis has presented to prove the best economical system. The obtained results show that installing such hybrid system consists of WES, PVS and BES is cheaper than installing each one individually.

Optimal Battery Bank Dimensioning Algorithm for Renewable Systems Electrification of Isolated Sites

The penetration of renewable energy systems in remote areas contributes to reply to its accrued demand of electricity. Renewable energy systems as photovoltaic generation systems and wind generation systems are characterized by their unpredictable and intermittent character presenting the main drawback of these systems. Although this advantage, the problems caused by the intermittency of these systems can be resolved by employing a battery energy storage system. To this end this paper proposes and analyses an efficient and optimal methodology dedicated to applications fed by renewable energy systems. Since an optimal energy storage bank sizing is needed in order to assure the continuity and reliability of electricity supply of remote areas from these kinds of energy sources. The first part of this article describes the renewable hybrid system structure and different factors influencing the storage system dimensioning. Different scenarios of renewable sources power generations in order to develop an optimal battery bank sizing algorithm are investigated the second part of this article. The formulation of the algorithm is finally presented and discussed.

Original Framework for Optimizing Hybrid Energy Supply

This paper proposes an original framework for optimizing hybrid energy systems. The recent growth of hybrid energy systems in remote areas across the world added to the increasing cost of renewable energy has triggered the inevitable development of hybrid energy systems. Hybrid energy systems always pose a problem of optimization of cost which has been approached with different perspectives in the recent past. This paper proposes a framework to guide the techniques of optimizing hybrid energy systems in general. The proposed framework comprises four stages including identification of input variables for energy generation, establishment of models of energy generation by individual sources, development of artificial intelligence, and finally summation of selected sources. A case study of a solar, wind, and hydro hybrid system was undertaken with a linear programming approach. Substantial results were obtained with regard to how load requests were constantly satisfied while minimizing the cost of electricity. The developed framework gained its originality from the fact that it has included models of individual sources of energy that even make the optimization problem more complex. This paper also has impacts on the development of policies which will encourage the integration and development of renewable energies.

Techno-economic optimization based approach for energy management of a stand-alone integrated renewable energy system for remote areas of India

In recent years, sustainability receives greater attention due to increasing demands and limited resources worldwide. The Indian state of Uttarakhand is rich in the availability of renewable energy resources such as solar, micro hydro, biomass, wind etc. Optimum utilization of these resources in stand-alone mode has been recognized as an economical and efficient option compared to grid extension for electrification of remotely located rural households. This paper presents a combined techno-economic optimization and energy management of a stand-alone solar-micro hydro-biomass-wind based IRES (Integrated Renewable Energy System) to meet the electrical energy demand of cluster of village hamlets of Uttarakhand state. A load shifting based DSM (demand side management) strategy has been suggested in the paper for energy management of the considered IRES. Further, optimization results without and with DSM strategy have been presented and compared. Finally, a sensitivity analysis has also been performed to evaluate the impact of different parameters on the considered system.

Advanced photovoltaic/hydro hybrid renewable energy system for remote areas

This paper presents modeling and simulation of the advanced photovoltaic (PV)/hydro based Hybrid Renewable Energy System (HRES) to electrify such isolated/remote areas, where grid accessibility is not possible. For 7.5 kW hydro generation system, a Self Excited Induction Generator (SEIG) with improved technique is used to optimize the utilization of hydro power. To achieve this aim, an uncontrolled bridge rectifier coupled with Hydro side Voltage Source Inverter is implemented for the SEIG based advanced hydro system. The PV system is configured by PV array, battery, DC/DC converter, maximum power point tracking controller, and PV side Voltage Source Inverter. A Constant Current Control scheme is developed in this paper to control active and reactive power flow and to synchronize hydro and PV systems. The proposed system uses fewer controlled switches, hence complexity of control has been reduced and system has higher efficiency and lower switching losses. The performance analysis of the HRES has been done to authenticate the existence of the system using the MATLAB software and results demonstrate that power quality of the proposed system is better and HRES is able to put into services.

Case study: Simulation and optimization of photovoltaic-wind-battery hybrid energy system in Taleghan-Iran using homer software

In respect to increasing demand for energy in the world and limited fossil fuel resources, there is a great need for using renewable energies (REs). One of the most attractive applications of RE technology is the application of hybrid energy systems in remote areas. An alternative to overcoming the intermittence of RE sources, such as the sun and wind (are freely available and environmental friendly), is to develop the hybrid energy system where excess electrical energy could be converted and stored. These sources combined with energy storage would provide a better system reliability making it suitable for stand-alone applications. They have been integrated and worked at the Taleghan renewable energies site in Iran. The National Renewable Energy Laboratory's hybrid optimization model for electric renewables simulation software has been used to carry out the optimal design and techno-economic viability of energy system in this study. The simulation results demonstrate that for hybrid energy system is consists of 0.8 kW PV modules, two wind turbines (0.4 kW each), 2.5 kW inverter, and 8 batteries (200 Ah and 12 V). The cost of energy is 1.655 US$/kWh, whereas the initial capital required, and net present costs are, 22998 US$ and 24623 US$, respectively.

Renewable energy systems for remote areas in Australia

It has been long thought that the northern and central regions of Australia are ideal places for the installation of remote area power supplies (RAPS) based on renewable energy. In particular the solar regime in these areas is among the highest in the world. The Centre of Appropriate Technology has been undertaking a project, as part of the Australian Cooperative Research Centre for Renewable Energy research program, to look at the viability of renewable energy systems in remote areas of northern and central Australia. The study has involved compiling a database of existing knowledge of renewables in these areas combined with a set of site visits and case studies to look at both community attitudes to renewable energy and the actual operation of the systems. The study started in early 1997 and is due to be completed towards the end of 1999. The present paper outlines the logistics of the study and some of the results. The emphasis so far has been on wind and solar systems (including hybrid diesel systems) in Aboriginal communities. Some work has progressed for systems in pastoral properties and tourist ventures. The fieldwork to date has covered northern South Australia and the Northern Territory. Further fieldwork will occur in northern Queensland and Western Australia in mid 1999.

Utilization of meteosat satellite-derived radiation data for integration of autonomous photovoltaic solar energy systems in remote areas

Due to the importance of the relief of Corsica, striking contrasts occur and turn a coastal Mediterranean climate on the littoral into an alpine one in the high mountains. Firstly, we demonstrate, computing a spatial correlogram, that for such countries it is not possible to deduce the solar irradiation received on any part of the island from the meteorological network. Consequently, satellites offer a good alternative for determining these solar data. We demonstrate a good accordance between daily solar irradiation values estimated from Meteosat satellite data and measured data on the considered sites. From the previous data of daily horizontal total irradiations, hourly total irradiations on tilted planes have been computed. These data have been used in an optimal sizing method of PV system, easily applicable to any site. So, for each site on the island of Corsica, we can determine the best adapted PV system, and we analyse differences between sizing characteristics according to the site of installation. Lastly, we have shown very good accordance between sizing results calculated, on the one hand, from measured irradiation hourly data and, on the other hand, from daily satellite images.

98/00475 Utilization of Meteosat satellite-derived radiation data for integration of autonomous photovoltaic solar energy systems in remote areas

98/00475 Utilization of Meteosat satellite-derived radiation data for integration of autonomous photovoltaic solar energy systems in remote areas