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The correlation between renewable energy technology innovation (RENTI) and carbon neutrality has been studied extensively. Meanwhile, an efficient digital financial system and a favorable innovation environment are essential to promote RENTI. This paper examines the effects of digital finance and the regional innovation environment on RENTI using panel data from 31 Chinese provinces spanning 2011 to 2020. The findings demonstrate that digital finance directly promotes RENTI. The marginal effect of digital finance is more significant for eastern regions and regions with developed finance. The threshold effect analysis shows that the positive impact of digital finance on RENTI reaches a higher level when government financial support and ICT development exceed a certain threshold. In addition, appropriate levels of human capital are conducive to the positive impact of digital finance. Finally, we find that digital finance promotes local RENTI and benefits RENTI in neighboring regions. Our findings offer insights for policymakers to guide digital finance to support RENTI and optimize the innovation environment. [ABSTRACT FROM AUTHOR]

Data analysis is one of the most important tools that can contribute to unveiling critical relationships. Econometric approaches are evolving continuously, while older methods although are not completely abandoned, they may be used vis-à-vis the new ones for comparison purposed. This special issue has called for papers that have used novel research methods in a panel data framework for the studying and modelling renewable energy use and management. This special issue is useful for readers because it provides them an overview of the those novel methodologies employed in the field of renewable energy economics and econometrics. [ABSTRACT FROM AUTHOR]

Geothermal energy is one of the largest renewable energy sources available in Mexico and is the most important non-conventional renewable energy source utilised in this country. It is estimated that Mexico has geothermal reserves of approximately 8000 MWe, which can be implemented for the generation of green hydrogen. The paper focuses on the geothermal energy potential of high-enthalpy resources dominantly found South and Southeast Mexico, through investigations of 12 hot springs, with temperature depths as high as 400 °C in some areas. The utilization of suitable power production equations is further refined using the Monte Carlo Method to optimize the numerical findings of the power potential. Therefore, the Visual Basic Application (VBA) in Microsoft Excel is used through the Visual Basic Editor (VBE) function to code the Volumetric Method Equations. Furthermore, 20,000 iterations are then simulated to produce the minimum and maximum power potential/capacity (MWe), from which 10 % and 90 % confidence intervals are then determined. The study calculates that, considering a production lifetime range of 25 years, a total of 147.57 MWe of geothermal power capacity could be generated across all 12 hot springs in Mexico. [ABSTRACT FROM AUTHOR]

Sustainable development has many dimensions, such as clean energy, green growth, and sustainable industry. Green finance has a key role in realizing these targets. The core focus of the existing paper is to demystify the influences of green finance, green energy on environmental dynamics in Malaysia covering the timeframe from 1990 to 2018. To this end, we employ the QARDL technique to peruse the effect of green finance, renewable energy, and economic growth on CO 2 emissions and ecological footprint separately. By doing so, we crosscheck the empirical outcomes and inspect the consistency of the analysis. Firstly, empirical results show that the ecological footprint model yields similar results to the CO 2 emissions model in terms of statistically significant quantile ranges and the magnitude of the coefficients. According to the overall results, GDP increases environmental degradation while green finance and renewable energy have a mitigating role. Finally, we confirm a significant EKC hypothesis for Malaysia. Based on these findings, we recommend Malaysian policymakers focus on energy efficiency, realize financial reforms and promote green energy through the financial system to achieve the 2050 net-zero emission target. [Display omitted] [ABSTRACT FROM AUTHOR]

The generation of electricity from free-flowing water is an important renewable energy source. In this paper, we introduce a new turbine concept based on a vertical axis turbine with two extraction planes and a rectangular harvest area suitable for rivers or ocean currents. Using numerical simulations, we show that the extension of the classic vertical axis turbine by linear sections can significantly improve efficiency, with gains of up to 12% in the case of the Reference Model 2 turbine, a benchmark prototype used for comparison. Based on the findings, a prototype is designed and built with a focus on optimizing the blade pitch using computational fluid dynamics simulations. The prototype is subsequently evaluated through performance measurements on a test boat. Our results show that the Linear Turbine has the potential to significantly improve the efficiency of kinetic energy converters for free-flowing water, with an efficiency of around 42% achieved in our small prototype. Key features of the turbine include its ability to generate electricity from rivers and ocean currents with minimal impact on the natural environment, its high potential efficiency, vertical construction, and linear working range. The design of the turbine is complex, but its potential applications include use in small-scale systems and as a environmental alternative to traditional hydroelectric dams. Further investigations are needed to focus on economic design and to validate improved designs with 3D fluid simulations. • New turbine concept with a vertical axis and two extraction planes. • High potential efficiency comparable or beyond traditional horizontal axis turbines. • Prototype design with tip speed ratio of 2 and 42% efficiency. • Design allows for easy extension and increased harvesting area. • Dynamic pitch adjustment for improved power generation. [ABSTRACT FROM AUTHOR]

Thailand had summited its Intended Nationally Determined Contributions (INDCs) in 2015 and ratified the Paris Agreement in September 2016. Its INDCs stated that by 2030 GHG emissions will be reduced by 20–25% when compared to the business- as -usual (BAU) scenario by using mainly domestic renewable energy resources and energy efficiency improvement. Therefore, this paper assesses the potential of greenhouse gas (GHG) emission reduction by the use of renewable energy in Thailand's INDCs and the economic impacts from GHG emission reduction. This paper employed the Asia-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE). Besides the BAU scenario, four mitigation scenarios are assessed at given GHG emission levels and renewable power generation targets. Results show that Thailand's INDC can be achieved under the current renewable energy target in Thailand's Power Development Plan 2015. As a result, macroeconomic loss will be small under the light GHG reduction target; however, it will be large under the stringent GHG emission reduction target. The GDP loss ranges from 0.2% in the case of a 20% reduction target to 3.1% in the case of a 40% reduction target in 2030. Thus, the availability of land for deploying the renewable energy technologies such as solar, wind and biomass needs to be assessed. [ABSTRACT FROM AUTHOR]

Renewable Energy Sources (RES) have prompted an additional burden on power system planners due to their stochastic nature. Hence it increases the need for Ancillary Services (AS) in power system. In deregulated electricity markets, AS has become an important issue because they are necessary for reliable and secure operation of a power system. Operating Reserve (OR), considered in this paper, is a measure of generators ability to increase their output under contingencies. ISO uses this service either for balancing purpose or for replacing the energy that had been scheduled to be provided by the unit that malfunctions. Thus establishing an efficient market for reserve services has become crucial. The premises of this paper is the development of penalty based Short-Term Market (STM) for the procurement of energy and OR. The effects of stochastic behavior of WPP on Social Benefit (SB) and Procurement Cost (PC) are investigated for the development of efficient STM. The proposed approach has been analyzed on IEEE-30 bus test system by implementing a sequential dispatch approach on various market structures. The results obtained under different market scenarios shows that there is a mandated requirement of effective penalty mechanism in order to discourage the imbalance behavior of RPPs. [ABSTRACT FROM AUTHOR]

To find an efficient and economic way to convert wave energy, a one-base multi-buoy offshore floating wave energy converter Sharp Eagle Wanshan is designed, consisting of four absorbing buoys, one semi-submersible barge, and other components. The working principle of the device is described in this paper. An experiment of a 1:13.78 model machine was carried out to test the hydrodynamic performance of the device and make an initial evaluation for the design The influence of wave period, wave height, work load and wave direction was tested. After construction, two-stage open sea tests have been finished in the waters near Wanshan Islands from November 2015 to June 2016. The device showed great power generation capacity with total generated output of 30530.57 kWh, and largest daily generation of 1847.09 kWh. During the open sea tests, the energy conversion efficiency was measured, and results show that capture width ratio of Wanshan remains higher than 20% in the wave period between 4 and 6.5 s and wave height range of 0.6–1.8 m. After operating in a wide range of conditions, including a tropical storm on May 27, amounts of tests data, experiences and lessons have been obtained and will be summed up and presented in the paper. [ABSTRACT FROM AUTHOR]

