Cost Of Renewable Energy Systems Research Articles

Assessing the economic viability of renewable energy systems in agriculture: a comprehensive review

The economics of renewable energy sources are very important factors to encourage its use in the short and long run. The most important economic factor is associated with the initial investment cost of renewable energy systems. Despite their significance, operational costs do not primarily drive the decision to adopt specific renewable energy systems. The objective of this review is to investigate the economics of renewable energy systems in the agricultural sector concerning the initiative investment cost, the operational cost, and the economic returns of these systems. The results showed that the initiative investment cost in the solar energy systems was the cheapest compared to the systems. This fact contributed to the high distribution of these systems in agricultural activities. The operational cost of the other systems including the wind, geothermal, and bioenergy systems were lower than the solar energy system, but still, their use in agricultural activities was for specific purposes. The economic returns of various renewable energy systems depend on their intended use and the nature of agricultural activities.

Optimal management strategies of renewable energy systems with hyperexponential service provisioning: an economic investigation

The current research proposes optimal management strategies for queueing modeling-based renewable energy systems with hyper-exponentially distributed maintenance/repair under the assumption of an admission control policy. Using the concept and steps of the matrix-analytical method, the steady-state probability distribution associated with energy systems is explicitly presented. A relatively straightforward computation that can help with modeling wind energy generation, investigating wind farm performance, optimizing energy based on system storage, reliability inspection, service maintenance planning, and numerous other purposes can be employed to mathematically derive several system performance indicators. The investigation findings are validated via quantitative outcomes, illustrative possesses, and a step-by-step recursive methodology for efficient management of the renewable energy system. Additionally, considering multiple governing parameter values, the nature-inspired optimization technique, Cuckoo Search (CS), is employed to demonstrate the optimum anticipated cost of renewable energy system. A comparison with other metaheuristics and semi-classical approaches is also presented to establish the best convergence results. In order to help system designers, policymakers, engineers, and researchers, several numerical examples are also provided to construct more practical strategies based on the production of energy, storage, and system management. The economic, parametric, and performance investigation findings are highlighted, and the opportunities and recommendations for further research are provided. In a nutshell, the outcomes of the present analysis can be adopted to formulate the most effective economic strategies and regulate decision-making processes in the energy sectors.

Future nuclear fission reactors – uncertainties, the effect of parameter choice and an application to small modular reactor concepts

Abstract. Today, steep declines in the generation costs of renewable energy systems, particularly solar photovoltaic and wind, combined with a recent spur in storage and flexible technologies mainly driven by batteries and renewable-energy-generated hydrogen are driving a paradigm shift in energy systems across the world, and renewable energy dominates investments in installed electricity generation systems (Ram et al., 2022). In contrast, in 2022 USD 4.8 billion (ca. 21 %) of the total spending in research and development expenditures by countries within the Organisation for Economic Co-operation and Development (OECD) was still spent on nuclear development alongside the current discussion in recent literature about the role of new nuclear developments in combating the recent energy crisis and climate change (Asuega et al., 2023; Ingersoll et.al., 2020; IEA, 2023). Since predicting future costs of technologies not yet developed is a complex exercise, we start this paper with a comparison of two different approaches from production theory and show that they have a theoretically equal structure (Steigerwald et al., 2023). This we then apply to estimate a range of potential production costs for 15 so-called small modular reactor (SMR) concepts for which sufficient data are available. These include light-water, high-temperature and fast reactors. In a third step, we apply the Monte Carlo method to benchmark the cost projections assumed by the manufacturers by varying production parameters in simulations of the net present value (NPV) and the levelized cost of electricity (LCOE). Besides this, we test whether the differences between the manufacturer estimates and ours differ between technology families of SMR concepts and apply a sensitivity analysis. This contributes to an intensifying debate in the literature on the economics and finance of SMR concepts (Steigerwald et al., 2023). In a final step we compared our results with current costs of renewable energy technologies and could conclude that none of the tested concepts is able to compete economically with existing renewable technologies, not even when taking their variability and necessary system integration costs into account. We conclude that any technology foresight has to take the case specifics into account as much as possible, including technological and institutional specifics; this also holds for SMR concepts.

