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Small wind turbines are often sited in more complex environments than the open terrain sites assumed in relevant installation guidelines or in the international small wind turbine design standard IEC61400-2. The built environment is an example of such a complex environment and installation of small wind turbines on the rooftops of high buildings has been suggested by architects and project developers as a potential means of incorporating sustainable energy generation into building design. In the absence of guidelines for installing wind turbines in the built environment, two key wind measurement parameters are the rate at which a data acquisition system (DAQ) samples the sensor, and the period over which the sampled data is averaged. This paper presents the results of the effect of sampling rate and averaging period on turbulence measurements from a monitoring system on a building rooftop, in order to inform the process of developing guidelines. The results will inform the development of a Recommended Practice of wind resource assessment in the built environment, via the International Energy Agency Task 27. The key finding of the paper is that, in general, 10 Hz sampling and 10 min averaging period give upper estimates for turbulence intensity and maximum values of the turbulence power spectra. Using these conservative values in the design of the turbine may be the best approach to ensure that the turbine can handle both the fatigue loads and resonance due to gusts. [ABSTRACT FROM AUTHOR]

Interest in renewable and clean energy sources is becoming significant due to both the global energy dependency and detrimental environmental effects of utilizing fossil fuels. Therefore, increased attention has been paid to wind energy, one of the most promising sources of green energy in the world. Wind speed forecasting is of increasing importance because wind speeds affect power grid operation scheduling, wind power generation and wind farm planning. Many studies have been conducted to improve wind speed prediction performance. However, less work has been performed to preprocess the outliers existing in the raw wind speed data to achieve accurate forecasting. In this paper, Support Vector Regression (SVR), a learning machine technique for detecting outliers, has been successfully combined with seasonal index adjustment (SIA) and Elman recurrent neural network (ERNN) methods to construct the hybrid models named PMERNN and PAERNN. Then, this paper presents a medium-term wind speed forecasting performance analysis for three different sites in the Xinjiang region of China, utilizing daily wind speed data collected over a period of eight years. The experimental results suggest that the hybrid models forecast the daily wind velocities with a higher degree of accuracy over the prediction horizon compared to the other models. [ABSTRACT FROM AUTHOR]

This article has been retracted: please see Elsevier Policy on Article Withdrawal ( http://www.elsevier.com/locate/withdrawalpolicy ). This article has been retracted at the request of the Editor-in-Chief. This paper bears substantial similarity to the following previously published papers by the same group of authors, neither of which were cited in Renewable Energy Volume 76 (2015): 72–81. The extensive similarity affects the originality of the paper here retracted. The previously published papers are as follows: “Overview of the Australian national electricity market transmission use of system charges for integrating renewable generation to existing grid”, Radzi, N.H., R.C. Bansal, Z.Y. Dong, K.N. Hasan, and Z. Lu., IET Generation Transmission & Distribution, 2012, DOI: 10.1049/iet-gtd.2011.0835 . “An efficient distribution factors enhanced transmission pricing method for Australian NEM transmission charging scheme”, N.H. Radzi, R.C. Bansal, Z.Y. Dong, M.Y. Hasan, and K.P. Wong, Renewable Energy, 2013, DOI: 10.1016/j.renene.2012.12.013 . [ABSTRACT FROM AUTHOR]

The increasing penetration of renewable energy sources in Europe requires market mechanisms which allow an efficient balancing of these sources. This paper analyzes the participation of renewable generators in the Spanish intraday market. First, the organization of the intraday market and the short-term market mechanisms influencing intraday trading are described. After that, day-ahead and intraday market prices, as well as intraday trading volumes, are used to study the behavior of market agents in the Spanish intraday market. Regarding renewable generators, the influence of support schemes on the behavior of these agents in the intraday market is also analyzed. This paper shows that the Spanish intraday market has effectively contributed to renewable generation balancing. Despite this, market distortions have incentivized some renewable generators to arbitrate between the day-ahead and intraday markets, giving rise to higher system costs. Based on the presented analysis, it is argued that these distortions need to be removed from short-term markets to incentivize market parties, especially intermittent generators, to reduce forecast errors over time, improving economic efficiency and avoiding the use of costly balancing actions performed by the System Operator. [ABSTRACT FROM AUTHOR]

This paper discusses an overall strategy for reducing energy demand in non-domestic buildings, mainly focusing on office developments. It considers four areas: reducing internal heat loads; addressing passive design through the building construction; using efficient and responsive HVAC systems and focusing on chilled (heated) surface systems; integrating renewable energy supply systems into the building design. The impact on energy use and carbon dioxide emissions will be discussed. The paper will draw from a range of design projects carried out in Europe, where this integrated approach has been applied, and then explore the benefits in relation to applications in the Middle East and China. Energy modeling results, to inform the design process will be presented, using energy simulation for three case study locations, in Zurich, the Chongqing and Abu Dhabi. [ABSTRACT FROM AUTHOR]

Eighty per cent of the people without access to electricity live in rural areas. Due to high investment costs in the grid, the solution to providing electricity to these people will mainly rely on the installation of islanded hybrid microgrids. Designers need to consider a variety of factors for the optimal design of hybrid microgrids. However, many of these criteria are qualitative or uncertain. This paper provides a novel methodology to assess the influence of such criteria in the design of a Hybrid Microgrid of Renewable Energy Sources (HRES). The method combines context analysis, literature review and the Analytic Network Process (ANP) through panels of experts and surveys. The methodology ranked the criteria and helped to design a HRES in an isolated Honduran rural community in the Mesoamerican Dry Corridor. The study presents a review and classification of the main criteria and energy technologies considered for the design of HRESs in rural communities. The most influential factors turned out to be the institutional support, the possible expansion of the grid to the community and the availability of local energy resources. Regarding energy technologies, photovoltaic and wind power ranked as the preferred followed by a biomass gasifier as backup. • Access to electricity will largely depend on new microgrids. • The article presents a novel methodology to select energy technologies of a HRES. • Institutional support largely affects the design of hybrid microgrids. • Solar PV is the preferred energy technology for a microgrid in Honduras. [ABSTRACT FROM AUTHOR]

Photovoltaic systems are one of the most promising renewable energy technologies for on-site generation. Most of the techno-economic studies consider distributed standalone photovoltaic generation with little consideration of community-based standalone photovoltaic systems. Location-based case studies are required to provide economic and reliable photovoltaic systems to meet the peak loads of residential neighbourhoods in an optimized manner. This paper devises an integrated evaluation methodology; a combination of white-box energy modelling and black box photovoltaic design optimization. This research uses optimization methods to develop a quantitative optimized model for analysing the opportunities of centralized systems to adequately meet the demands of a residential neighbourhood and support the grid. This analysis includes three metrics including the level of the energy production, reliability of system for peak power and finally the capital cost of implementation in residential districts. Results indicate that the size of a centralized photovoltaic installation is less when compared to distributed installations to support a similar single peak load. The required converter size is reduced for the centralized system owing to the reduced system size. Centralized installations require fewer batteries to store surplus energy produced due to increased interaction of energy flows. Centralized installations are economically more viable than distributed ones. • An evaluation methodology is developed to compare the feasibility of centralized PV. • Centralized PV installations ensure an optimized PV system size. • Feasibility metrics include energy production, reliability and capital cost. • Centralized PV systems are the optimal choice for sustainable planning. [ABSTRACT FROM AUTHOR]