Composition of renewable power system for stratospheric airships is introduced, curved paving model of solar array is established, the high accuracy calculation method for output power of solar array is proposed, and operation process of renewable power system is simulated. On basis of this, endurance of the stratospheric airship is evaluated, and the influence of some important factors on endurance is analyzed, including wind resistance strategy, photoelectric transformation efficiency of solar array and the specific energy of lithium battery. Simulation results show that, 1) endurance of the stratospheric airship can be improved by adjusting power sequential during day and night with maneuverable wind resistance strategy, for the case in this paper, endurance increases 24.2 h compared with fixed point wind resistance strategy, 2) endurance can be greatly improved in a certain range through increasing photoelectric transformation efficiency of solar array and the specific energy of lithium battery, for cases in this paper, endurance increases 73.5 h and 47.5 h respectively, 3) to realize closed cycle of renewable power system during day and night, attenuation of radiation flux with the change of date must be considered in design of renewable power system, and sufficient redundancy should be designed for solar array. [ABSTRACT FROM AUTHOR]

Torrefied biomass has considerable potential as a biomass fuel to replace coal in energy and process heat production. The aim of this paper is to evaluate the potential of torrefied biomass in different industries, both power and non-power generation industries, and considers the impact of such use on the international biomass market. The power generation sector has been so far the leader in testing torrefied biomass use with other industrial demand lagging behind. There are promising technical possibilities for greater torrefied biomass use in a number of other areas such as the steel, non-metallic minerals, as well as the pulp and paper industries. Although a large increase in torrefied biomass consumption by industry is not immediately foreseeable, industrial use by actors outside the energy generation sector could increase demand for torrefied biomass in general and, as a result, stimulate development of global torrefied biomass markets. Results show that the torrefied biomass demand significantly depends on the bioenergy markets. It seems that despite of the challenges, the growth of torrefied biomass demand will have a large progress in coming years. [ABSTRACT FROM AUTHOR]

Offshore wind energy and wave energy are two exploitable sources of renewable energy available in the same marine environment. A co-located energy harvesting system of these two resources has the potential to play a leading role in the recent renewable energy mix mandate. A co-located system of mature offshore wind technology and a nascent wave energy technology can exploit the synergies of the two technologies, including the reduced cost, the easy operation and maintenance, and more importantly the potential of decreased power variability. This paper deals with a multi-site analysis of wind and wave power resources, and the estimation of exploitable energy through different wind turbines and wave energy converters (WECs). Results are presented for NSW Australia, but the devised strategy is generic and can be implemented in any region. Ten WECs, with different operating principles, are used for the estimation of the exploitable wave power, and the best performing converter is considered for the co-located wind-wave farm. A power fluctuation factor is introduced to quantify the reduction in power variability of the co-located wind-wave farm. Different percentage mixes of wind and wave energy are evaluated for the co-located wind-wave farm in the multi-site analysis. •A multi-site analysis of wind and wave for estimation of exploitable energy. •Performance evaluation of wind and wave energy conversion technologies. •Power variability representation with power fluctuation factor for a co-located farm. •Characterization of percentage share of wind and wave in a co-located farm. [ABSTRACT FROM AUTHOR]

The transition to an energy system with a focus on electricity sector is becoming more and more crucial to increase the life expectancy of fossil fuels, but also to meet the current commitments regarding greenhouse gas emissions. This paper presents the most credible options to increase the share of renewable energy resource in the Algerian electricity power system by 2050. Screening curve method is used to assess the levelized cost of electricity (LCOE) of different technologies for electricity generation and EnergyPlan tool is used to estimate total annual cost, annual investment cost, renewable energy resource share and CO 2 emissions during the time horizon. The efficiency and the simplicity of multi-objective cuckoo search algorithm make it a powerful approach for solving energy strategy multi-optimization problem. Considering LCOE economic order and the availability of renewable energy resource, the energy transition strategy is established by minimizing the total annual cost and maximizing renewable energy share in 2035, 2040, 2045, and 2050 using multi-objective cuckoo search algorithm. The results revealed that achieving 75% is technically feasible but will require significant investment. [ABSTRACT FROM AUTHOR]

In this paper, the influence of dust and extreme dust events in the renewable energy generation in the island of Tenerife has been studied. Two different models have been proposed: one model to estimate the influence of atmospheric Particulate Matter (PM) in the Photovoltaic (PV) generation, and a second model that captures the influence of a set of weather and temporal variables, including PM, in the renewable generation of the island. Additionally, the hypothetic situation of extreme dust events occurring in a future 100% renewable electric system in the island of Tenerife is analyzed. Results show the interconnections between PM2.5, PM10 and wind resources on the present and future power output in the Island, and how the future storage capabilities need to take into account these events for a necessary increase in resilience related to climate change and related extreme weather events. • Extreme dust events in renewable energy generation for islands is studied. • Models are based on the influence of atmospheric PM in the PV generation. • The hypothetic situation in a future 100% renewable electric system is analyzed. • Results show the interconnections between PM2.5, PM10 and wind resources. • Storage capabilities need to take into account for a necessary increase in resilience. [ABSTRACT FROM AUTHOR]

In order to alleviate the resource depletion as well as achieve decarbonization, developing renewable energy system is a feasible solution. This paper establishes a wind-photovoltaic-battery-thermal energy storage hybrid power system, and investigates its multi-objective planning-operation co-optimization. The hybrid system utilizes the cost-effectiveness of thermal energy storage and flexibility of battery to jointly tackle the intermittency of renewable energy. A novel coordinated operation strategy based on the operation threshold of power block is proposed, and the planning-operation co-optimization model considers the minimization of net present cost and loss of power supply probability to determine the optimal operation threshold and sizing decision variables. The co-optimization problem is solved by a proposed multi-objective evolutionary algorithm with decision-making (MOEA-DM), which introduces the preference information of decision-maker to guide the evolution towards preferred region. Furthermore, the uncertainties and losses of wind power are captured by a data-driven forecast model. Finally, the results of case study show that: (1) the data-driven model performs higher accuracy in wind power forecast compared to commonly-used physical models; (2) The proposed MOEA-DM has better convergence, diversity and robustness performance in decision-maker's preferred region compared to widely-used Non-dominated Sorting Genetic Algorithm-Ⅱ (NSGA-Ⅱ); (3) Hybrid battery-thermal energy storage system achieves better economy and reliability through the optimal coordinated operation strategy compared to either single energy storage under different test conditions. [ABSTRACT FROM AUTHOR]

Despite the high commitments of the European Union (EU) member countries toward achieving the sustainable development goals (SDGs), on average, the region has reportedly under performed in the area of ensuring sustainable production and consumption. This paper uses the Generalized Method of Moments (GMM) estimation of panel vector autoregressive (PVAR) with impulse response functions (IMFs) to assess the effects of domestic material consumption, renewable energy, financial development, and greenhouse gas emissions on environmental quality in the EU-28 countries based on the panel data for the period 2000:Q1–2017:Q4. The empirical results reveal that the shocks to domestic material consumption, renewable energy, economic growth, financial development, and greenhouse gas emissions affect the drives towards a sustainable environment. Particularly, the shocks to renewable energy and financial development improve environmental quality, while the shocks to domestic material consumption and greenhouse gas emission deteriorate environment quality. The shock to economic growth improves environmental quality up to the 4th horizon after which it begins to deteriorate environment quality. Furthermore, the panel causality results indicate bidirectional causality between greenhouse gas emissions and the rest of the variables except renewable energy, which is unidirectional. The causality between economic growth and renewable energy, economic growth and financial development, and financial development and renewable energy has a feedback effect while a unidirectional causality flows from economic growth to domestic material consumption. These findings have implications for sustainable production and consumption. • Effects of domestic material consumption, renewable energy, and greenhouse gas emissions on the environment are examined • Improved GMM estimation of Panel VAR and impulse response functions are explored • Renewable energy and financial development improve environmental quality • Domestic material consumption and greenhouse gas emissions deteriorate environment quality • Economic growth only improves environmental quality up to the 4th horizon after which it deteriorates the environment. [ABSTRACT FROM AUTHOR]