Multi-objective optimization of a multi-story hotel's energy demand and investing the money saved in energy supply with solar energy production

This study presents a comprehensive proposal for multicriteria optimization of the energy requirement of a multi-story hotel structure, which benefits economically and environmentally. EnergyPlus has been exercised for simulation of a given hotel building and to analysis energy demand. Besides, to implement optimization of building parameters, “Non-dominated Sorting Genetic Algorithm” (NSGA) was applied in JEPlus + EA software. Three building-related parameters have been investigated to optimize energy consumption after sensitivity analysis calculations: building orientation, overhang tilt angle, and overhang depth. Multi-objective optimization has been applied, considering three objectives with equal weight allocated to each factor. These criteria include the energy consumption of heating, cooling, and electrical equipment. The results of multi-objective optimization in the climatic zone of Tehran, show that the total energy demand is reduced by about 118 GJ annually. Furthermore, the long-time saved cost as a result of the optimization is proposed to be invested in the photovoltaic solar system's installation to make the building more sustainable. According to the result derived from Homer Pro software, 2.39 % of the hotel's annual energy consumption will be provided from clean energy. Despite the high cost of renewable energy systems, the costs related to producing electricity reduced significantly.

Size optimization of a stand‐alone hybrid photovoltaic/wind/battery renewable energy system using a heuristic optimization algorithm

Today, it has become imperative to design these systems at optimum size to make reliable and minimize the total costs of renewable energy systems. There are many studies about size optimization in the literature. However, few studies have approached the problem with a heuristic method at different levels of reliability and compared the results with commercial software. This paper aims to fill this gap by proposing an artificial bee colony (ABC) algorithm with different reliability ratios for renewable energy systems size optimization and comparing the results of the proposed method with the results of the HOMER Pro software. The current methodology is validated with a real case study on the load demand of a school building (latitude 41.37, longitude 27.3) in Turkey. The peak and average load per day for the school building are 7.4 kW and 51.8 kW, respectively. The proposed method has presented 14.71%, 14.36%, and 6.23%, respectively, more economical solutions than HOMER Pro software for hybrid photovoltaic (PV)/wind/battery, PV/battery, and wind/battery renewable energy system scenarios. In addition, the ABC algorithms with different reliability ratios (%0, %0.2, %1, and %3) are used to analyze the effect on the system cost of the loss of power supply probability. According to the results, the hybrid renewable energy system consisting of 230 PV panels, 6 wind turbines, and 34 batteries is the most economical option with a total annual cost of $42 717.58 compared to stand-alone systems with a reliability %0 ratio. It has been seen that increasing the loss of power supply probability reduces system costs. Consequently, this study shows that using the ABC algorithm in size optimization of renewable energy systems yields accelerates the decision-making process and more optimized solutions.

Design and Optimization of Integrated Distributed Energy Systems for Off-Grid Buildings

Abstract Off-grid concepts for homes and buildings have been a fast-growing trend worldwide in the last few years because of the rapidly dropping cost of renewable energy systems and their self-sufficient nature. Off-grid homes/buildings can be enabled with various energy generation and storage technologies; however, design optimization and integration issues have not been explored sufficiently. This paper applies a multi-objective genetic algorithm (MOGA) optimization to obtain an optimal design of integrated distributed energy systems for off-grid homes in various climate regions. Distributed energy systems consisting of renewable and nonrenewable power generation technologies with energy storage are used to enable off-grid homes/buildings and meet required building electricity demands. In this study, the building types under investigation are residential homes. Multiple distributed energy resources are considered such as combined heat and power (CHP) systems, solar photovoltaic (PV), solar thermal collector (STC), wind turbine (WT), as well as battery energy storage (BES) and thermal energy storage (TES). Among those technologies, CHP, PV, and WT are used to generate electricity, which satisfies the building’s electric load, including electricity consumed for space heating and cooling. Solar thermal energy and waste heat recovered from CHP are used to partly supply the building’s thermal load. Excess electricity and thermal energy can be stored in the BES and TES for later use. The MOGA is applied to determine the best combination of distributed energy resources (DERs) and each component’s size to reduce the system cost and carbon dioxide emission for different locations. Results show that the proposed optimization method can be effectively and widely applied to design integrated distributed energy systems for off-grid homes resulting in an optimal design and operation based on a trade-off between economic and environmental performance.

Deep decarbonization and the supergrid – Prospects for electricity transmission between Europe and China

Long distance transmission within continents has been shown to be one of the most effective variation management strategies to reduce the cost of renewable energy systems. In this paper, we test whether the system cost further decreases when transmission is extended to intercontinental connections. We analyze a Eurasian interconnection between China, Mid-Asia and Europe, using a capacity expansion model with hourly time resolution. Our modelling results suggestthat a supergrid option decreases total system cost by a maximum of 5%, compared to continental grid integration. The maximum cost reductionis achieved when (i) the generation is constrained to be made up almost entirely by renewables, (ii) the land available for VRE farms is relatively limited and the demand is relatively high and (iii) the cost for solar PV and storage is high. This is explained by that a super grid allows for harnessing of remote wind-, solar- and hydro resources demand centers. As for low-cost storage, it represents a competing variation management option, and may substitute part of the role of the supergrid, which is to manage variations through long-distance trade. We conclude that the benefits of a supergrid from a techno-economic perspective are in most cases negligible, or modest at best.