This paper describes the developed MATPLAN - a probability-based production costing tool that treats renewable energy sources as candidates in a power system expansion planning study. Similar to the structure of the well-known Wien Automatic System Planning (WASP) package, MATPLAN comprises six modules: LOAD-CALC, EXIST-GEN, CANDI-GEN, CONFIG, OPTIMIZE and ELCC. MATPLAN takes into account the variable nature of renewable energy sources, including both solar and wind farms, and allows a user to consider renewable energy as options for expansion planning using a probability-based model. In contrast to the current practice that treats renewable energy sources as negative loads, MATPLAN enables system planners to take renewable sources as normal options for generation expansion planning problems, which can directly determine the optimal expansion policy and ELCC analysis of a system with high renewable penetration. MATPLAN is also designed as an open access software package which academics and practitioners can adapt to their specific situations and run many case studies as a screening tool. In the case studies, the tool was validated by comparing its resulting optimal expansion planning plan against that of the well-known WASP package and further tested using realistic field data. The complete MATPLAN code repository has been released under open-source licenses for public access, URL: https://github.com/wasp2019/MATPLAN. MATPLAN Wiki is also available, providing MATPLAN overview, features, user guides and developer resources. • MATPLAN has been developed for resource adequacy and production costing analysis. • It considers variable nature of renewables instead of deterministic data. • It combines probabilistic and optimization methods to handle renewables. • It has been validated by comparing the results against WASP. • MATPLAN has been made available as an open access software package on Github. [ABSTRACT FROM AUTHOR]

Decarbonization of the electricity sector is one of the major measures in slowing down the pace of climate change. In this paper, we analyze the impacts of energy storage systems (ESS) and year-to-year variability and uncertainty in the hourly profiles of variable renewable energy (VRE) on power system decarbonization in 2050. We perform this analysis through capacity expansion optimization based on technology cost projections and CO 2 emission restrictions based on 11 years of wind, solar, and load data variations in Italy's power system, with a particular focus on how ESS changes the optimal generation portfolio and system performance. We also explore the impact of ESS duration on the renewables' adoption and system costs. To quantify the impact of VRE variability in different years, we present a comparative analysis of capacity expansion optimization based on multiple-year and single-year data. Our results indicate a high RES penetration even in the absence of decarbonization policies, due to expected declines in future technology costs. In the transition to a zero-carbon electricity system, carbon capture and storage (CCS) with less than 100% carbon capture efficiency will play a role only in intermediate low-emission scenarios unless future technology advancements improve its capture efficiency. ESS investments contribute to lower total system costs by replacing more expensive flexibility resources. However, the value of ESS changes by its duration, with longer ESS durations having lower marginal value per added kWh storage capacity. Variability in VRE profiles leads to substantial variation in the system's configuration and energy cost, depending on what year is used in the optimization. Decision making based on single-year data can therefore lead to substantial increases in the systems' operational costs in other years due to increased probability of capacity shortages and load curtailments. In contrast, optimizing over multiple VRE and load years provides a more robust and cost-effective generation expansion strategy. • Results show high RES penetration levels even without decarbonization policies. • Decarbonization is less expensive with ESS, under given cost assumptions. • The marginal value of EES drops rapidly as more capacity is added. • Annual variations in VRE significantly change the system configuration and costs. • Planning with single-year data can lead to high operational costs in other years. [ABSTRACT FROM AUTHOR]

The uncertainties caused by the high penetration of renewable energy sources (RESs) and electric vehicles (EVs) challenge the normal operation of the distribution system. In order to mitigate the negative impact of fluctuations of RES outputs, a smart charging strategy of EVs is presented in this paper. First, a novel uncertainty model using set pair analysis is proposed for the prediction of RES outputs, which provides a different choice of RES modeling method. Second, EVs are modeled as demand-responsive loads by introducing stochastic dynamic pricing. Then, two fluctuation indexes are defined to measure the volatility of RES outputs, and the charging cost is adopted as an economic index for protecting EV users from financial losses. Finally, an optimal charging model is established to minimize the volatility indexes and charging costs. The genetic algorithm is used to solve the model, the seasonality of RES outputs and the spatial-temporal characteristics of EV charging loads are discussed in the simulation under different conditions. Simulations are conducted in the modified IEEE 33 test system, results show that the proposed charging strategy is effective in alleviating the output fluctuations of RESs. The charging cost of EVs can be reduced by 7.6% and 10.3% respectively in winter and summer. • A new uncertainty model of renewable energy sources is proposed. • A unique demand response model of electric vehicles is introduced. • Two fluctuation indexes are defined to measure the volatility. • An optimal framework is formulated to minimize fluctuation indexes and cost. [ABSTRACT FROM AUTHOR]

Traditional ways of planning and operation of electricity networks have been challenged lately by the spread of variable renewable energy sources, especially solar photovoltaics, and the need for better forecasting has increased interest in various solutions. Categorization of solar irradiance data, as one of the earliest applied techniques, is a frequently discussed topic in the literature, but the efficiency of different methods may be significantly variable. The aim of this paper is to compare various categorization methods using a one-year-long solar irradiance dataset and reflect on their inefficiencies and the need for more timely solutions. Six methods have been selected and implemented, including deterministic and non-deterministic ones. The number of groups created by the methods varies between three and five, and they also use data with different temporal resolution. The aim of the comparison was to reveal the strengths and weaknesses of the implemented methods and to highlight possible contradictions among them, based on two tests: uniformity in identifying days with clear or cloudy conditions and contradictory identifications. The results have shown that the usability of certain methods is limited as they are very sensitive to input data, and categorization is often inconsistent, which limits the usability and dissuades users of such methods. • Six solar irradiance categorization methods are implemented and compared. • Identification of days with clear and cloudy conditions are tested. • Examples of contradictory identifications are evaluated. [ABSTRACT FROM AUTHOR]