Distributed generation (DG) can offer significant value to power systems by reducing some of the energy and emission marginal costs of centralized generation. These costs can change significantly with the expansion of power systems, especially when renewable energy integration is supported on large new transmission capacity. Accordingly, these cost and price changes could have a potentially large impact on the system value of DG. In this paper, we assess the impact of increasing transmission capacity, for a massive integration of renewable energy, on the energy and environmental system value of solar PV, wind, and energy storage DG. To illustrate this, a case study is presented based on the main Chilean electric power system. We found significant variations in the DG value with different transmission line capacity levels. For instance, just the energy value of PV and storage DG changed up to 43% and 100%, respectively, for line capacity levels growing from 0% (no line) to 200%, in one key transmission line analyzed. This can also represent a strong impact on the revenue of DG projects, generally paid based on this energy value. Furthermore, DG revenue losses can be problematic considering that DG still offers a significant environmental value. • System energy and emission marginal costs are key drivers of the system DG value. • We assess system DG values as a function of transmission line capacity levels. • There is a large impact of transmission capacity variations on the system DG values. • Transmission and renewable systems can cause significant DG revenue losses. • The energy value of PV and storage DG can change up to 43% and 100%, respectively. [ABSTRACT FROM AUTHOR]

In the light of increasing negative impacts on environment of fossil fuels, development of renewable energy utilization is a high priority. In this regard, hybridization of geothermal and solar energies (as two types of abundant renewable resources) has been proved to be a promising combination for renewable-based power generation systems. For power generation from low-grade renewable resources, the transcritical CO2 (TRCC) power cycle has been considered as an ambitious competitor against ORC and Kalina cycle. This paper aims at development and proposal of a novel efficient trigeneration system based on TRCC cycle for production of power, hydrogen, and freshwater driven by hybrid solar-geothermal energies. In proposed system, thermoelectric generators and HDH desalination unit are employed for waste heat utilization of TRCC cycle. Thermodynamic and thermoeconomic analyses and two-objective optimization are conducted and monthly performance of the system is estimated for real environmental data. Results showed that, the system yields highest values of power, hydrogen and freshwater in May, respectively as 1286 kW, 1.989 kg/h, and 13.38 m3/day. Under the optimized conditions, the system yields energy efficiency of 23.35% with a unit product cost of 17.07 $/GJ. Also, the results revealed efficiency improvement via increasing the solar energy share. In addition it is shown that, developed system in this work can yield higher efficiency compared to a similar trigeneration system based on the Kalina cycle. [ABSTRACT FROM AUTHOR]

This study explores the dynamic effect of non-renewable energy, renewable energy, economic growth, and foreign direct investment on environmental degradation in twenty selected African countries over the period 2000–2015. We have adopted Environmental Kuznets Curve hypothesis and the Pollution Haven/Halo hypothesis simultaneously. In the first stage, this paper performs cross-independence test and found cross-sectional dependence in carbon emissions, non-renewable energy, and renewable energy. In the second stage, it applies first generation and second generation unit root tests for panel data and found that all concerning variables are I(1) except for economic growth which is found I(0). Therefore, we used the Panel Autoregressive Distributed Lag approach using Pooled Mean Group, Mean Group, and Dynamic Fixed Effect estimators. The results indicate that all independent variables are significant and positive to CO 2 emissions except for renewable energy found significant and negative to CO2 emissions, and foreign direct investment found significant and positive only in the long term. Moreover, the Environmental Kuznets Curve hypothesis did not hold in our sample, while we found strong evidence for the Pollution Haven hypothesis in selected African countries. • non-renewable energy, renewable energy, economic growth, and foreign direct investment-CO 2 emissions relationship is investigated. • Positive effect of non-renewable energy and negative effect of renewable energy are found. • The Environmental Kuznets Curve hypothesis does not hold. • The Pollution Haven hypothesis is verified. [ABSTRACT FROM AUTHOR]

Offshore wind offers an excellent opportunity for domestic renewable energy production with a vast potential for future energy systems. Offshore wind resource assessment, however, can be challenging. Remote sensing data e.g., Synthetic Aperture Radar (SAR), provide high spatial resolution detailed information on the spatial variability of offshore wind and have been used for wind resource assessment, as well as for the long-term validation of wind speed estimates from other sources (e.g. Numerical Weather Prediction models). This paper focuses on the evaluation of a 26-month time-series of Sentinel-1 SAR Level 2 OCN products for wind resource assessment in the offshore areas around Cyprus. Sentinel data were evaluated against a 10-year regional reanalysis dataset (UERRA) time-series and wind measurements from 5 coastal meteorological stations in Cyprus. Comparison revealed an overall agreement between the fitted stations and Sentinel Weibull distributions while discrepancies exist between the two data sources and UERRA. Bias observed between Sentinel and UERRA Weibull-derived statistics appears to be spatially dependent. Preliminary wind power assessment results indicate a significant wind power potential for the southwestern offshore areas of Cyprus, surpassing 400 W / m 2 on average, offering thus economically viable solutions in terms of a future offshore wind power project development. [ABSTRACT FROM AUTHOR]

This paper aims to provide a scientific approach that indicates the need to focus on renewable energy potential to meet energy needs in Turkey. Turkey began to take advantage of renewable energy technologies a few years ago. Accordingly, the issue of determining the best renewable resources for the country has been brought to the agenda in recent years. The issue was considered to be a limited multi-objective optimization problem allowing us to achieve a reliable result. However, the parameter of each resource was considered as a range value, rather than traditionally expressed as an exact value, and a multi-objective decision problem was developed with an interval coefficient. This method allows us to obtain more accurate and reliable results without the need to resort to normalization methods used to eliminate unit differences. According to the results of this study, the most convenient alternatives for Turkey are hydro, wind, and solar power. The findings also support decision policies aimed at reaching targets for the electricity sector in 2023, as put forth by the Ministry of Energy and Natural Resources (MENR). • Multi-dimensional analysis of optimum renewable energy resources for a sustainable economy. • Selection of renewable energy sources under uncertainty. • More sensitive selection of resources by representing the instability in expert opinions with interval numbers. • The most optimum renewable energy resources for Turkey: "geothermal, solar, and wind.". [ABSTRACT FROM AUTHOR]

The rapid uptake of renewable energy technologies in recent decades has increased the demand of energy researchers, policymakers and energy planners for reliable data on the spatial distribution of their costs and potentials. For onshore wind energy this has resulted in an active research field devoted to analysing these resources for regions, countries or globally. A particular thread of this research attempts to go beyond purely technical or spatial restrictions and determine the realistic, feasible or actual potential for wind energy. Motivated by these developments, this paper reviews methods and assumptions for analysing geographical, technical, economic and, finally, feasible onshore wind potentials. We address each of these potentials in turn, including aspects related to land eligibility criteria, energy meteorology, and technical developments of wind turbine characteristics such as power density, specific rotor power and spacing aspects. Economic aspects of potential assessments are central to future deployment and are discussed on a turbine and system level covering levelized costs depending on locations, and the system integration costs which are often overlooked in such analyses. Non-technical approaches include scenicness assessments of the landscape, constraints due to regulation or public opposition, expert and stakeholder workshops, willingness to pay/accept elicitations and socioeconomic cost-benefit studies. For each of these different potential estimations, the state of the art is critically discussed, with an attempt to derive best practice recommendations and highlight avenues for future research. • Review of over 300 studies on large-scale onshore wind potential assessments. • Analysis of geographic, technical, economic and 'feasible' potentials. • Identify weaknesses in methods and best practice examples. • Methods could improve transparency, validation, and sensitivities. • Further interdisciplinary research required on 'feasible' potentials. [ABSTRACT FROM AUTHOR]

