Availability Of Renewable Resources Research Articles

Forecasting the ecological footprint of G20 countries in the next 30 years

The Ecological Footprint evaluates the difference between the availability of renewable resources and the extent of human consumption of these resources. Over the past few decades, historical records have shown an accelerated decline in the availability of resources. Based on national footprint and biocapacity accounts, this analysis aims to advance the forecasting of the G20 countries' ecological footprints over a 30-year time frame. We employed a time series forecasting approach implemented in Python, which included-modular regression (Prophet) and Autoregressive Integrated Moving Average (ARIMA & Auto-ARIMA) methods. We evaluated and combined the performance of these three methods. The results indicated that among the largest economies of the G20, only four countries are projected to have a positive ecological footprint balance by 2050. These countries share the common denominator of large land areas and a moderate population growth projection. However, the overall trend of the indicator suggests that it will continue to decline.

Spatio-temporal distribution of renewable freshwater resources and their availability in Kosovo—an analysis from the Eastern Region

The study aims to analyze the availability of renewable freshwater resources and their spatiotemporal distribution in the Eastern Region of Kosovo (ERK). As a crucible resource for agricultural, industrial, and commercial activities, water scarcity will lead to water shortages. Kosovo is a landlocked country, and ERK is the most important region for industrial activities (coal, mines) and agricultural use (plains). Located in continental climate conditions, surrounded by middle to high-altitude mountains, the region does not have a favorable spatio-temporal distribution of freshwaters. The determination of the water resources is based on the amount of surface runoff, which being divided per capita, gives indications of the water resources of a region (catchment). For our aims, main river discharge and population statistics are used to analyze the spatiotemporal distribution and availability of renewable freshwater in ERK. Falkenmark Freshwater Indicator with 1.483 m³/capita/year shows that ERK lies under water scarcity, and existing water reservoirs offer low security for water withdrawals, and further reservoirs would prevent water scarcity in the region.

Optimizing energy solutions: A techno-economic analysis of solar-wind hybrid power generation in the coastal regions of Bangladesh

Hybrid renewable energy systems have acquired attention worldwide for their ability to harness multiple renewable sources parallelly like solar, wind, and hydropower, presenting numerous advantages. Bangladesh is forced to rely on the traditional fossil fuel-powered power generation infrastructure in order to meet the nation’s increasing need for electricity. The goal of this paper is to improve the percentage of renewable energy in Bangladesh’s energy landscape by addressing the technical, economic, and environmental elements of building a specialized hybrid system at Patenga Sea Beach through a methodical approach. This study is the first to pinpoint and address Patenga Sea Beach’s limits in light of Shah Amanat International Airport’s nearby location in Chittagong. In order to build the suggested system, a daily load demand of 1000 kWh and an annual peak demand of 53.57 kW were taken into account. The analysis shows that this system has a levelized cost of energy (LCOE) of 0.03$, generating 4,604.591 MWh of power annually. Findings from HOMER reveal an initial capital outlay of $350,688 for initial capital investment, with an annual O&M cost of $3,821, contributing to its cost-effectiveness. During the span of its lifetime, the hybrid system can also avoid 5,767 tons of CO2. The simulation program PVsyst has been utilized to assess the PV system-specific performance, viability, and outcomes. According to the PVsyst evaluation, the PV system has an 89 % system performance ratio, a 0.017$ levelized cost of energy, and a break-even period of only 6.6 years. The sensitivity analysis examines renewable resources, factoring in climate change’s effects on solar irradiation, wind speed, replacement cost, and operational expenses. It validates the hybrid system’s viability across various environmental scenarios, demonstrating resilience to changes in renewable resource costs and availability. The suggested hybrid system can be placedto minimize costs associated with energy generation, circumvent structural and geographic limitations, improve the Patenga Sea beach’s visual appeal, and lower greenhouse gas emissions. In addition to supporting future decisions about the deployment of hybrid systems, this research could assist in the integration of sustainable and renewable energy sources into the national grid.