The paper addresses the assessment of the Stirling engine performance by comparing biomass and solar energy as external renewable energy sources. A program-code was developed in the MatLab® to solve the thermal model of an alpha-Stirling engine, accounting for the limitations in the heat transfer processes in the regenerator and the losses due to pumping effects. The solar energy source was modelled as a concentric solar dish collector, considering a receiver located at the focal point and designed to absorb the maximum possible of the solar radiation. Regarding the biomass system, the temperature of the flue gases leaving the bed is computed through an energy balance, considering the fuel energy introduced into the bed, the energy that is provided by the bed and the incident radiation in the bed. The simulation results show that the biomass-fuelled Stirling engine provided 87.5% more power output than the solar energy source, with an efficiency of 46.67%. Also, the average receiver temperature from the solar source is about 775 K, whereas, in the boiler bed, the temperature reaches the value of 1288 K. In the solar-dish modelling, the reflected radiation that passes into the cavity receiver depends on the aperture ratio and rim angle. It was proved that a rim angle of at least 45° is required to ensure lower focal distances. Otherwise, the Stirling receiver needs to be far from the surface of the dish, resulting in higher thermal losses and lower temperature inside the receiver cavity. In biomass-fuelled system, it was shown that the temperature of the flue gases increases with the increasing the radiation flux, and decreases for higher split percentages between the primary and secondary air. The study also revealed the need to investigate the combustion stability regarding the particle emission in the flue gas, which can reduce the temperature close to the hot cylinder of the Stirling engine. The LCoE for the solar-power system is of about 1658 €/kWh, which is 52% higher when compared with the biomass-fuelled system (0.109 €/kWh). In conclusion, biomass-fuelled Stirling engines are able to provide a higher power output with higher thermal efficiency, avoiding the problems usually related to solar energy intermittency. Image 1067 • The solar energy source was modelled as a concentric solar dish collector. • A bed model was developed to predict the flue gas temperature. • The biomass-fuelled Stirling engine provided 87.5% more power output than the solar. • The solar dish Stirling produces 2.3 kW of power with an efficiency of 31.3%. • The biomass-fuelled system produces 4.3 kW of power with an efficiency of 46.7%. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are currently the most popular green transportation. Wind power has received widespread attention as a kind of renewable energy source. Their rapid development has brought new challenges for the power grid. However, the technology of vehicle to grid (V2G) can realize the peak shaving of the power grid, which is considered to be an effective method to promote the integration of EVs and wind power. Therefore, in this paper, a novel integrated framework of EVs and wind farms (WEV) is proposed to use the EVs charging and discharging to smooth the wind power penalty cost that caused by overestimated and underestimated of available wind power. While a new multi-objective dynamic economic emission dispatching model based on the WEV system (WE_DEED) is developed to consider both emission and total cost objectives. In order to solve the complex constrained WE_DEED problem, we propose a multi-objective differential evolution algorithm with the self-adaptive parameter operator and local search operator based on non-dominant sorting (SaMODE_LS). Moreover, an effective constraint handling method is applied to deal with the constraints in WE_DEED problems. Different test systems based on 10-unit are given to demonstrate the reasonability and efficiency of the proposed model and method. • A new framework for the integration system of EVs and wind farms is proposed. • A novel multi-objective DEED model based on WEV system is established. • The self-adaptive parameter and local search operators are proposed. • The SaMODE_LS with the constraint handling method is developed to solve WE_DEED. [ABSTRACT FROM AUTHOR]

Food spoilage represents an urgent issue in tropical developing countries because of the lack of correctly refrigerated post-harvest storage, transportation and distribution facilities. This paper searches for the best choice of configuration and design parameters of food refrigeration systems integrated with renewable conversion units in tropical areas using a multicriteria approach (energetic, exergetic and economic). Fourty-four technically feasible integrated configurations are identified for three preservation temperatures of the food (8, 2 and −20 °C). Each configuration is simulated from the energetic, exergetic and economic point of view during one year of operation using detailed design and off-design models. A thermal storage or the connection with the electric grid is considered in the integrated configurations fuelled by solar energy to guarantee a continuous operation. Results show that the PV-powered flash-intercooled compression system is the most efficient integrated configuration for each food storage temperature (annual average COP in the range 2.3–5.7) but it represents the most economically viable option only for the highest food preservation temperature. At lower temperatures, the single-effect absorption cycle coupled with a bagasse-fired boiler shows lower costs because of the very low price of bagasse in tropical countries. On the other hand, all options including the half-effect absorption cycle result to be the less promising in terms of both COP and costs. • Flesh-intercooled systems show the highest COP (2.2–4.5) for T food = 8,2,-20 °C. • Best annual COPs (0.9–2.1) are obtained by compression systems + PV-panels. • Best average annual η e x are of the order of 10% (compression) and 5% (absorption). • Compression systems show the lowest total annual costs (575 to 935 € / k W c o o l i n g ). • Selling the electricity from absorption + biogas-ICE options leads to economic gains. [ABSTRACT FROM AUTHOR]

The increasing demand for energy from renewable sources is entailing the development of technologies oriented to increase the profitability of such projects and thus the attractiveness for potential investors. Wind power constitutes one of the most relevant renewable energy sources; however, the costs of the wind farms associated with Operations & Maintenance are prominent along the life-cycle. This paper proposes an approach intended to reduce these costs and lower the Levelized Cost of Energy. In this context, it is presented an opportunistic maintenance policy based on more accurate reliability estimates of the wind turbines components. The reliability of the components is estimated through a model based on Artificial Neural Networks that dynamically calculates the impact of operational conditions on the failures of the wind turbines. The approach has been validated through a case study based on real field data which proposes a multi-objective optimization of the maintenance strategy for the life-cycle of a wind farm. The obtained results provide interesting findings from the perspective of wind farms investors, operators, and owners. • Life-cycle approach for the maintenance management of wind farms considering operational environment. • Dynamic reliability model based on Artificial Neural Networks. • Comparison of several scenarios entailing different maintenance strategies and reliability models. • Case study based on real field data to see the benefits of the proposed approach. • Extensive experimentation and optimizations to validate results. [ABSTRACT FROM AUTHOR]

In this paper, the efficient salp swarm algorithm (ESSA) is proposed to solve the energy management (EM) with emission problem of renewable micro-grid (MG) including storage devices. Because of the uncertainties in the renewable energy sources (RESs), load demand and market prices, the probabilistic approach based on (2m + 1) point estimate method and ESSA is employed to solve the probabilistic EM problem. The proposed ESSA can be derived by introducing two modifications on the conventional salp swarm algorithm (SSA) to improve the balance between exploration and exploitation, speed up the convergence and avoiding the stuck in local optima of the SSA. The ESSA is employed to solve the deterministic and probabilistic EM with emission problem. Where the multi-objective optimization problem of cost and emission functions is transferred into a single objective function to minimize the total operating cost of the MG. The proposed ESSA is evaluated using a typical grid-connected MG with energy storage devices and compared with other methods. The results verify the superiority of the ESSA to solve the EM problem of the MG over other methods. • The probabilistic approach based on ESSA and point estimate method is proposed. • The proposed method is used to solve the deterministic and probabilistic EM of MG. • The EM problem considers minimization of cost and emission as a single problem. • The proposed method has been evaluated using a typical MG with different scenarios. • Results of all cases show the superiority of the proposed method over other methods. [ABSTRACT FROM AUTHOR]

The abundant geothermal energy in hot dry rock (HDR) formations is an attractive renewable energy resource with great potential. China will develop its first HDR geothermal formation in the Gonghe Basin. HDR is a hard and low-permeability granite containing very few fluids. Development requires fluids to cyclically flow between injection and production wells to extract geothermal energy in the artificial heat transfer zone. Hydraulic fracturing is the main technology for creating flow paths. But few studies have investigated fractures in HDR geothermal formations. This paper investigated fractures as flow paths in HDR geothermal formations during hydraulic fracturing. Hydraulic fractures were simulated using a custom true-triaxial hydraulic fracturing test system in a realistic formation environment, in which a scaled wellbore was used that was built in outcrop granite rock from the Gonghe Basin. Fracture creation in granite was investigated via experiments, as well as influence factors, and what experience could be achieved. This study can be used to design and evaluate hydraulic fracturing projects in potential HDR geothermal formations. • Hydraulic fracturing was simulated in high temperature via experiment. • Fracture creations were studied in outcrop granite of HDR geothermal formation. • In-situ stress and weak planes affects fracture propagation. • Custom designed pumping procedures can enlarge the heat transfer area. [ABSTRACT FROM AUTHOR]