Large greenhouse gas reductions are possible with a fully decarbonised grid and electric land transport. Additional electric load could pose a significant challenge to a grid with high levels of variable and non-dispatchable renewable energy sources. This scenario is not well-examined, nor is the use of pumped hydro energy storage for low-cost energy balancing. In this paper, we investigate the electrification of land transport within a photovoltaics and wind dominated 100% renewable electricity system. Only technologies that are deployed at scale and widely available globally are considered, namely photovoltaics, wind, battery electric vehicles, high voltage transmission, and pumped hydro. As a case study we present an hourly energy balance analysis of the Australian National Electricity Market with 100% renewables and 100% uptake of electric vehicles for land transport. The cost of the system is determined by occasional periods (days-weeks) of low renewable generation, and therefore only weakly dependent on the charging regime. The 40% increase in electricity demand due to electric land transport can be incorporated with a 4%–8% increase in the levelized cost of electricity. An exception occurs if most passenger vehicle charging occurs during the evening peak period, in which case the average price increases by about 18%. [ABSTRACT FROM AUTHOR]

Site selection is an integral component of energy planning. For renewable technologies, Geographic Information System (GIS) and multi-criteria decision-making became the most prevalent approach for such a data-intensive task. However, site selection can also be carried out using GIS and Cost-Benefit Analysis (CBA). This paper aims to introduce a four-stage energy modelling framework for siting of Variable Renewable Energy (VRE) farms using GIS and CBA. Adopting a well-established framework, the first three stages are dedicated to finding suitable sites and estimating spatio-technical inputs. In the fourth stage, CBA is performed from the developer's perspective, and the viability of VRE technologies is assessed using the benefit-cost ratio. The model output is a viability map, and externalities are separately calculated to assist planning and policymaking. We implement this framework to assess the viability and estimate the externalities of utility-scale solar PV and wind farms in Bohol and find a modest potential for viable VREs in this province. The compensation effect, which is inherent to linear combination models, is unavoidable and is manifested in our results. We have also evaluated the model sensitivity to the model variables and parameters. This framework can be implemented in a study area of any geographic scale. • A four-stage spatial energy modelling framework is introduced •Benefit-cost ratio is used to measure the viability of variable renewable energy •Externalities are separately calculated to assist planning and policymaking •Compensation effect amongst variable and between technologies are manifested [ABSTRACT FROM AUTHOR]

Over the years, Governments of South Asia have faced the challenge of achieving the goal of sustainable development. On the one hand, they must satisfy the ever-growing demand for energy and, on the other hand, the interminable deterioration of the environment is causing great concern among political economists. The widening gap between the demand and supply of energy, over-reliance on the use of fossil fuels, and increasing import bills due to rising global prices are the challenges that South Asia is facing. These can be overcome by using its great potential in renewables. This paper uses SWOT methodology to identify that the poor financial situation of the distribution companies, due to power losses and non-cost-reflective tariffs, and the lack of credit opportunities, due to high interest rates and inaccessibility of loans for the long-term, are the major impediments to the growth of the renewable energy sector of the region. Moreover, there is a conflict of interest between the manufacturers of renewable energy equipment and the developers of renewable energy projects in terms of Government policy concerning the imposition of import duties. India is moving towards protection of the former, while the latter see opportunities in the renewable energy sector of Pakistan. [ABSTRACT FROM AUTHOR]

Pistacia atlantica Desf. fruit oil may be considered as a feedstock which is low cost and does not compete with food crops for biodiesel production. The aim of this paper was to investigate the effect of the variation in fatty-acid composition and oil accumulation in developing P. atlantica fruits on the resulting biodiesel properties. Samples were collected from two Algerian sites, i.e. Ain oussera and Laghouat. Gas-liquid chromatography revealed that the oleic acid (51.6–55.4% of fatty acids) was the major component, followed by linoleic acid (21.9–29.4%), and palmitic acid (12.7–19.4%). The highest tocopherol isomer contents were observed in the immature stage (200–256 μg g−1 oil). The quality of the biodiesels synthesized from immature and mature P. atlantica fruit oils was tested according to the international standards. All biodiesel samples exhibited a high energy content with a higher heating value (HHV) of 40 MJ kg−1. Meanwhile, the cetane number, long chain saturation factor, degree of unsaturation, oxidative stability and density were in the ranges 53–55, 4.3–5.6, 101–113, 3.4–3.8 h, and 852–862 kg m−3, respectively. The cold flow behavior of biodiesel was assessed through the cloud point (CP) and the cold filter plugging point (CFPP). The CP value ranged from −4.5 to −2.3 °C, and CFPP from −7.1 to −4.9 °C. The above fuel properties comply with the limits imposed by the EN 14214–08, GB/T 20828–07 and ASTM D6751-2010 standards, showing a promising source for biodiesel production in Algeria. • Potential of Pistacia atlantica fruit oils as renewable energy is demonstrated. • Effects of harvest period and growing region on oil content are evaluated. • Biodiesel was produced through the esterification of fatty acids. • Biodiesel from P. atlantia fruit oil has quality equivalent to standards. • Physicochemical characterization established biodiesel's suitability for engines. [ABSTRACT FROM AUTHOR]

Corporate environmental information disclosure systems are important for controlling pollution caused by corporate activities. However, different motives associated with environmental information disclosure have different influences on the financing of companies. This paper adopts renewable energy companies instead of high pollution industries as a research object. The study analyzes the resource-dependent disclosure motivation of renewable energy companies, and the impact of environmental information disclosure on the scale and cost of direct and indirect financing. The results show the following. First, renewable energy companies in China have a resource-dependent motivation to disclose environmental information, with a gap between the level of environmental information disclosure and their actual environmental performance. Second, renewable energy companies may obtain more direct financing amount and lower indirect financing costs, but cannot obtain lower direct financing costs and more indirect financing amount by improving the level of environmental information disclosure with the resource-dependent motivation. Third, there are differences in the specific incentives for environmental information disclosure among the Eastern, Middle, and Western regions of China. The government needs to standardize the detailed rules and standards of the corporate environmental information disclosure system, and improve the environmental protection awareness and the implementation of green credit in the Western region. [ABSTRACT FROM AUTHOR]

Waste-to-energy (WTE) technologies convert municipal solid, and biomass wastes into affordable renewable heat and power energy. However, there are large uncertainties associated with using waste feed as a renewable energy source. This paper proposes a WTE management tool that provides forecasting and real-time optimization of power generated with the consideration of anomaly. The WTE management framework was designed based on a biological neural network, the Hierarchical Temporal Memory (HTM) coupled with a dual-mode optimization procedure. The HTM model is inspired by the mechanism in the cerebral neocortex of the brain, providing anomaly identification and spatial-temporal prediction. In this work, the HTM-based smart energy framework is demonstrated in an industrial case study for the power generation of a waste-to-energy cogeneration system. HTM was compared with methods such as Long Short-Term Memory (LSTM) neural network, Autoregressive Integrated Moving Average (ARIMA), Fourier Transformation Extrapolation (FTE), persistence forecasting, and was able to achieve mean squared error (MSE) of 0.08466% while giving 35450 Euro profit in half a year. Coupled with a novel dual-mode optimization procedure, HTM demonstrated 11% improvement with respect to only predictive optimization (with HTM) in estimated gross profit. [Display omitted] • A practical, effective and robust smart energy management framework was presented. • A neocortex-inspired algorithm, Hierarchical Temporal Memory was used for prediction. • An industrial cogeneration plant in Czech Republic was used as the case study. • HTM predicted demands better than LSTM, ARIMA and Fourier analysis (MSE = 0.8466%). • Novel dual-mode optimization was used which achieved 27.3% improvement in gross profit. [ABSTRACT FROM AUTHOR]