How demand-side management can shape electricity generation capacity planning

Forward-looking strategies for Demand Side Management (DSM) can accelerate the clean energy transition and reduce carbon emissions if electricity load can be shaped to be better matched to the hourly availability of renewable resources. Time-varying rates are increasingly used to motivate load shifting, capitalizing on the increasing size of loads that can be easily shifted, such as electric vehicle charging and electric heat pumps. This study analyzes the hourly availability of current and renewable resources for two representative electricity grids in the USA. While many demand-management programs are currently designed to shift load to nighttime when demand is low, to use low-cost PV the opposite shift into daytime will be preferred. Given that investments in electricity generation capacity shape the grid for decades, generation capacity planning should proactively anticipate how DSM programs (and associated load shapes) will change as the generation mix changes. These future load shapes determine the optimal resources to be acquired and can be modified by DSM to facilitate variable renewable integration. Ongoing regulatory proceedings in Colorado are described as a case study for an existing decision-making process.

Optimal Operation and Market Integration of a Hybrid Farm with Green Hydrogen and Energy Storage: A Stochastic Approach Considering Wind and Electricity Price Uncertainties

In recent years, growing interest has emerged in investigating the integration of energy storage and green hydrogen production systems with renewable energy generators. These integrated systems address uncertainties related to renewable resource availability and electricity prices, mitigating profit loss caused by forecasting errors. This paper focuses on the operation of a hybrid farm (HF), combining an alkaline electrolyzer (AEL) and a battery energy storage system (BESS) with a wind turbine to form a comprehensive HF. The HF operates in both hydrogen and day-ahead electricity markets. A linear mathematical model is proposed to optimize energy management, considering electrolyzer operation at partial loads and accounting for degradation costs while maintaining a straightforward formulation for power system optimization. Day-ahead market scheduling and real-time operation are formulated as a progressive mixed-integer linear program (MILP), extended to address uncertainties in wind speed and electricity prices through a two-stage stochastic optimization model. A bootstrap sampling strategy is introduced to enhance the stochastic model’s performance using the same sampled data. Results demonstrate how the strategies outperform traditional Monte Carlo and deterministic approaches in handling uncertainties, increasing profits up to 4% per year. Additionally, a simulation framework has been developed for validating this approach and conducting different case studies.

Assessing the impact of renewable energy penetration and geographical allocation on transmission expansion cost: A comparative analysis of two large-scale systems

Ambitious renewable energy development plans require an efficient electricity grid connection of massive generation capacity. Significant transmission network investments are considered necessary to support the energy transition. This paper analyses the transmission grid reinforcement requirements of two large-scale electricity systems with notably different geographical distributions of renewable resource availability and load density. The results indicate that optimal transmission expansion accounts for less than 10% of total annualised system investment (generation capacity + transmission grid). This is true even in transmission systems with significant existing bottlenecks. The study includes a sensitivity analysis of the location of renewable energy source (RES) capacity. The sensitivities examine the impact of varying the concentration of RES in resource-rich areas, as well as the proportion of RES capacity connected at the distribution level. Both sensitivities are evaluated over a common base case scenario. The results show that a higher concentration of RES capacity in resource-rich network zones can more than double the optimal transmission expansion requirements. In contrast, the implementation of distributed generation (DG) leads to the allocation of generation closer to demand centres, resulting in transmission grid savings of up to 30%. These effects are more pronounced in networks where RES capacity is located further away from major demand centres. This is because existing bottlenecks are exacerbated by higher RES concentration and relieved as the share of DG increases.

Renewable green oil as a low-cost option for large-scale, long duration energy storage to produce on-demand electricity