The ocean plays host to a vast array of sources of energy. These energies simply need to be developed efficiently and effectively, as well as harmonized and collected. This paper will present and discuss two major sources of sustainable ocean energy—wind and wave—which can be combined effectively into one multi-purpose structure. These dynamic structures are emerging as useful in many international settings. However, the United States' (U.S.) areas are slow to adopt. This research presents a hierarchical analysis for decision makers to utilize in strategic offshore location planning with regard to these platforms. Surprisingly, the Gulf of Mexico (GOM) proves to be in a favorable position for entities considering use of such multi-purpose platforms. • Combinatory analysis of energy collection modes. • Provides a conceptual framework using a hierarchical analysis tool. • Optimal location decisions for U.S. coastal regions. [ABSTRACT FROM AUTHOR]

The increasing demand for energy from renewable sources is entailing the development of technologies oriented to increase the profitability of such projects and thus the attractiveness for potential investors. Wind power constitutes one of the most relevant renewable energy sources; however, the costs of the wind farms associated with Operations & Maintenance are prominent along the life-cycle. This paper proposes an approach intended to reduce these costs and lower the Levelized Cost of Energy. In this context, it is presented an opportunistic maintenance policy based on more accurate reliability estimates of the wind turbines components. The reliability of the components is estimated through a model based on Artificial Neural Networks that dynamically calculates the impact of operational conditions on the failures of the wind turbines. The approach has been validated through a case study based on real field data which proposes a multi-objective optimization of the maintenance strategy for the life-cycle of a wind farm. The obtained results provide interesting findings from the perspective of wind farms investors, operators, and owners. • Life-cycle approach for the maintenance management of wind farms considering operational environment. • Dynamic reliability model based on Artificial Neural Networks. • Comparison of several scenarios entailing different maintenance strategies and reliability models. • Case study based on real field data to see the benefits of the proposed approach. • Extensive experimentation and optimizations to validate results. [ABSTRACT FROM AUTHOR]

In this paper, the efficient salp swarm algorithm (ESSA) is proposed to solve the energy management (EM) with emission problem of renewable micro-grid (MG) including storage devices. Because of the uncertainties in the renewable energy sources (RESs), load demand and market prices, the probabilistic approach based on (2m + 1) point estimate method and ESSA is employed to solve the probabilistic EM problem. The proposed ESSA can be derived by introducing two modifications on the conventional salp swarm algorithm (SSA) to improve the balance between exploration and exploitation, speed up the convergence and avoiding the stuck in local optima of the SSA. The ESSA is employed to solve the deterministic and probabilistic EM with emission problem. Where the multi-objective optimization problem of cost and emission functions is transferred into a single objective function to minimize the total operating cost of the MG. The proposed ESSA is evaluated using a typical grid-connected MG with energy storage devices and compared with other methods. The results verify the superiority of the ESSA to solve the EM problem of the MG over other methods. • The probabilistic approach based on ESSA and point estimate method is proposed. • The proposed method is used to solve the deterministic and probabilistic EM of MG. • The EM problem considers minimization of cost and emission as a single problem. • The proposed method has been evaluated using a typical MG with different scenarios. • Results of all cases show the superiority of the proposed method over other methods. [ABSTRACT FROM AUTHOR]

The abundant geothermal energy in hot dry rock (HDR) formations is an attractive renewable energy resource with great potential. China will develop its first HDR geothermal formation in the Gonghe Basin. HDR is a hard and low-permeability granite containing very few fluids. Development requires fluids to cyclically flow between injection and production wells to extract geothermal energy in the artificial heat transfer zone. Hydraulic fracturing is the main technology for creating flow paths. But few studies have investigated fractures in HDR geothermal formations. This paper investigated fractures as flow paths in HDR geothermal formations during hydraulic fracturing. Hydraulic fractures were simulated using a custom true-triaxial hydraulic fracturing test system in a realistic formation environment, in which a scaled wellbore was used that was built in outcrop granite rock from the Gonghe Basin. Fracture creation in granite was investigated via experiments, as well as influence factors, and what experience could be achieved. This study can be used to design and evaluate hydraulic fracturing projects in potential HDR geothermal formations. • Hydraulic fracturing was simulated in high temperature via experiment. • Fracture creations were studied in outcrop granite of HDR geothermal formation. • In-situ stress and weak planes affects fracture propagation. • Custom designed pumping procedures can enlarge the heat transfer area. [ABSTRACT FROM AUTHOR]

To meet the future energy demand and avert any looming crises, efforts are being carried out to utilize sustainable and renewable energy resources. In this paper, the naturally occurring non-linearity and non-stationarity deficiencies within the climatological predictors to forecast solar radiation (Rdn) are resolved via a multivariate empirical mode decomposition method (MEMD). First, a set of antecedent weekly lags at timescale (t -1) of input datasets were collated and then were divided into training and testing subsets. The MEMD method is restricted to dissolve the training and testing climatic data independently into intrinsic modes functions (IMFs). As the numbers of total IMFs were very large, the singular value decomposition (SVD) algorithm is accustomed for dimensionality reduction simultaneously capturing the most relevant oscillatory features embedded within the IMFs. Finally, the random forest (RF) model is applied to forecast Rdn at selected solar-rich regions in Australia. The resulting hybrid MEMD-SVD-RF model was established as a consequence of the aforementioned modelling strategy. The results are benchmarked with other comparative models. The hybrid MEMD-SVD-RF model generates better and reliable forecasts having significant implications for renewable and sustainable energy applications and resources management. • A double decomposition based solar radiation forecasting model incorporating climate drivers. • Multivariate decomposition splits climate drivers into intrinsic mode functions (IMF). • Singular value decomposition reduces dimensionality to pertinent features from a pool of IMFs. • Random Forest (RF) algorithm used to design newly integrative hybrid model. • Hybrid model provides significant energy management implications. [ABSTRACT FROM AUTHOR]

Although it is widely accepted that renewable energy consumption is vital for environmental sustainability, the environmental effectiveness of individual renewable energy types is often overlooked. Therefore, this paper examined the multivariate relationship between disaggregated renewable energy (hydroelectricity, wind, solar and biomass) consumption, economic growth and environmental pollution for the period from 1991 to 2014 in G-7 (The Group of Seven) countries. The study used both augmented mean group estimator and panel bootstrap causality method to consider the cross-sectional dependence and country specific heterogeneity across G-7 countries. Empirical findings indicate that increasing biomass energy consumption was efficient to reduce carbon emission in France, Germany, Japan and the United States; increasing hydroelectricity usage was efficient to reduce carbon emission in Italy and the United Kingdom; wind energy consumption reduced emission in Canada and solar energy usage was efficient on reducing emission in France and Italy for observed period. Moreover, in case of panel, it is found that increasing hydroelectricity, biomass and wind energy consumption reduced carbon emissions while the impact of solar energy consumption is statistically insignificant in G-7 countries. In addition, the hydroelectricity consumption was found the most efficient renewable energy source to reduce environmental pollution for the panel of G-7 countries. • Disaggregated renewable usage consumption and carbon emission nexus is investigated. • Increasing hydroelectricity usage reduces emission in Italy, the UK and the US. • Increasing wind energy usage reduces emission in all G-7 countries excluding Japan. • The effect of solar energy consumption on emissions is statistically insignificant. [ABSTRACT FROM AUTHOR]