Renewable hybrid energy systems using geothermal energy: hybrid solar thermal–geothermal power plant

Abstract New and innovative solutions are being developed to overcome the challenges of detrimental effects that the traditional energy systems cause. This means that sustainable methods are implemented to do so, noting that when such developments are taken into consideration and are studied, this leads to a significant drop in the cost of renewable energy systems. In this work, a hybrid system consisting of a single flash steam geothermal power plant and a solar thermal system using a parabolic trough collector (PTC) is studied. Based on the available works in literature, the required design materials and modeling equations are chosen and discussed. The heat transfer fluid (HTF) as water is chosen as the working fluid for the PTC due to its low cost and high specific heat capacity. The calculations are carried out for the PTC on a specific day, time and location, and the simulations for the geothermal power plant (GPP) are carried out using System Advisor Model (SAM) software, assuming a specific increase in the temperature of the geofluid due to the additional heat transfer from the HTF of the PTC. The power plant output is 20 MW powered by four production wells. The results show that the energy production is ~15 GWh in January, which is the highest during the year due to the required energy demand for electricity consumption and district heating. Moreover, a mini review of the mathematical modeling of PTC and single flash geothermal power plant is presented.

Cost minimization for fully renewable electricity systems: A Mauritius case study

Climate change is the world's most prominent environmental problem, and fossil-fuel combustion is its primary cause. To set carbon reduction goals, policy makers require information on feasibility and cost of renewable energy systems. In this study, we describe an economic approach to modeling a national electricity system based entirely on renewable sources, using the island-nation of Mauritius as a case study.Many renewable electricity studies consider levelized costs of electricity (LCOE), which represents average cost of electricity, but cost minimization requires equalizing marginal costs. With variable sources, marginal costs change over time. Minimizing cost thus requires a model incorporating variability at high time resolution (daily or hourly), with the objective of minimizing the levelized cost of electricity for an entire electricity system (LCOES).In Mauritius, the minimum-cost renewable electricity portfolio includes roughly equal proportions of solar, wind, and biomass electricity, along with electricity storage. Policy issues include setting renewable energy targets, selecting policy instruments to incentivize optimum renewable energy portfolios, incorporating energy efficiency, determining appropriate discount rates, ensuring land availability, and accounting for non-cost considerations. Many of the economic and policy issues identified apply universally, and methods demonstrated in this study could be used anywhere in the world.

Design of a reward-penalty cost for the promotion of net-zero energy buildings

The investment cost of renewable energy systems for achieving net-zero energy buildings (ZEB/NZEB) is a vital factor concerned by most building owners, which raises a requirement for a new financial scheme specifically designed considering the level of ZEB. This study thus focuses on the design of reward-penalty mechanism for promoting the target of net-zero energy balance in each building design, enabling that a cost-effective design option for buildings where high integration of renewable energy systems can be expected. The benefits for building owners are formulated into three scenarios (S0, S1, and S2), in which the effectiveness of the proposed three functions were investigated. The results show that a higher cost is required by a lower level of ZEB whilst considerable bonuses can be realized by owners opting for higher levels of ZEB. In addition, the boundary of building energy consumption level as well as zero energy level is identified and provided for the proposed three reward-penalty functions. Based on the case study, the proposed reward-penalty functions were verified to be effective for a building energy consumption level between 0.8 and 2.0, with an error index lower than 7.0%. This study can provide an efficient yet effective approach for developing a financial scheme to further boost zero energy buildings.