<p class="MsoNormal" style="text-align: justify;"><span style="font-size: 14pt; font-family: 'times new roman', times, serif;">The rapid growth of renewable solar and wind energy necessitates extensive, long-term energy storage solutions to stabilize the electric grid and address the intermittent nature of these sources. In the absence of cost-effective long-duration, large-scale (LDLS) energy storage, there is a risk of increased disruptive blackouts and brownouts as intermittent energy sources approach 50% of electricity generation. Our analysis underscores volumetric energy density as a pivotal determinant in LDLS energy storage solutions, which is particularly crucial during periods of diminished renewable resource availability, such as the rainy season. Despite emphasis on conventional electric batteries and mechanical storage technologies such as compressed air and pumped hydro for LDLS, their costs pose a significant obstacle to widespread adoption, especially in emerging economies. In this study, we present a groundbreaking approach to LDLS: on-demand electricity generation from carbon-neutral renewable oil, known as "green oil," leveraging Reliance’s innovative catalytic hydrothermal liquefaction (R-CAT-HTL) technology. Our investigation evaluated two distinct sources of green oil production: organic waste streams (e.g., municipal solid waste, agricultural-waste, etc.) and on purpose production of algal biomass. We demonstrate that burning renewable green oil to produce electricity offers a cost-effective solution for large-scale (GWh) long-duration (many days) energy storage, ensuring the stability, reliability, and resiliency of the electric grid. We also demonstrate that minimum 14 days, ideally 30 days energy storage is needed for continuous uninterrupted service, especially critical for manufacturing facilities. Through a meticulous levelized cost of storage (LCOS) analysis comparing green oil with other LDLS technologies reported in literature, we demonstrate the cost effectiveness of green oil. In this model, green oil serves as stored energy, functions akin to a battery and is efficiently converted into electricity through conventional reciprocating engines or next-generation more efficient turbines. Our findings suggest that green oil derived from diverse organic sources is the most economically viable option for GWh-scale storage, particularly when storage requirements extend beyond a single day. This research thus presents a transformative cost-effective solution to the pressing challenge of LDLS energy storage, accelerating a sustainable and resilient energy future.</span></p>

Green retailer: A stochastic bi-level approach to support investment decisions in sustainable energy systems

This paper presents a bi-level approach to support retailers in making investment decisions in renewable-based systems to provide clean electricity. The proposed model captures the strategic nature of the problem and combines capacity sizing decisions for installed technologies with pricing decisions regarding the electricity tariffs to offer to a reference end-user, representative of a class of residential prosumers. The interaction between retailer and end-user is modeled using the Stackelberg game framework, with the former acting as a leader and the latter as follower. The reaction of the follower to the electricity tariff affects the retailer’s profit, which is calculated as the difference between the revenue generated from selling electricity and the total investment, operation and management costs. To account for uncertainty in wholesale electricity prices, renewable resource availability and electricity request, the upper-level problem is formulated as a two-stage stochastic programming model. First-stage decisions refer to the sizing of installed technologies and electricity tariffs, whereas second-stage decisions refer to the operation and management of the designed system. The model also incorporates a safety measure to control the average profit that can be achieved in a given percentage of worst-case situations, thus providing a contingency against unforeseen changes. At the lower level, the follower reacts to the offered tariffs by defining the procurement plan in terms of energy to purchase from the retailer or potential competitors, with the final aim of minimizing the expected value of the electricity bill. A tailored approach that exploits the specific problem structure is designed to solve the proposed formulation and extensively tested on a realistic case study. The numerical results demonstrate the efficiency of the proposed approach and validate the significance of explicitly dealing with the uncertainty and the importance of incorporating a safety measure.

Evaluation and deployment of a unified MPPT controller for hybrid Luo converter in combined PV and wind energy systems

AbstractThis work emphasizes the development and examination of a Hybrid Luo Converter integrated with a unified Maximum Power Point Tracking (MPPT) for both grid and independent hybrid systems. The primary objectives of this hybrid system are to efficiently harness power from intermittent and variable renewable sources while elevating low-voltage energy inputs to utility-grade levels. Unlike previous studies employing specific MPPT algorithms for solar and wind sources, this work aims to simplify the control system by utilizing a unified MPPT controller. This research also introduces a novel approach involving dual-lift hybrid Luo converters to create hybrid systems, operating exclusively or concurrently based on the availability of renewable resources. To maximize power generation from all renewable sources, a unified MPPT algorithm is developed. The hybrid system, incorporates 500 W wind and 560 W PV systems, the innovative Luo converter, and the unified MPPT controller. A comprehensive comparative analysis is presented, comparing the hybrid system's performance with that of traditional control algorithms, such as the Perturb & Observe, and Radial Basis Function Network controllers. The successful prototype of the converter validates the practicality of the proposed approach.

Selection of a sustainable location for waste electrical and electronic equipment recycling plant using Entropy and Evaluation based on Distance from Average Solution.