Offshore wind energy is recognized as an important source of renewable energy and has experienced rapid growth in recent years especially in north-western European countries. In this paper, the efficiency of 71 offshore wind farms across five north-western European countries is assessed using the Data Envelopment Analysis (DEA) Method. The number of turbines, cost, distance to shore, and area of the wind farms are selected as the inputs and the connectivity to population centres, the produced electricity and the water depth are considered as the outputs. The results show that the average CCR efficiency score of all offshore wind farms considered in this study is 87%, and the relative median efficiency of offshore wind farms in different countries is not statistically different. This study offers a practical and holistic performance assessment to the offshore wind stakeholders and policy makers via including economic, environmental, technical and social inputs and outputs in the analysis. • A benchmark study of the current status of European offshore wind farms. • The average efficiency score of 71 offshore wind farms across Europe is 87%. • Median efficiency scores across countries is not statistically different. [ABSTRACT FROM AUTHOR]

The article analyses the renewable energy implementation and prediction prospects examining the case of Lithuania. This paper presents the achieved results obtained by implementing the targets of National Energy Independence Strategy and requirements of the EU directives for EU Member States. It was disclosed that over the last 5 years, the share of renewable energy sources (RES) in gross inland fuel and energy consumption in Lithuania increased about 1.3 times. Gross domestic product (GDP) grew annually on average 3.2%. Country's GDP increased about 1.3 times and gross inland and final fuel and energy consumption – about 10–12%. The largest share of RES in Lithuania came from solid biofuels – 80.6% in 2017. For the last 5 years, wind energy production increased about 2.5 times and biogas energy consumption – about 2.8 times. Total emissions of greenhouse gasses decreased by 3% and air pollutants by 23%. Lithuania has set targets to increase RES share in the final energy consumption up to 30% by 2020, 45% by 2030 and 80% by 2050 years. The analysis identified the most promising directions for sustainable energy development and their environmental impact. That is also suitable for use in other countries, in order to provide local energy resources. • Main components of RES and tendencies of their usage in Lithuania were assessed. • Lithuanian energy policy has led to GDP growth of 1.3 times and annually on 3.2%. • Increase of gross inland consumption of RES from 15.8 to 20.4% is disclosed. • Decrease of total GHG emissions of 3% and air pollutants of 23% is estimated. • A target to increase RES share up to 30% by 2020 and 80% by 2050 was revealed. [ABSTRACT FROM AUTHOR]

Health centers and hospitals can be categorized as one of the major consumers of electrical energy in building sectors. Due to their competitive environment, they need to decrease their costs, including energy costs. On the other hand, environmental problems, lack of fossil fuels, and high energy consumption lead to using alternative energy generation methods like renewable energy sources (RESs). In this paper, we consider that the hospital can produce part of its energy from RESs for cost reduction and we implement demand dispatch energy program for using RESs efficiently. The challenge is that the main goal of hospital is providing health services not energy cost reduction. Therefore, we present a bi-objective formulation for using RESs in hospitals in a way to minimize costs and dissatisfaction by scheduling the activities of the hospital by considering hospital's specific constraints and limitations. With the help of the proposed model, hospitals will decrease energy costs while maintaining comfort of patients and surgeons at the same time. The model is solved using real data of a hospital in Iran, and sensitivity analysis on different parameters is done. The proposed model will cause reduction in energy cost of the hospital by implementing demand dispatch program for using RESs in the hospital. • Health centers are considered as a new type of energy consumers. • Wind turbines and solar panels are used for energy generation in hospitals. • Activities are scheduled in a way to minimize the cost and the dissatisfaction of patients and surgeons. • The limitations of hospitals are considered in the mathematical model. • The proposed model reduces energy use in peak hours and shifts the loads to time periods with renewable energy generation. [ABSTRACT FROM AUTHOR]

This paper presents the current trends and challenges related to the aging of renewable energy infrastructure and its visual impact, looking at case studies in California, United States. The first wind turbines installed in California are approaching the end of their life cycle. More than 30 years ago they created a new type of energy landscape – one based on renewable energy sources. Wind farms in particular dramatically change the image of the landscape and raise many questions concerning their aesthetic impact on the landscape. In theory, decommissioning would return a landscape to its pre-industrial character, but conducted research allowed to distinguish four scenarios for the transformation of aging wind energy infrastructure: (1) full decommissioning, (2) constant repowering (3) repowering preceded by full decommissioning, (4) transition towards a tourist attraction. Our research revealed that repowering after full decommissioning is a better solution than partial repowering for reducing the possible cumulative impact of wind farms, which typically consist of different wind turbine sizes and styles. Repowering done for large areas, over a relatively short timeframe, reduces the densely built-up industrial image of the wind farm, and allows for minimizing of the space occupied by wind turbines. • Investments in wind energy may have long-term impact on the landscape. • Decommissioning of aged infrastructure is usually followed by repowering. • Wind farms after repowering may cause more significant visual impact than before. • Repowering establishes industrial character of the renewable energy landscape. [ABSTRACT FROM AUTHOR]

Generation of hydrogen using electrolysis process with integrated renewable energy sources is highly important especially in environmental aspects. In this paper, we demonstrate that the enhancement of electrolysis performance of alkaline electrolysis stacks by diminishing the distance between electrodes, while changing the properties of the Membrane Electrode Assembly (MEA). Prior to that, the performances of mono-polar and bi-polar configurations of alkaline electrolysis stack are compared through 3-D modelling and experimental fabrication. At first, two different single cell alkaline electrolysers are designed using SolidWorks as a design software and the designed cell has been fabricated using an in-house 3D printer, to avoid post machining processes. Thereafter, the best performing cell is selected by considering the performance of both designs through different experiments. Finally, the performance of the selected cell is enhanced by changing the distance between electrodes and properties of MEA. Thus, the best performing cell has been selected for the fabrication process of mono-polar and bi-polar electrolysis stacks. At last, both mono-polar and bi-polar configurations of alkaline electrolysis stacks are designed and implemented to compare the electrolysis performance of both configurations by maintaining minimum electrode distance. The results imply that the electrolysis performance of the cell can be enhanced by reducing the distance between electrodes, and the designed bi-polar stack has a better performance in terms of the efficiency, power and flow rates than the mono-polar equivalent. • Alkaline electrolysis configuration (i.e. mono-polar and bi-polar) modelling for performance analysis. • Membrane electrode assembly (MEA) configuration effect on electrolysis performance. • Improvement of electrolysis performance with bi-polar stack compared to mono-polar equivalent. [ABSTRACT FROM AUTHOR]

The increasing demand of electricity has led to drastic use of renewable energy resources because of the scarcity and environmental effects of fossil fuel. Photovoltaic energy is one of renewable energy sources that emerges exponentially due to its environmentally friendly, operating and maintenance free, among other benefits. However, the main drawback of photovoltaic energy is its unreliability due to unpredictable nature of solar. Thus, this paper tackles a novel optimization technique based on multi-objective sizing of grid connected photovoltaic without energy storage systems. The objective aims at minimizing the total life cycle cost (TLCC) and energy purchased from utility grid while maximizing the reliability. In this study, the microgrid system reliability is expressed by the loss of power supply probability (LPSP). Mixed integer linear programming has been used to determine the decision variables which are the optimal number of photovoltaic panels and the hourly powers from utility grid. A case study has been done based on daily power demand of Engineering workshops at Jomo Kenyatta University of Agriculture and Technology (JKUAT). From the results obtained, the optimal number is 354 photovoltaic arrays, 0.6022 kWh is purchased from the grid from 7:00 h to 18:00 h, and the total life cycle cost of the project is found to be 191630$. The daily potential energy saving is up to 64.16%. • Mixed integer linear programming is used to determine the decision variables. • The optimal number of photovoltaic panels is 354. • The total life cycle cost is 191630 $ and daytime grid energy is 0.622 kWh. • The daily potential energy saving is up to 64.16%. [ABSTRACT FROM AUTHOR]