Performance investigation of an advanced hybrid renewable energy system in indonesia

The vast percentage of people of the world; particularly in the developing countries; are living mostly in the decentralized, rural and remote areas those are geographically secluded from the grid connection. Power distribution and continuous fuel transportation to produce the electrical energy for these areas pretenses a great challenge. Using renewable energy resources in off grid hybrid energy system might be a solution of this problem. Moreover, high cost of renewable energy systems has led to its slow adoption in many countries. Hence, it is vital to select an appropriate size of the system in order to reduce the cost and excess energy produced as well as to maximize the available resources. A hybrid energy system has been designed as well as simulated to support a small community considering an average load demand of 80 kWh/d with a peak load of 8.1 kW. The simulation and optimization of operations of the system have been done by HOMER software using the real time field data of solar radiation and average wind speed data of that area. The simulation ensures that the system is suitably feasible with respect to net present cost and CO2 emission reduction purpose. The result shows that NPC and CO2 emission can be reduced about 29.65% and 16 tons per year respectively compared with the conventional power plants. The NPC of the optimized system has been found about USD 160,626.00 having the per unit Cost of Energy about USD 0.431/kWh. The analyzed hybrid energy system might be applicable for other region of the world where the climate conditions are similar. © 2017 American Institute of Chemical Engineers Environ Prog, 37: 1424–1432, 2018

Optimized Hybrid Wind-Diesel Energy System with Feasibility Analysis

The enormous percentage of people in the world; particularly in the developing countries; are living mostly in decentralized, rural and remote areas, those are geographically secluded from the main grid connection. The power distribution and continuous fuel transportation to generate electricity for these areas pretenses a very big challenge. By proper utilization of renewable energy resources in off grid hybrid energy systems will be an efficient solution of this crisis. Moreover, the high cost of renewable energy systems has led to its slow adoption in many developing countries. Hence, it is very important to find an appropriate size of system in order to reduce the energy cost and excess electricity generation as well as to maximize the available resources. Therefore, a hybrid energy system has been designed and simulated to support a small community considering an average load demand of 85 kWh/d with a peak load of 8.7 kW. The simulation and optimization of the system have been performed by the HOMER software using real time field data of solar radiation, wind speed and biomass of that particular area. The simulation results confirm that the system is suitably feasible with respect to the net present cost (NPC) and CO2 emission reduction purpose. The simulation results also confirm that the NPC and CO2 emission can be reduced about 32.45% and 29 tons per year respectively compared to the conventional power plants. The NPC of the optimized system has been found about USD $160,626 having per unit Cost of Energy (COE) about USD $0.431/kWh and the operating cost USD $10,779/yr.

Techno-economic Analysis of a Smart-grid Hybrid Renewable Energy System for Brisbane of Australia

Abstract The immense percentages of people of the world are living mostly in the decentralized, rural and remote areas those are geographically secluded from the grid connection. Power distribution and continuous fuel transportation to produce the electrical energy for these areas pretences a great challenge. A smart-grid hybrid energy system has been designed and simulated to support a small community considering an average load demand of 34 kWh/d and peak load of 4.6 kW. The total simulation and optimization process of the hybrid energy system have been done by HOMER Software with the meteorological data. The simulation results ensure that the proposed system is economically and environmentally feasible. The results show that Net Present Cost (NPC) and CO2 emission can be reduced about 29.65% per year compared to the conventional power plants. The NPC of the optimized system has been found about US$ 33,310.00 having the Cost of Energy (COE) about US$ 0.209/kWh. This analysed hybrid system will be applicable for similar meteorological and environmental conditions. This analysed hybrid system will be applicable for similar meteorological and environmental conditions. The urban area, including the central business district, are partially elevated by spurs of the Herbert Taylor Range, such as the summit of Mount Coot-tha, reaching up to 300 meters (980 ft) and the smaller Enoggera Hill, Brisbane, Australia. Using renewable energy resources in off grid hybrid energy system might be a solution of this issue. Moreover, high cost of renewable energy systems has led to its slow adoption in many countries. Hence, it is vital to select an appropriate size of the system in order to reduce the cost and excess energy produced as well as to maximize the available resources. Reduction of some greenhouse gasses as well as reduction of per unit cost according to the market price are main contribution of this research. The analysed hybrid solar-wind-diesel renewable energy system will be the most feasible and environment friendly in comparison with other traditional or conventional energysources in terms of reliability and cost effectiveness.

동적 에너지 시뮬레이션을 이용한 시설원예용 에너지 공급시스템의 경제성 분석

Recently, the usage of renewable energy system has been recommended because of the energy saving and depletion of fossil fuel. Especially, ground source heat pump system(GSHP) has a high efficiency by using annual stable ground temperature. Also, wood pellet is low cost and a high calorific value compared to fossil fuel. However, only small number of farms have applied renewable energy system to horticultural facility because of a high initial costs and uncertainty of its cost efficiency. In this study, in order to analyze the feasibility for the horticulture, TRNSYS simulation based on the standard horticultural facility was conducted in different weather and covering material conditions. Then, comparative feasibility analysis of each energy supplying system was conducted. As a result, we have found out that a high initial cost of renewable energy system was recovered by the economics of the energy cost. Due to the energy cost reduction, the payback periods were 10-11 years in the case of GSHP and 4-6 years in the case of wood pellet boiler.