The production and consumption of electronic goods have experienced a significant increase over the years, leading to a substantial surge in the global volume of electronic waste, commonly referred to as Waste Electrical and Electronic Equipment (WEEE). The selection of a sustainable location for WEEE recycling plants plays a crucial role in mitigating environmental concerns, preserving resources and promoting economic development. It signifies a proactive and responsible approach to electronic waste management in the contemporary world. To tackle the challenge of selecting sustainable locations for WEEE recycling plants, this study employed the Entropy and Entropy and Evaluation based on Distance from Average Solution (EDAS) methodologies, evaluating 10 alternative cities in Turkey based on 13 criteria. The selected criteria include land cost, personnel cost, energy cost, availability of labour, government support degree, tax preferences, road network accessibility, number of electronic equipment producers, existence of recycling plants, suitability of land use, population and availability of renewable resources (wind power and solar energy). The Entropy method was employed to calculate the weights assigned to each criterion, whereas the EDAS method was utilized to evaluate the decision alternatives. The results provide region-specific recommendations, such as Antalya for the Mediterranean region and Samsun for the Black Sea region. The literature lacks sufficient research on the selection of sustainable locations for WEEE recycling plants. Furthermore, the utilization of real data enhances the study's credibility and provides practical insights for decision-making. The selection of a sustainable location for a WEEE recycling plant in Turkey not only demonstrates the country's environmental commitment but also sets a global example for responsible waste management.

A stochastic two-stage microgrid formation strategy for enhancing distribution network resilience against earthquake event incorporating distributed energy resources, parking lots and responsive loads

The sustainability of energy systems has been severely affected in recent years by the quantity and intensity of high-impact, low-probability events. As a result, the resilience concept has been introduced to analyze the operation of networks against such events. This paper proposes a stochastic two-stage microgrid formation formulation to maximize the restored loads and enhance the resilience index of electrical distribution systems in the face of earthquake events. In this regard, an earthquake incident is modeled in the first step utilizing geographical data, peak ground acceleration and fragility curves. Then, a two-stage linear programming and graph theory is applied to form microgrids in response to the mentioned disturbances, where the variables in the planning and operating states are optimized in the first and second stages, respectively. The influence of different components including diesel generators, renewable energies, storage units and electric vehicles is investigated. In addition, the role of responsive loads and uncertainties related to line failure, load variation, renewable resources availability and electric vehicles are considered during the analysis. The results for various scenarios validate that the presented approach increases load supply capability and resiliency index by 38.7% and 38.8%, respectively.

Neutrosophic Multi-Criteria Decision-Making Framework for Sustainable Evaluation of Power Production Systems in Renewable Energy Sources

To make the change to a cleaner, more sustainable energy future, it is essential that power production systems be evaluated sustainably. To estimate the overall sustainability performance of various power production systems, this evaluation takes into account a wide range of parameters. Impact on the environment, availability of renewable resources, resource efficiency, social and economic implications, economic feasibility, grid integration and dependability, technical maturity, and scalability are all taken into account. Stakeholders may make better judgments and give higher priority to power production systems that take into account environmental impacts, resource efficiency, social impacts, and economic viability by evaluating these factors. So, we used the multi-criteria decision-making (MCDM) approach VIKOR to assess the power production systems in the sustainability criteria. The VIKOR method is used to rank the several alternatives. We integrated the neutrosophic set with the VIKOR method to deal with inconsistent information. We used seven criteria and ten alternatives in this study. The development of a sustainable and resilient energy sector is aided by the sustainable evaluation of power production systems, which in turn helps to reduce the effects of climate change and safeguard the environment.

Offshore Wind Power Potential in Brazil: Complementarity and Synergies

Renewable sources stand out in energy planning due to their contribution to greenhouse gas emission reduction when displacing fossil fuels and the enhancement of energy security through the diversification of the energy matrix. Understanding and optimizing the complementary operative synergy between different energy sources over time and space leads to efficient policies. This article uses an hourly Pearson’s correlation coefficient to explore the complementarity between offshore wind and other power generation sources in the Brazilian matrix. An analysis of offshore wind power feasibility in the Brazilian power system will be conducted, considering environmental implications, synergies with the oil industry, costs, and complementarities with other energy sources. The methodology uses an optimization model to minimize costs and optimize the production mix while considering the time series of renewable energy, subject to demand constraints, renewable resource availability, reservoir storage, capacity limitations, and thermal generation. The study concludes that the northeast and southeast electrical subsystems must start offshore wind installation in Brazil due to their complementarity with hydropower production, synergy with the oil and gas industry, and proximity to the largest consumption spots.