This paper deals with the internal dispatch policy for Hybrid Power Stations (HPS) consisting of renewable energy source (RES) based generation and storage facilities, operating in isolated island power systems in a coordinated manner to provide dispatchable power. Objective of the proposed dispatch method is the maximization of HPS revenues during real time operation, while avoiding deviations from the dispatch orders (DOs) issued by the System Operator (SO). DOs can be met either by RES production directly injected to the grid or by the storage facilities of the station. A Model Predictive Control (MPC) method is implemented to regularly update the internal dispatch decisions for HPS components, relying on an optimization problem built upon the Mixed Integer Linear Programming (MILP). In the proposed formulation the technical and operating constraints of the examined HPS configuration are taken into consideration, while a variable time resolution technique is also adopted to reduce computational complexity and achieve feasible solutions within acceptable time limits. • An internal dispatch method for HPSs contributes to their optimal management. • The variable time resolution approach achieves optimal solutions in reasonable time. • Exploitation of imbalance tolerances may increase revenues for the station. • BESS of high rated power and limited energy capacity improve operation of the HPS. • SoC variability penalization for BESS greatly improves battery life expectancy. [ABSTRACT FROM AUTHOR]

Forecasting of renewable energy resources and their output power is playing a key role to improve the grid energy efficiency by making some load generation management. Tidal currents output power is depending on the tidal currents constitutions (speed magnitude and direction) forecasting. The accuracy of the tidal currents forecasting models is very important especially when we deal with smart grid and renewable energy integration. Many models are proposed in the literature for tidal currents forecasting but most of the models are not able to control the requirements of the smart grid due to their accuracy. This paper is proposing hybrid approaches for harmonic tidal currents constitutions forecasting based on clustering approaches to improve the system accuracy. These hybrid models involve various combinations of Wavelet and Artificial Neural Network (WNN and ANN) and Fourier Series Based on Least Square Method (FSLSM) techniques. The proposed work is validated by using two different datasets; one for tidal currents speed magnitude and the other one for tidal currents direction as well as K-fold cross validation. Simulations results prove the importance of the proposed models to improve the system performance. The proposed models are tested based on actual tidal currents data collected from the Bay of Fundy, Canada in 2008. • Six different hybrid models are proposed for harmonic tidal currents forecasting. • The hybrid approaches are combinations of Wavelet, ANN and Least Square Method. • The most accurate hybrid model is the model of WNN and ANN with MAPE of 1.0322. • Two different datasets used (speed magnitude and direction) for work validation. • The proposed models are tested using data collected from the Bay of Fundy in 2008. [ABSTRACT FROM AUTHOR]

This paper investigates the local complementarity of three types of renewable sources (solar, wind and tidal). One of the main drawbacks of non-conventional renewable energy sources is their intermittent nature. Wind energy depends on the wind speed, which varies throughout the day. The generation of photovoltaic solar energy is strongly affected by clouds, that cause an abrupt drop of power to less than 50% of its rated capacity. In contrast, tidal energy is characterized by a high degree of predictability. This article raises important features of local complementarity of these renewable sources. These properties can be exploited to improve the firm power of isolated microgrids, leading to a variety of beneficial operational consequences. The contributions and conclusions presented here are supported by case studies and real data measured in the coastal region of northern Brazil. [ABSTRACT FROM AUTHOR]

The home energy management is an efficient tool to manage energy in the buildings that organizes different technologies and mathematical techniques to minimize energy cost. Home energy management often utilizes renewable energy resources to supply load demand in the building. Current home energy management systems utilize one or several of the available hardware-software capacity resources to deal with energy consumption in the buildings. However, a comprehensive model including various hardware and software capacity resources may increase the flexibility of the model. In this regard, this paper studies an efficient paradigm for home energy management in the building connected to electric grid. The proposed model forms an energy hub including the hardware resources (i.e., vehicle-to-home, wind turbine, and diesel generator) and software tools (i.e., demand response program). All the capacity resources and grid power are optimally adjusted to minimize the daily operational cost of the building as well as improvement of resiliency and self-healing. Wind energy and load uncertainty are modeled through stochastic programming. The seasonal pattern is considered for loads, prices, and wind energy. Simulation results demonstrate that operating all capacity resources minimizes the daily operational cost. When the wind energy, demand response program, vehicle-to-home, and diesel generator are not utilized, the cost is increased by 900, 230, 84, and 322%, respectively. It is also confirmed that the building not only can operate when one of the components is not connected, but also it is able to supply the demand under off-grid operation. • Home energy management is modeled on building connected to grid. • Building is supported by hardware and software capacity resources. • Demand response program, diesel generator, and vehicle-to-home are operated. • Wind and load uncertainty are incorporated by stochastic programming. • Resiliency and self-healing are studied following failures and events. [ABSTRACT FROM AUTHOR]

China's economy has flourished since reform and opening up. At the same time, China's ability to attract foreign investment in the world continued to increase. However, with the rapid development of the economy, China's energy crisis and environmental pollution have been continuously deepened, exposing increasingly serious problems in the energy consumption structure. As a critical mean to address the environmental problems and achieve sustainable development, the production and utilization of renewable energy resources is particularly critical. This paper aims to investigate the relationship amongst renewable energy consumption, foreign direct investment and gross domestic product in 31 Chinese provinces from 2000 to 2015. Specifically, the unit root test, cointegration test, vector error-correction model, impulse response function analysis, and Granger causality test are employed for the estimations. The empirical results indicate that there is a long-term and stable equilibrium relationship between gross domestic product per capita, foreign direct investment per capita, and renewable energy consumption per capita. Additionally, in the short term, foreign direct investment cannot significantly cause renewable energy consumption change; but in the long run, a modest slowdown in gross domestic product growth and targeted foreign direct investment will generate a significant boost on renewable energy in China. • Relationship amongst renewable energy consumption, GDP and FDI in China is examined. • Vector error correction model and fully modified ordinary least squares are employed. • Long-run equilibrium exists between renewable energy consumption, GDP and FDI. • There is unilateral causality from GDP and FDI to renewable energy consumption in the long run. • FDI cannot significantly cause renewable energy consumption change in the short term. [ABSTRACT FROM AUTHOR]