In this paper, nanoencapsulation of PCM n-Octadecane with PMMA polymeric shell enhanced with comonomer PEHA via miniemulsion polymerization was performed. The effects of comonomer addition to homopolymer shell were studied to achieve a qualified shell. Optimization of nanocapsules was carried out based on RSM to investigate the effects of design parameters of Monomer/PCM, Comonomer/Monomer, and Emulsifier/PCM on the percentage of encapsulation and production cost. Innovatively, the renewable energy system was employed to provide the required energy and water for the polymerization reaction. Moreover, by introducing the nanofluid slurry containing CuO nanoparticles, the performance of synthesized nanocapsules as thermal energy storage (TES) was investigated in the PV-thermal PTC/gas boiler heating system installed in the designed room. The result indicated that the addition of comonomer EHA could improve the thermal stability and morphology of the polymeric shell. According to the optimization outcomes, the encapsulation percentage of 83.3% at the cost of 0.083$ provided the nanocapsules with the latent heat of 66 Jg-1. Also, the results of room temperatures indicated the effectiveness of the proposed heating system providing thermal heat comfort along with the overall improvement of the system utilized with the TES. [Display omitted] ● Employing solar PTC-gas boiler-nanofluid slurry as a promising heating system. ● Implementation of the renewable energy system for a cleaner production. ● Nanoencapsulation of n-Octadecane by polymeric shells through miniemulsion. ● Improving the thermal stability of PMMA shell by adding PEHA comonomer. [ABSTRACT FROM AUTHOR]

Arising the Nearly Zero Energy Buildings (NZEB) concept in Europe, the solar district heating systems (SDHS) present a potential solution to meet the buildings sector's European energy performance directive. Nevertheless, current practices face several technological and economical barriers to ensure service quality. In this context, our work presents a sustainability analysis (technical, economic, environmental, and social) for SDHS integration in the residential sector to meet the NZEB and positive energy building goals. This paper proposes an application of a machine learning model incorporating multi-objective optimization and multi-criteria decision making to facilitate a sustainability index for the decision-making stakeholders and policymakers. The proposed analysis application is illustrated through retrofitted residential communities with building energy rating (D) at different sizes (10, 25, 50, 100, and 500 houses) located in Emmen (Netherlands) and compared to a standard decentralized heat pump. The optimization results show the ability of SDHS to provide a solar fraction up to 95% in the community of 500 houses. Furthermore, achieving a NZEB status is only approved economically from a community size of 100 houses with a life cycle cost of 41 €/m2 and a payback period of 25 years. These results align with a substantial environmental and social improvement of 78.2% and 29.7%, respectively, compared to the decentralized heat pump. Overall, this study provides policy decision making with an evaluation for positive energy communities and suggests the SDHS integration to meet the global sustainability goals. [Display omitted] • Sustainability evaluation for solar district heating is proposed. • A multi-objective optimization based on a surrogate model is framed. • Five retrofitted solar residential communities located in the Netherlands are optimized. • Renewable energy fraction up to 95% can be achieved for the 500 houses. • Solar district heating is a competitive solution to attain Nearly Zero Energy Building. [ABSTRACT FROM AUTHOR]

Renewable energies are getting ongoing growing interest and so are cross-flow turbines to harness water energy to produce electrical energy. Use of numerical methods to evaluate and predict this type of turbine performance can be of major help. This paper presents a Darrieus turbine numerical performance results. The present numerical method uses hydrodynamics theory applied to this turbine with three rotating blades, taking in consideration their relative angle of attack and hydrodynamic coefficients changes with the azimuthal angle. A comparison of these results with our experimental results is done for five water flow velocities (V = 0.43–0.73 m/s). The computer source code developed in this study allows determining this turbine torque, mechanical power and their coefficients. Good agreement between the numerical and experimental results is observed. For instance, for V = 0.73 m/s, the relative differences between the numerical and experimental maximal torque, mechanical power and their coefficients are respectively equal to 1.85%, 5.33%, 1.85% and 1.85%. The maximal torque and power relative differences vary respectively from 1.33% to 4.76% and from −3.95% to 10.40% for the other flow velocities. This new approach could be very useful because of its merit of providing a good performance evaluation of cross-flow turbines with much less computing time and much lower cost than computational fluid dynamics software methods. [Display omitted] • A novel-original method to evaluate cross-flow water or wind turbines performance. • Useful contribution in cross flow water and wind turbines design and development. • The source code allows determining the torque, power, torque and power coefficients. • Very good agreement between the experimental and numerical results. • A relative difference of 1.85% and 5.33%, respectively for the torque and power. [ABSTRACT FROM AUTHOR]

Despite the importance of cost of capital and expected returns from investing on renewable electricity generation in Africa on one hand and the implications of such investments on economic, social and environmental factors on the other. These concepts are not well understood by non-finance and finance actors respectively. Studies that analyze renewable energy-growth nexus at regional and global level are lacking. Instead, existing studies emphasize on individual countries or panel of countries. The paper undertakes comparisons of costs and returns of selected renewable energy technologies in Africa and presents estimates of its impact on Africa's economic growth between 1990 and 2014. Even with abundant renewable resources and well performing technologies measured using levelized cost of electricity and expected internal rate of return, investment on renewable electricity generation is quite low. Findings from Autoregressive Distributed Lag approach and cointegration established a long run relationship among hydro power generation, carbon emissions and electricity consumption. Error Correction Model results suggest that investment in renewable generations excluding hydro power generation is boosted by economic growth, so long as development of such renewables corresponds with lesser carbon emissions. To accelerate renewable development, SSA countries will need to deploy initiatives that enhances national economic growth. [ABSTRACT FROM AUTHOR]

With the ongoing increase of variable renewable energy sources (VRES), such as wind or solar power, weather dependent production profiles induce uncertainty on the supply side and change operations at large in wholesale power markets. In this paper, we study how an increasing market share of VRES affects spot power price dynamics and the forward price premium. Using data from simulated power markets, we analyse the forward premium in three identical power markets with a varying market share of VRES supplied to the system. We demonstrate that markets with a high share of supply from VRES yield a significantly lower forward premium than markets with a low market share of wind or solar supply. Our results further confirm that, regardless of the market share of supply from VRES, forward power prices contain information about future spot power prices. These insights generate important implications for producers, retailers and other market participants exposed to wholesale price risk. • Variable renewable energy sources impact price dynamics in forward and spot power markets. • Supply from variable renewable energy sources decreases power price forward premiums. • Forward power prices contain information about future spot power prices. • The study suggests implications for market participants exposed to power price risk. [ABSTRACT FROM AUTHOR]

The concept of a microgrid (MG) has been introduced to integrate the conventional generators, different renewable energy resources and energy storage systems (ESS) to meet the specific load demand. However, the intermittent nature of renewable energy resources produces a variable output, which drives an imbalance between power generation and demand in MG. The ESS is utilized to makes a balance between power generation and demand. When several renewable energy resources and ESS are available in MG as energy resources, then an energy management system (EMS) is required that can handle the stochastic nature of renewable energy resources, schedule the power of renewable energy resources and ESS for managing the power flow among MG resources and main grid while ensuing cost-effective operation. Therefore, this paper proposed an optimum EMS that aims to minimize the overall operating cost of grid-connected MG along with the short-term forecasting of PV power and load demand. The proposed EMS consists of four modules: forecasting, scheduling, data acquisition (DAQ), and human–machine interface (HMI) modules. An improved hybrid forecasting approach that combines a 3-level stationary wavelet transform (SWT) and grey wolf optimization-based least-square support vector machine (GWO-LSSVM) is proposed in the forecasting module to achieve day-ahead forecasting of PV power and load demand. In the scheduling module, the weighted salp swarm algorithm-based scheduling is applied to achieve the optimum power flow of grid-connected MG. Then, the DAQ and HMI module is used to monitor, analyze, and modified the input variables of the forecasting and scheduling module. The MATLAB/Simulink environment is then used to simulate the proposed EMS for grid-connected MG. Finally, numerical results demonstrate the efficiency of the proposed EMS for grid-connected MG with commercial load demand over the existing competitive approaches. [ABSTRACT FROM AUTHOR]