A techno-economic assessment for fuel cells hybrid systems in stationary applications

ABSTRACT This study evaluates the techno-economic feasibility of integrating fuel cells into stand-alone power generation systems, combined with different technologies such as diesel generators, wind turbines, and batteries. An optimisation analysis was performed using the Hybrid Optimization Model for Multiple Energy Resources (HOMER) software to minimise energy costs and several system architectures were obtained for different operating scenarios. The performance and cash flow of the selected system were included. The results suggest that the combination of traditional technologies for fuel cell power generation could be feasible for a country like Colombia, depending on economic factors such as the Consumer Price Index (CPI), the discount rate, and the availability of renewable resources. The proposed system achieves a Levelized Cost of Electricity (LCOE) of $0.112/kWh, comparable to state-of-the-art systems in the literature. This research contributes to the global effort of transitioning to alternative energy sources and reducing carbon emissions.

Characterization of the proximity to urban areas of the global energy potential of solar and wind energies

This study estimates the global energy potential of solar photovoltaics and onshore wind power and characterizes it with respect to the proximity to urban areas. Solar and wind power are centerpieces of a decarbonized energy system, and that different to other energy resources are disperse and widely available across the world. Therefore, characterizing how close or far these resources can improve the estimation of their availability. The analysis is based on a model using geo-referenced data and parameters related to the energy resources, technologies and land features. Results showed that the energy potential of solar (409 PWh yr−1) and wind (354 PWh yr−1) energies concentrates in the vicinity of urban areas, demonstrating the value of resources close to urban areas for covering current electricity needs. For example, current electricity consumption can be covered with high-grade solar resources (capacity factor >24%) within 30 km away from urban areas, or with middle-grade onshore wind resources (capacity factor >20%) within 20 km away from urban areas. Thus, it suggests that constraining the use of solar and wind energy in the proximity of urban areas due to social acceptability concerns, may significantly impact the deployment of high to mid-quality resources. The study is a starting point to evaluate the effect of restrictions and costs related to the proximity on the availability of renewable resources and their penetration in long-term decarbonization scenarios.

Environmental and techno-economic viability of using hydrogen in the vehicle sector for a rapid energy transition in Argentina

Argentina has a wide availability of renewable resources, which provides important advantages for the hydrogen vector incorporation. The province of Córdoba is an excellent model case for the study of the rapid incorporation of hydrogen as fuel, to replace 20% V/V of natural gas consumed in vehicular use. This does not involve major changes in infrastructure or modifications to the vehicles. This paper computes and analyzes the levelized cost of hydrogen with the emissions associated for each part of the complete hydrogen supply chain. Two different production sources were used: renewable energies sources and the Argentine electrical grid; and two production pathways: in situ and centralized production. Comparing the same volume of proposed hydrogen compressed natural gas and current CNG, a cost decrease in the majority of the scenarios and a CO2eq emission reduction ranging from 19.5 to 8.2% are achieved, even if the hydrogen is produced using the carbon-intensive grid electricity.

Global trading of renewable electricity-based fuels and chemicals to enhance the energy transition across all sectors towards sustainability

Renewable electricity-based fuels and chemicals are expected to play an ever-growing role in future sustainable energy systems. e-Fuels and e-chemicals are crucial for the defossilisation of hard-to-abate segments in long-distance aviation and marine, as well as industrial feedstocks. This study evaluates the role of e-fuels and e-chemicals in a global energy system transition from 2030 to 2050 by analysing the demand for these fuels, potential for production, and costs. Furthermore, the global trading potential of e-fuels and corresponding benefits are assessed. The wide availability of renewable resources enables the diversification of energy markets compared to the current concentrated fossil fuels trade, leading to lower volumes of traded e-products than currently traded volumes of fossil fuels. South America, sub-Saharan Africa, and Middle East and North Africa regions emerge as important exporters of e-fuels and e-chemicals. This study estimates that 23–32% of the total demand will be traded, depending on the type of e-fuel and e-chemical. Results indicate that global trade will reduce the global average levelised cost of e-fuels and e-chemicals by 4.4–6.8% in 2050, with some regions yielding a reduction of up to 38% compared to a self-supply scenario. Globally, the trading of e-fuels and e-chemicals is estimated to reduce total energy costs by 136 b€ annually. The risk of supply disruptions to importers can be mitigated with diversified portfolio strategies combining different exporting regions. Global trade benefits both importers, as the costs of e-fuels and e-chemicals are reduced, and exporters that benefit from additional income, employment, and tax revenues.