The current paper reflects on the challenges faced by European islands with regards to electricity supply, focusing on an island area of major interest, i.e. the Aegean Sea region. In this context, the main problems related to the use of imported oil and the associated high electricity production costs are discussed, together with the prospects of increased exploitation of Renewable Energy Sources (RES). For the latter accomplishment, the main elements of an integrated energy solution are presented, comprising mature RES technologies and more novel aspects, corresponding to energy storage, Demand Side Management and intelligent Energy Management on the basis of advanced forecasting techniques. Moreover, insight and preliminary operational evidence are provided with regards to the application of such an integrated solution on the island of Tilos, in Greece, where the development and test-operation of a pilot smart microgrid and Hybrid Power Station were recently completed, in the context of the TILOS Horizon 2020 Program. • A short review of the electricity production status in Aegean islands is undertaken. • Challenges and prospects of RES in the Aegean islands' region are discussed. • We present novel elements that can support increased RES shares for Aegean islands. • We focus on the development and pilot operation of Tilos island smart microgrid. [ABSTRACT FROM AUTHOR]

In today's world, where the demand for energy has increased and the supply/demand balance for energy has become increasingly difficult, the role of renewable energy is quite important. One of the most important sources of renewable energy in the world is the biogas, which offers great contributions to prevent environmental pollution and ensure ecological balance. Because Turkey has the necessary resources for the production of biogas, it is a popular country for the establishment of biogas production facility, which has a great importance from renewable energy sources. The aim of this study is appropriate city selection for a new biogas facility which will be an alternative to already existing biogas production facilities in Turkey. The study focuses on the identification of renewable energy potentials by evaluating 3 cities with rich and diverse characteristics in terms of biomass quantity. In this paper, a model with 12 criteria which affects the evaluation of the alternatives is proposed for selecting the suitable city in Turkey for biogas production with proposed solution method. In proposed methodology, the SWARA method, which uses the ranking of each decision maker, is used in the first phase of the solution in which the importance weights of the criteria in the model are determined. After obtaining criteria weights with SWARA method, for selecting appropriate city to establish a biogas facility, COPRAS method is used that is a one of multi criteria decision making method. The proposed model is showed by an illustrative example and the results are explained. • SWARA and COPRAS methods were integrated for a selection problem. • For a MCDM problem, the importance of the criteria was determined by SWARA method. • The alternatives were evaluated by COPRAS method. • The proposed hybrid method was applied to a sector problem that had never been applied before. [ABSTRACT FROM AUTHOR]

Variable renewables such as solar photovoltaics and wind power are key technologies for achieving the decarbonization of the power sector. However, they differ significantly from conventional power generation sources. As the share of variable renewables increases, these differences lead to numerous challenges in power systems. Failure to deal with these challenges may jeopardize power system reliability or the achievement of decarbonization targets. Various solution technologies are available to mitigate these challenges. The extant literature, however, lacks clarity on the scope of the challenges and the solution technologies to address them. This study provides a comprehensive overview of challenges and solution technologies among all domains of the power system. The interrelation matrix of challenges and solution technologies developed in this study provides important insights: First, solution technologies vary significantly in their potential to solve certain challenges. The solution potential of different technologies can therefore help prioritize solution technologies in addition to focusing on cost-effective options. Second, it is possible to identify groups of solution technologies that can help mitigate certain challenge groups. The categorization developed in this paper helps to better specify the need for specific solution technologies and enhances transparency of the complex process of renewable energy integration. • The study collects and structures challenges for the integration of renewables. • It collects solution technologies that are available to address these challenges. • It provides orientation on the scope and the potential of solution technologies. • This increases transparency of the complex process of renewable energy integration. [ABSTRACT FROM AUTHOR]

In recent years, the sun has been used as one of the main sources of renewable energy and supplying energy through solar cells has been quickly increased. This paper develops a two-echelon multi-period multi-product solar cell supply chain (SCSC) with three scenarios including (1) The presence of domestic supplier in a monopoly market, (2) The arrival of a foreign rival to the competitive market, and (3) The government intervention in a competitive market. Three scenarios under non-cooperative Nash game are modeled and formulated for two types of solar cells, dye-sensitized and perovskite. The obtained solutions of three scenarios from the game models are put in a mathematical model for a solar cell powerhouse. In this multi-period multi-product mathematical model, the degradation of the solar cells is considered. In the meantime, solar cell powerhouse as one of the end-users of solar energy deals with the degradation by substitution solar panels. The proposed model determines how many solar panels/modules from two kinds of it should be installed and substituted in each period and which scenario to be selected. Finally, it is represented a numerical example, sensitive analysis, and management insights for the proposed model. • Developing a two-echelon multi-period multi-product solar cell supply chain (SCSC) with three scenarios. • Studying three scenarios under non-cooperative Nash game for two types of solar cells (dye-sensitized & perovskite). • Considering the degradation of the solar cell in the mixed-integer mathematical model. • The results show that the government intervention along with applying subsidy and tax has the best performance. [ABSTRACT FROM AUTHOR]

Providing power to rural communities, which are far from the grid and suffer from lack of energy access in Africa, especially in Benin, in a sustainable manner requires the adoption of appropriate technology. This paper aims at analysing the techno-economic feasibility of hybrid renewable energy system (HRES) for sustainable rural electrification in Benin, using a case study of Fouay village. HOMER software is used to perform optimization, simulation and sensitivity analysis. The analysis showed that hybrid solar photovoltaics (PV)/diesel generator (DG)/battery (of 150 kW/62.5 kVA/637 kWh) is the least cost optimal system. This system ensures a reliable power supply, reduces battery requirements by 70% compared to PV/battery system and achieves 97% CO 2 emissions reduction compared to a conventional DG. Moreover, the study demonstrated that the most economical HRES depends strongly on the potential energy sources available at a location and power plant's remoteness from the beneficiary. In summary, as solar radiation is an abundant resource across the country, this hybrid PV/DG/battery system can be a suitable model to power remote areas in Benin, and we recommend it for future electrification projects in the country in place of the current widely deployed PV/battery system. • PV/DG/battery is the least costly system with a COE of $0.207/kWh. • HRES (PV/DG/battery) reduces battery storage requirements by 70%. • PV/DG/battery system has a short payback period of 3.45 years and a high IRR of 33.3%. • The robustness of the system is discussed by performing the sensitivity analysis. • Optimised HRES (PV/DG/battery) is economically more viable than grid extension. [ABSTRACT FROM AUTHOR]

In light of the latest regulations in the energy sector, renewable energy sources are quickly becoming more important. Among renewable energy sources, the one that has the greatest potential for use in Poland is natural and waste biomass. Application of solar energy to biomass thermal conversion methods e.g., pyrolysis, affords the opportunity for additional solar energy storage as well as amplification of the pro-ecological effect of the entire conversion process. Precise control of waste biomass pyrolysis via an investigation into the process thermodynamics, kinetics, and heat transfer phenomena allows to direct the reaction for production of desirable products, ranting reduction in of disposal cost of biomass, even sewage sludge. The goal of this study was to develop new design of laboratory-scale solar pyrolytic reactors to investigate the solar pyrolysis of waste biomass. Within presented paper, pyrolysis fundamentals, including process thermodynamics and kinetic principles, were reviewed. In addition, recently-developed, and artificial-powered solar pyrolytic reactors were discussed with a brief comparison of popular light sources for solar pyrolysis studies. After numerous consultations with artificial light sources producers and researchers, own design of a solar pyrolytic reactor is presented, along with a project development, preliminary experiment results and basic methodology for future studies. • Solar pyrolysis is promising way of waste biomass conversion, free of greenhouse gases emissions. • Pyrolysis principles with emphasis on process thermodynamics and kinetics are presented. • Proper kinetic modelling of biomass pyrolysis is crucial to predict feedstock behaviour inside the reactor. • Solar pyrolysis studies performed on artificial light reactors in last 20 years are discussed. • Finally, solar pyrolysis reactor powered by 1.6 kW xenon-arc lamp, reaching 500 °C at 85.5% of lamp power is presented. [ABSTRACT FROM AUTHOR]