Access to electricity is vital in rural regions of Africa. There is substantial potential to utilise wind energy, yet investment in renewable energy projects is trivial because it has been insufficiently endorsed. As a result, most people living in remote regions of Africa rely entirely on diesel-powered generators, which expel pollutants in substantial amounts. These adversely affect the health of people and the environment. Sudan – one of Africa's largest countries – has a range of resources from which renewable energy could be generated, including favourable wind power generating conditions. This paper represents the first effort in literature to use a strategic perspective to explore how viable wind energy systems are in Sudan. It reports a study using the Hybrid Optimization Model for Electric Renewables (HOMER) across 21 diverse sites in Sudan. It identifies the optimal wind turbine system and best locations and analyses the costs involved and how much pollution could be prevented by implementing wind farms instead of diesel systems. The results establish that the optimal type of wind turbine across the investigated locations is the Enercon E−138 EP3. Wind farm use is expected to avoid almost 49 million kg/year of pollutants and reduce energy cost by US$0.91317/kWh. The optimal sites for utilising wind energy were Wawa, Dongola, Karima, Wadi Halfa and Al-Goled in order of suitability and their low costs of electricity and high wind speed records. Wind turbine pricing is predicted to reduce over time, so the study varied the cost of wind turbines to understand the impact on project economics. A reduction in wind turbine costs by 10 % lowered energy cost to between US$0.03681/kWh and US$0.04052/kWh. A further 25 % price drop reduced the cost of energy to between US$0.03067/kWh and US$0.03376/kWh. This study reveals the significant potential of integrating renewable energy into the energy mix of Sudan and provides an essential reference for wind farms in the energy sector across other developing countries. • Finding the ideal wind turbine system and sites for exploiting wind energy in Sudan. • Exploring the costs and evaded emissions using wind farms over diesel generators. • Investigating the impact of wind turbine price on the project economics. • The optimal wind turbine was determined to be Enercon E−138 EP3. • The best locations for harvesting wind energy are Wawa Dongola, Karima and Wadi Halfa. [ABSTRACT FROM AUTHOR]

The flexible coupling of sectors in the energy system, for example via battery electric vehicles, electric heating or electric fuel production, can contribute significantly to the integration of variable renewable electricity generation. For the implementation of the energy system transformation, however, there are numerous options for the design of sector coupling, each of which is accompanied by different infrastructure requirements. This paper presents the extension of the REMix energy system modelling framework to include the gas sector and its application for investigating the cost-optimal design of sector coupling in Germany's energy system. Considering an integrated optimisation of all relevant technologies in their capacities and hourly use, a path to a climate-neutral system in 2050 is analysed. We show that the different options for flexible sector coupling are all needed and perform different functions. Even though flexible electrolytic production of hydrogen takes on a very dominant role in 2050, it does not displace other technologies. Hydrogen also plays a central role in the seasonal balancing of generation and demand. Thus, large-scale underground storage is part of the optimal system in addition to a hydrogen transport network. These results provide valuable guidance for the implementation of the energy system transformation in Germany. • Combination of all options for flexible sector coupling has high synergy potential. • Flexible hydrogen production is a key enabler of renewable energy system integration. • Hydrogen storage and transport networks are important future energy infrastructures. • Climate targets require a timely acceleration of sector coupling implementation. [ABSTRACT FROM AUTHOR]

With the growing importance of renewable energy generating resources around the world, the government is working towards expanding the share of renewable energy to 20% of total power generation considering the limitation of coal-fired and nuclear generation by 2030 in South Korea. However, the growing number of wind generating resources being connected to the electrical power system presents a challenge for transmission grid planning to increase the penetration of wind power while maintaining high levels of reliability and security of the electrical power system. In this paper, we propose a probabilistic power output model of wind generating resources for network congestion management. We use the historical data from the wind farms located on Jeju Island in South Korea to fit the Weibull distribution and implement Monte Carlo simulations. The simulation results, which represent network congestion with probabilistic values, are applied to the empirically modeled power grid of Jeju Island and a steady-state security evaluation is performed. The proposed probabilistic approach will be a key role to reduce the risk of over-investment in power transmission facilities compared to the deterministic approach to develop the generation mix scenarios with high wind power penetrations. • A New probabilistic approach based on Monte Carlo Simulations is presented. • A practical process for probabilistic wind power output modeling is proposed. • Probabilistic security assessments for network congestion management are suggested. • An empirical data of Jeju Island's wind farms is considered for network congestion analysis. [ABSTRACT FROM AUTHOR]

To achieve a high penetration of renewable energy integration, an effective solution is to explore the interdependence between numerical weather prediction (NWP) data and historical wind power to improve prediction accuracy. This paper proposes a novel combined approach for wind power prediction. The characteristics of NWP and historical wind power data are extracted by using the feature extraction technique, the predictor is designed based on extreme learning machine (ELM) and least squares support vector machine (LSSVM) model, and then key parameters of the prediction models are optimized by improving cuckoo search (ICS) to obtain a reliable value, which is defined as the pre-combined prediction value (PPA). To obtain a reliable result, a variance strategy is developed to allocate the weights of the pre-combined prediction model to obtain the final predicted values. Four seasons dataset collected from regional wind farms in China is utilized as a benchmark experiment to evaluate the effectiveness of the proposed approach. The results of comprehensive numerical cases with different seasons show that the proposed approach, which considers multiple-error metrics, including error metrics, accuracy rate, qualification rate, and improvement percentages, achieves higher accuracy than other benchmark prediction models. • A novel combined framework is proposed to predict short-term wind power. •Linear and nonlinear feature extraction strategies are applied to analyze the character of NWP data. •A variance combined strategy is used to allocate the optimal weight of the primary combined model. •The wind power prediction error analysis is conducted by multiple-error performance metrics. [ABSTRACT FROM AUTHOR]

The paper focuses on fabricating a white cement brick fuel cell (WC–BFC) using agricultural waste rice husk ash (RHA) for sustainable power generation. The samples from each material with three different compositions 0, 2, and 12% of RHA were analysed. First with (RHA + sand) and (RHA + sand + cement) for commercial brick technology. This study aims to replace the present ordinary old concrete brick with WC-BFC technology in the market. Steel is an essential material used in concrete for longs decades due to its strength and stability. Therefore, the brick cost depends on the type of electrode used for brick fabrication. However, Ammonium chloride 0.3 g/ml was used as fuel with regular intervals of time for WC-BFC. Where steel/graphite electrodes generate a higher power density of 2008.93 mW/m2 with 12% RHA concentration and later for long life electrodes, Graphite/Graphite is also optimised to see the effect on the power. These bricks themselves generate massive free power from their own. The proposed technology is eco-friendly, inexpensive, sustainable, and compatible with generating renewable energy for vast brick commercial applications. On one side work as a regular concrete brick, and another side free power supply. This technology itself is clean, safe, and sustainable. [Display omitted] [ABSTRACT FROM AUTHOR]