Bang for the Buck

This article focuses on the need to develop alternatives to fossil fuels for present-day and future energy systems. The direction of energy research ought to be toward material science that can extend the life and lower the cost of renewable energy systems, rather than toward highly theoretical analyses that have over-the-horizon payoffs. Additionally, the planning for a smooth transition from fossil based to sustainable energy must include a side-by-side analysis of the economics as well as the energy return on energy investment (EROI) of each potential system. The EROI analysis would ensure the long-term viability of the technology, and the commercial analysis would show how much the system will cost and, thereby, provide an estimate of the money required for the installation in the transition period. The transition from the oil- and coal-based economy to a sustainably based future is not expected to be easy; however, taking advantage of the low-hanging fruit of conservation and energy efficiency will make that transition easier and much less painful.

Optimization of Korean energy planning for sustainability considering uncertainties in learning rates and external factors

During the last few decades, energy planning has focused on meeting domestic demand at lower total costs. However, global warming and the shared recognition of it have transformed the problem of energy planning into a more complex task with a greater number of issues to be considered. Since the key issue is to reduce greenhouse effects, governments around the world have begun to make investments in renewable energy systems (e.g., hydro, wind, solar, and/or biomass power). The relatively high costs of renewable energy systems and the uncertain outlook of their rate of diffusion in the market make it difficult to heavily rely on them. The uncertain variations in production cost over time are especially challenging. To handle uncertainties, the concept of the learning rate was adopted in this study so as to compute the costs of energy systems in the future and Monte Carlo simulation was performed.The aim of this study was to optimize plans of conventional and prospective renewable energy systems with respect to production cost. The production cost included capital, fixed, variable, and external costs. For the case study, the energy situation in South Korea was used. The results of the case study where the proposed methodology was applied could provide useful insights economically and strategies of sustainable energy management for ambiguous environments.

Techno-economical optimization of hybrid pv/wind/battery system using Neuro-Fuzzy

High cost of renewable energy systems has led to its slow adoption in many countries. Hence, it is vital to select an appropriate size of the system in order to reduce the cost and excess energy produced as well as to maximize the available resources. The sizing of hybrid system must satisfy the LPSP (Loss of Power Supply Probability) which determines the ability of the system to meet the load requirements. Once the lowest configurations are determined, the cost of the system must then be taken into consideration to determine the system with the lowest cost. The optimization methodology proposed in this paper uses the ANFIS (Adaptive Neuro-Fuzzy Inference System) to model the PV and wind sources. The algorithm developed is compared to HOMER (Hybrid Optimization Model for Electric Renewables) and HOGA (Hybrid Optimization by Genetic Algorithms) software and the results demonstrate an accuracy of 96% for PV and wind. The optimized system is simulated in PSCAD/EMTDC and the results show that low excess energy is achieved. The optimized system is also able to supply power to the load without any renewable sources for a longer period, while conforming to the desired LPSP.

Renewable energy: a response to climate change

“We recognize the importance of renewable energy for sustainable development, diversification of energy supply, and preservation of the environment. We will ensure that renewable energy sources are adequately considered in our national plans and encourage others to do so as well. We encourage continuing research and investment in renewable energy technology, throughout the world”. Communique from the G8 Leaders’ Summit, Genoa, July 2001. The Third Assessment Report of the IPCC confirmed that the Earth’s climate is changing as a result of human activities, particularly from energy use, and that further change is inevitable. Natural ecosystems are already adapting to change, some are under threat, and it is evident that human health and habitats will be affected world-wide. Such climate changes could also affect the present supplies of renewable energy sources and the performance and reliability of the conversion technologies. This paper concentrates on the reduction of carbon dioxide emissions and the role that the global renewable energy industry might play in this regard. (The five other major greenhouse gases are given less emphasis here.) The paper compares the costs of renewable energy systems with fossil fuel-derived energy services and considers how placing a value on carbon emissions will help provide convergence. The move towards a de-carbonised world, driven partly by climate change science and partly by the business opportunities it offers, will need to occur sooner rather than later if an acceptable stabilisation level of atmospheric carbon dioxide is to be achieved. Government policy decisions made now will determine the sort of future world we wish our children to inherit. The renewable energy era has begun.