Water-related limits to growth for agriculture in Iran

Globally, agriculture is the primary water consumption sector. This study used water footprint (WF) as a bottom-up tool and satellite imagery as a top-down tool to estimate the internal water use (WU) in the agricultural sector in an innovative way to show the effects of water-intensive use in agriculture in an arid country. The WF of Iran has been quantified for 19 main crops and for related agricultural products exported from Iran to partner countries. Using a bottom-up approach, Iran's total yearly agriculture net water consumption is estimated to be 42.43 billion cubic meters (BCM) per year. Out of 42.43 BCM total net internal water use, only 1.61 BCM is virtual-water export related to these 19 products, and the remaining 40.82 BCM is for internal use. Our results using satellite imagery show that in case of using all possible lands for agriculture, it would require 77.4 BCM. However, not all these lands are within human reach, and the maximum available water is way lower than this amount. Using satellite imagery, the total evaporation from agricultural lands shows 55.27 BCM for 2020, which agrees with national reports during 2005–2014. This study shows that agricultural water consumption tends to use internal water resources at a maximum level for export and national use, significantly impacting renewable and non-renewable water resource availability, especially in groundwater.

Systematic literature review of integrated project scheduling and material ordering problem: Formulations and solution methods

Project cost performance and resource availability can be improved by integrating project scheduling and material ordering. Integrating project scheduling and material ordering can achieve an optimal total cost due to trade-offs among project cost elements such as material purchase costs, availability of renewable resources, and ordering and holding material. Several studies in the project scheduling literature have addressed project scheduling and material ordering problems with varying assumptions and characteristics and have formulated these problems using mathematical models. This paper reviews studies that modeled and solved these integrated problems using a systematic literature review approach. The systematic literature review seeks to provide evidence to answer research-specific questions such as 1) Under what assumptions and conditions have the integrated project scheduling and material ordering problems been studied? 2) How are these problems formulated, and what mathematical models are proposed? 3) What methods are used to solve the mathematical models? 28 articles were eventually chosen during the search process steps. The selected articles were reviewed and presented using a classification scheme that consists of five aspects: project scheduling problem type, material ordering aspects, uncertainty conditions, objective function, and solution method. The mainstream of research in this scope is identified based on the article review results; thus, future research fields can be identified. This paper provides authors who want to research in this area with insights into the formulation of problems and solution methods, as well as information from previous articles.

Integration of non-energy among the end-use demands of bottom-up whole-energy system models

The complexity of bottom-up energy system models has progressively grown to enhance the representativeness of the system under analysis. Among them, whole-energy system models aim at representing the energy resources, conversion technologies, and energy demands of regions (i.e., a country) in its entirety. Despite this effort leading to an increased number of conversion processes modeled, the typologies of the end-use demand have remained limited to three categories: electricity, heat, and transportation. A fourth category, herein addressed as the non-energy demand, has widely been neglected. Being associated with the production of chemicals (i.e., plastics and fertilizers), the non-energy demand represents 10% of the world’s total end-use demand. Its relevance becomes fundamental in analyses that define the optimal defossilization pathways of energy systems with high dependence on fossil resources. This contribution introduces a schematic representation of the conversion processes involved in the satisfaction of the non-energy demand. Through its implementation in a bottom-up whole-energy system model, it evaluates the impact of this additional end-use in the configuration of the optimal energy system. In this study, the Belgian energy system, characterized by a penetration of the chemical and the petrochemical industries up to 20% of its total end-use demand, is taken as a reference case. The transition to a defossilized energy system is enforced through a snapshot analysis with a progressively more restrictive emissions cap. The results emphasize the role of renewable carriers (i.e., methanol and ammonia) in the defossilization of the energy system, otherwise hindered when the non-energy demand is neglected. The 100% import of these carriers at the lowest emissions cap highlights the potential dependence of the country under analysis, with limited availability of renewable resources, from countries exporting renewable methanol and ammonia.