In the context of recent environmental debates related to the impact of economic development on environment quality, this paper's aim is to explain the GHG emissions in few EU New Member States (Bulgaria, Slovakia, Slovenia, Czech Republic, Hungary, Romania and Poland) in the period 1990–2019 using a panel data approach (panel threshold and dynamic panel models) and a time series approach (vector error correction models). The importance of this study is related to the identification of paths to reduce pollution in order to manage climate challenges. The results indicate similarities and differences in terms of the impact of various indicators on the total GHG emissions and in the agricultural sector. There is a negative correlation between human development index/GDP and total GHG emissions when GDP growth is below and above 0.83%. Above this threshold estimate, there is a more strong and negative correlation between human development index and GHG emissions than below the threshold value. Below 1.41%, human development index and growth of value-added in agriculture do not influence pollution in agriculture. Above 1.41%, economic growth and change in value-added in agriculture positively influence the pollution in this sector. The relationship between GDP and GHG is inverted N-shaped for Bulgaria, Hungary, Czech Republic, Slovakia, Slovenia and Romania (sample countries), while the relationship between value-added in agriculture and GHG is N-shaped. This research confirms the U-shaped RKC at the national level and for agriculture in the sample countries, while an inversely U pattern was observed for Poland. Renewable energy consumption reduces total GHG emissions in the sample countries. Some policy proposals are indicated to promote a sustainable development in these countries with less pollution. [Display omitted] [ABSTRACT FROM AUTHOR]

Wind power is recognized as one of the most promising renewable and clean energy sources under the context of the increasing depletion of fossil fuels. The exact wind speed forecasting has great significance for the large-scale connection of wind farms with the power grid. In light of this, this paper contributes to establishing a novel hybrid model that can predict the future wind speed accurately. Firstly, the original wind speed time series is decomposed by the fast ensemble empirical mode decomposition into several sub-series that are further integrated by the runs test. The phase space reconstruction is used to dynamically choose each integrated sub-series' input and output vectors for the prediction model. Additionally, an improved whale optimization algorithm is exploited to optimize the weights and bias of the extreme learning machine. Finally, prediction results are obtained from the aggregation of each integrated sub-series prediction. To verify the accuracy and applicability of the proposed hybrid model, we apply several comparative models to conducted two case studies using different wind speed time series from Inner Mongolia that is Asia's largest gathering area of wind power farms. According to the experimental results, it can be concluded that the decomposition reduces the volatility and randomness of wind speed, and the runs test lowers the forecasting complexity. The phase space reconstruction can capture the chaotic property of wind speed series. The optimization for the whale optimization algorithm enhances its global and local optimization ability to further improve the performance of extreme learning machine. Overall, the proposed hybrid model can effectively capture the non-linear characteristics of wind speed series. • A novel hybrid short-term wind speed prediction model is proposed. •The model of FEEMD-RT-PSR is used for the data preprocessing. •Whale optimization algorithm is optimized. •The performance of extreme learning machine is improved. [ABSTRACT FROM AUTHOR]

An efficient and equitable allocation scheme for renewable portfolio standard (RPS) quota is of great significance to renewable energy (RE) development and the improvement of the electricity trade market. This study establishes a quota allocation model based on the lowest cost of RE generation to determine the RPS targets (LC-RPS) of 30 Chinese provinces. Subsequently, an index system based on energy consumption, RE resource endowment, historical responsibility, and transmission facilities is constructed to determine the RPS targets (IN-RPS). Finally, the two scenarios mentioned above are compared with the RPS target allocation scenario published by the Chinese government (GM-RPS) and with the NO-RPS scenario. The results show that: Compared with those of GM-RPS and IN-RPS, the power generation cost associated with the LC-RPS is reduced by 8.5% and 49.4%, respectively, and the unit power generation cost is reduced by 9.4 and 39.7 RMB/MWh, respectively; the fairness of the LC-RPS is marginally worse than that of the other three scenarios, but the fairness of the power generation cost is still relative average, thereby demonstrating distribution fairness. This paper appeals to the Chinese government for the perfection of a national renewable energy certificates (REC) trade market and offering additional REC for solar generation. •Least-cost quota (LC-RPS) and index system allocation schemes are proposed. •The renewable energy (RE) generation capacity of 30 Chinese provinces is determined. •The power generation cost of the LC-RPS is reduced compared with other schemes. •The LC-RPS scheme is more efficient and meets national RPS targets. •The generation resources are diversified with the improvement of the national REC trade market. [ABSTRACT FROM AUTHOR]

The benefits of biomass as an alternative fossil fuel can be realized mainly through biomass consumption. This paper examines the growth rate and spatial patterns of biomass consumption in the United States (hereafter US) during the period 2000–2012, using the SLOPE index, Moran's I and local Moran's I. Results indicate that US States show either slow growth or slow decline in biomass consumption during the period 2000–2012. The number of States that have slow growth in biomass consumption is slightly larger than the number of States showing slow decline. The pattern of growth rate of biomass consumption revealed by the SLOPE index and the observed pattern of the temporal variation of biomass consumption ensures that the SLOPE index can catch the growth rate of biomass consumption. This pattern does not align with the increased annual investment in biomass, indicating that the investment in biomass does not flow down to the biomass industry effectively. The pattern of growth rate of biomass consumption will provide additional evidence for the debates about the effectiveness of State renewable energy policy, and demonstrates an urgent need for appropriate State renewable energy policies. There is a High-High spatial cluster around the Southeast of the US and a Low-Low spatial cluster in the Middle of the US in 2000, 2004, 2008 and 2012. The regional spatial cluster in biomass consumption has somewhat relationship with the growth rate of biomass consumption, which can help the understanding of the growth rate of biomass consumption. • The SLOPE index is used to investigate the growth rate of biomass consumption. • The pattern of growth rate does not align with the increased annual investment. • There is an urgent need for appropriate State renewable energy policies. • There are regional clusters in biomass consumption in 2000, 2004, 2008 and 2012. • The regional spatial cluster has somewhat relationship with the growth rate. [ABSTRACT FROM AUTHOR]

In this paper, we present the first attempt at modelling the impact of economic policy uncertainty on renewable energy consumption in the USA using monthly data from 1986 to 2019. By implementing recent nonparametric (nonlinear) econometric approaches, we find that our models suffer from nonlinearity and smooth, as well as abrupt structural changes. The nonparametric unit root tests indicate non-stationarity of the model variables while the cointegration suggests the presence of nonlinear cointegration. The Granger causality analyses establish robust nonlinear causation in both directions between the policy uncertainty and renewable energy variables, with one exception: from geothermal energy to the three-component index of uncertainty. The nonparametric regressions exhibit a negative long-run association between policy uncertainty and renewable energy consumption, i.e., higher economic policy uncertainty lowers renewable energy consumptions and vice-versa. These findings have robust policy implications as they underscore the importance of governments, policymakers and concerned agents to maintain uniformity in economic policy to encourage renewable energy consumption in the USA. [ABSTRACT FROM AUTHOR]

This paper deals with the performance and techno-economic analysis of micro-hydropower plant consists of array of Helical Savonius hydrokinetic turbines (HSHKT). In this study, an optimal inter-turbine distance (L) and two specific HSHKT array formations, i.e., triangular and staggered are considered on a 69 m river stretch corresponding to a study area of 2.36 km2. River free stream velocity ranges between 0.88 and 1.88 m/s. Sensitivity analyses were carried out in HOMER software based on the free stream velocity and electric load to investigate the feasibility of the standalone hydrokinetic turbine renewable energy systems (RES) suitable for the rural community. Further, optimization analyses were performed considering minimum total net present cost (TNPC) and cost of energy (COE). The optimum RES consists of triangular formation of 24 numbers of HSHKTs, with 524 kWh/d electrical load, 187 numbers of battery and converter of 46 kW, having COE of Rs 8.22/kWh, TNPC of Rs 14.5 × 106 and electric production of 399.5 MWh/yr. TNPC and COE of triangular formation are 4.83% and 9.12% less than staggered formation, whereas electric production of the triangular is 4.99% more than the staggered formation. Thus, based on economic and energy indicators triangular array formation is considered as best for RES configuration. [ABSTRACT FROM AUTHOR]

Worldwide, the emerging trend of hybrid renewable energy sources integration in modern power systems is increasing due to privileged prices and clean electricity supply. However, the optimal planning of rural hybrid systems is a challenging and complex task, especially when different alternatives and sustainability aspects are considered. This paper develops an integrated decision-making approach for the optimal planning of a 100% renewable energy supply system comprising solar, wind, hydro, and biomass sources in a rural area located in Pakistan. An hourly-based design optimization analysis of twelve on/off-grid electrification alternatives is performed. The optimization model simultaneously addresses five sustainability criteria related to economy, reliability, ecology, society, and topography aspects. Furthermore, a novel hybrid decision-making model has developed to identify the unique best configuration with on-grid and off-grid options. The proposed model combines fuzzy analytic hierarchy process, multi-objective optimization based on ratio analysis technique for order of preference by similarity to an ideal solution, and evaluation based on distance from average solution methods. The results reveal that the solar-hydro-biomass battery with a life cycle cost of 10.9 M$ is the top-ranking off-grid system. When the hybrid system is connected to the grid, the solar-hydro-battery has found the most appropriate design with a life cycle cost of 12.96 M$. Both scenarios have a negligible capacity shortage of 0.09%. Ecologically, the optimal off-grid system produces only 408.37 kg/yr of CO 2 due to the significant energy share of solar and hydro sources (99.3%). The optimal on-grid system produced the minimum CO 2 with 29,177.89 kg/yr compared to other alternatives. Also, employing the optimal on/off-grid designs require land area and jobs of 96.6 m2, 14 jobs, and 118 m2, 15 jobs, respectively. Overall, the developed approach with the presented case study offers a valuable benchmark and guidelines for investors and stakeholders to create realistic investment plans for the energy industry looking to push efficient inducements to encourage the high dissemination of renewables. [Display omitted] • 100% renewable energy system is established for on/off grid rural electrification. • Twelve distinctive solar/wind/hydro/biomass-based hybrid energy alternatives are optimized. • An integrated fuzzy-AHP/TOPSIS/EDAS/MOORA decision-making model is proposed. • Cost, reliability, emission, social, and topographical criteria are simultaneously considered. • Results prove the long-term sustainability of 100% renewable in rural Pakistan. [ABSTRACT FROM AUTHOR]

The paper examines the integration between electricity and renewable energy certificate (REC) markets for India. The empirical investigation covers the factors influencing solar and non-solar REC markets, using an autoregressive distributed lag (ARDL) modeling approach. The variables used in this study are the traded volume of solar and non-solar RECs, the traded volume of electricity, wholesale electricity price, and prices of solar and non-solar RECs. The dataset contains monthly time series for the period January 2013–July 2020. The ARDL bounds test results show that the variables are cointegrated. The long-run ARDL estimates indicate that the traded volume of solar REC is influenced by the traded volume of electricity (positive effect), wholesale electricity price (negative effect), the traded volume of non-solar REC (positive effect), and price of solar REC (negative effect). However, the traded volume of non-solar REC is influenced by only traded volume (positive effect) and price (positive effect) of solar REC. Based on the findings of this study, few suggestions are discussed to strengthen the REC market in India. [Display omitted] • Impact of electricity market on renewable energy certificate (REC) market is examined for India. • Autoregressive distributed lag model is employed on a monthly time series data over January 2013–July 2020. • Only the traded volume of solar REC is influenced by traded volume and price of electricity. • Traded volume of solar and non-solar RECs is positively related to each other. • An increase in the price of solar REC raises traded volume of non-solar REC. [ABSTRACT FROM AUTHOR]

This paper analyses the current status and barriers to wind energy deployment in Africa. We find that wind energy in Africa has rapidly grown by 740% from 0.74 GW (GW) in 2009 to 5.5 GW as of 2018. This has been spurred by continued falling costs, improved technologies, and political commitment. Notwithstanding the above, Africa still had installed only about 1% of its estimated wind capacity as of 2018, despite having competitive costs and speeds capable of deploying utility-scale wind farms. Wind LCOE costs in Africa have declined by 30% from an average of US cents 10 to 7 per kWh between 2010 and 2019. Furthermore, wind energy development on the continent is sporadic and skewed toward southern and northern Africa. While some countries have introduced targets for wind energy and instruments such as feed-in-tariffs, we find that the promotion, and scale-up of wind energy is lacking in many countries on the continent. Our findings add to the growing body of literature on the nascent wind industry in Africa. An equally important feature of this study is demystifying these challenges while making a case for shifting fossil fuel dominance in Africa by supporting clean energy transition. • Wind energy has grown by 740%, from 0.74 GW to 5.5 GW between 2009 and 2018. • Africa has installed only about 1% of its estimated wind capacity as of 2018. • Wind LCOE costs in Africa have declined by 30% between 2010 and 2019. • Wind development is sporadic and skewed toward southern and northern Africa. • Promotion and scale-up of wind energy is lacking in most of the countries reviewed. [ABSTRACT FROM AUTHOR]

Tendency towards installation of distributed photo-voltaic (PV) systems has led to an increased emphasis on grid frequency control. Grid-interactive buildings equipped with heating ventilation and air conditioning (HVAC) system has a great potential to regulate the frequency in renewable energy resources rich grids. This paper integrates distributed PV systems in a decoupled building-to-transmission-network (B2TN) and explicitly formulates the interaction between a grid and the buildings through real time pricing (RTP). As grid frequency conveys the information about operating conditions of a power system, therefore, frequency based RTP generators namely; linear, hyperbolic tangent and inverse hyperbolic tangent are used. A price responsive model predictive controller (MPC) for optimal scheduling of HVAC load is developed where reference temperature set point is dynamically adjusted subject to RTP. Moreover, the clear and cloud covered sky impacts of PV power generation on frequency and RTP deviations are investigated. Comparatively, inverse hyperbolic tangent model maps the frequency deviations on a wider RTP range which increases the scale of reference temperature set point resulting peak frequency deviation suppression up to 40 % and load regulation beyond 12 MW without inherently affecting the building electricity cost when compared to ordinary MPC (without demand response service). • Decoupled framework integrated buildings, grid and photovoltaic system. • Price-responsive model predictive control developed for grid frequency support. • Real time pricing computed as a function of grid frequency deviations. • Results showed 40% peak frequency deviations suppression and 12 MW load regulation. [ABSTRACT FROM AUTHOR]

This study explores the effect of geopolitical risk on renewable energy deployment, assuming that geopolitical uncertainty stimulates nations to be independent and rely on their renewable energy sources in order to reduce the geopolitical risk concomitant to fossil fuel inflows. The current paper's data sample covers 10 net crude oil importer countries during the period 1985–2017. It employs panel cointegration analysis and estimate an autoregressive distributed lag model. The results show that geopolitical risk has a significant and positive effect on renewable energy diffusion. Therefore, this work determines that it is an incentive, not an obstacle, to renewable energy deployment. The present study's policy implication is that renewable energy development is expected to increase if the geopolitical risk rises, all else being equal. [ABSTRACT FROM AUTHOR]

The State of Illinois is examining prospects to increase the development of in-state renewable energy resources on public lands. In response, this research develops a scalable decision-support tool for identifying suitable areas for solar energy generation in the state. This paper provides guidance for state agency-driven solar development by evaluating the suitability of potential generation areas in terms of environmental impact, socioeconomic costs, and energy productivity, and providing a forum for critical decision-making. More specifically, geospatial technologies are combined with a suitability analysis to reveal the potential for solar energy generation on public lands. This study demonstrates the usefulness of the resulting information for supporting both regional and local decision-making as a Planning Support System (PSS). Our analysis suggests that the large-scale analysis using fine resolution data is useful for comparison and site-specific decision making - with site verification protocols in terms of physical implementation. We find that planning decisions for solar development should use a fine-grained suitability approach at a large scale and a feasibility analysis at a specific scale. We present our findings in statewide application along with a scalable PSS tool to optimize and support solar decision-making process and democratize the information for engaging a broader audience. [Display omitted] [ABSTRACT FROM AUTHOR]