Hydrokinetic energy has been mainly studied in areas where the principal driver of the current is the tide. However, in certain areas river discharges play also a principal role. The exploitation of the hydrokinetic resource in such areas has its own peculiarities, dictated by the combined influence of the two driving agents. The objective of this paper is to investigate the exploitation of hydrokinetic energy in the Miño Estuary, the largest estuary in NW Spain and N Portugal, with a focus on the site-specific performance of hydrokinetic energy converters (HECs) and its intra-annual variability. A state-of-the-art hydrodynamics numerical model is implemented and successfully validated based on field data. A third-generation HEC—to be more specific, the new Smart Freestream Turbine (SFT)—is considered, and its performance at the location with the greatest potential is assessed by means of: (i) site-specific efficiency, (ii) availability factor, and (iii) capacity factor. We find that, whereas the site-specific efficiency does not vary significantly, the availability and capacity factors do experience substantial intra-annual (seasonal) variability. In summer and autumn, river discharges are low, and the tide dominates the hydrokinetic resource. In contrast, during winter and spring, the river discharges significantly contribute to the resource, leading to a considerable increase in the availability and capacity factors. More generally, the results imply that in areas subject to combined fluvial and tidal influences the performance of HECs may depart significantly from that in tide-dominated areas, and this departure must be carefully weighed in assessing a project. • Hydrokinetic resource under influence of tide and river discharges is investigated. • River discharges induce a pronounced seasonal variability in the hydrokinetic resource. • The hydrokinetic resource is controlled to a large extent by the hydrological regime. • River discharges lead to a considerable increase in the performance during winter. [ABSTRACT FROM AUTHOR]

Economic emission dispatch (EED) problem of an electrical power system can be considered as one of the most popular constrained multi-objective optimization problems to minimize the cost and emission simultaneously subjecting to various constraints. Although many approaches have been presented to deal with this problem, it is still a challenge issue especially when more and more renewable energy sources such as wind power and solar power are incorporated into the system due to their intermittence and uncertainty. To improve the EED performance with those renewable power generations, a constrained multi-objective population extremal optimization algorithm called CMOPEO-EED is proposed by utilizing an advanced constraint handling technique, i.e., the superiority of feasible solution approach. To demonstrate the effectiveness of the proposed method, three versions of a modified IEEE 30-bus and 6-generator system with renewable power generations are considered as the test systems. The comprehensive experimental results and analyses fully validate that the proposed CMOPEO-EED method in this paper outperforms these recently reported single-objective success history based adaptive differential evolutionary algorithm (SHADE)-based EED method and constrained non-dominated sorting genetic algorithm-based EED (CNSGAII-EED) method in terms of cost and emission indices. Image 1002310 • Three cases of renewable power are incorporated for EED problem. • Superiority of feasible solutions is embedded in CMOPEO to handle constraints. • CMOPEO is developed firstly for multi-objective EED problem. • Three test systems illustrate its superiority to CNSGAII-EED and SHADE. [ABSTRACT FROM AUTHOR]

The coordinated control of Distributed Energy Resources (DER) allows the full exploitation of DER advantages. Smart Microgrids (SM) seem to be the best solution for the management of modern Low Voltage (LV) grids with DER especially for Non-Interconnected Greek Islands. The main purpose of this paper is to investigate the economic benefits that can be obtained from the coordinated control of DER and micro-Combined Heat and Power (mCHP) Units in SM operation. For each examined scenario, various market prices expressed by the System Marginal Prices (SMP) and DER-mCHP penetrations are considered for annual operation. All different cases are compared between them to determine which one is the most advantageous in terms of operational cost. A typical LV SM, standard DER units and typical market values have been considered to provide initial results. In addition, a sensitivity analysis is carried out in order to determine the effect of installed DER power on grid operation, such as in operating cost, power losses, power injected from the upstream distribution network, local DER production, etc. The presented results show clear the economic benefits in SM operation. • Technical and financial benefits from the Smart Microgrids (S_MG) as a result of DER and CHP coordination. • Economical evolution of Smart Microgrid operation in Non-Interconnected Islands. • CHPs and boilers in the S_MG scheme provides flexibility heat demand satisfaction and economic benefits for the consumers. • Fuel cells can support the integration of RES into electricity systems in Non-Interconnected Islands. [ABSTRACT FROM AUTHOR]

Load shedding has been a continuous challenge for the country on its way to advancement in industrialization and improvement in the living standard of its inhabitants. National energy mix is imported fossil fuel dominant affecting the buying options of the people. This paper proposes a grid-connected run-of-canal based micro-hydropower system and presents the designing of the proposed micro-hydropower system on the available head on a link canal between Balloki-barrage on the River Ravi and Sulaimanki-barrage on the River Sutlej. The electricity is to be used to supply the load of nearby villages and the surplus energy is to be fed into the nearby 11-kV grid while in peak hours, electricity is purchased from the grid. HOMER was used to verify the technical and economic feasibility of the proposed micro-hydropower project in meeting the load requirements. As the proposed system is only hydro resourced, HOMER performed optimization analysis and provided Net Present Cost (NPC) and the Levelized Cost of Energy (LCOE) of the proposed grid-connected micro-hydro system. Optimization analysis verified the validity of the proposed system based on the LCOE and the NPC. The system is expected to recover all the costs in the 5th year of the lifetime of the project. • A run of canal-based micro-hydropower project is proposed at the BS-link canal-I. • Designing of the proposed micro-hydropower project is presented. • Sensitivity analysis of the micro-hydro parameters is studied. • Optimization and economic analysis of the proposed micro-hydropower project is performed in HOMER. [ABSTRACT FROM AUTHOR]

Advancements in space technology have enabled the acquisition of reliable marine data, facilitating research on the potential of ocean renewable energy as an alternative source that can reduce dependency on fossil fuels, subsequently mitigating climate change. However, the ocean renewable energy development in Malaysia has not received adequate attention from local authorities and communities due to low resources in this area. Insufficient in-situ data, both in spatial and temporal dimensions, poses challenges in investigating the characteristics of ocean parameters, hindering a thorough study of the potential for ocean renewable energy development. Hence, this paper aims to identify potential ocean renewable energy development locations using the altimetry data and spatial-temporal clustering using the K-means technique. Theoretically, Malaysian seas are suitable for harnessing wind and waves with energy density ranges of up to 104.69 kW/m2 and 4.21 kW/m, respectively. This study enhances the understanding of Malaysian potential for ocean renewable energy, providing valuable information to stakeholders and the government to increase their interest in ocean renewable energy as a sustainable source for electricity generation in the future. [ABSTRACT FROM AUTHOR]

Wave energy is a significant source of renewable energy harnessed by wave energy converters (WECs). However, due to the relatively high levelised cost of energy (LCoE), wave energy has not attained a commercial stage yet. To minimise the LCoE, since the optimum (uncontrolled) WEC design typically differs from the optimum controlled WEC design, control co-design (CCD) techniques are essential. With CCD, the WEC control-related aspects are taken into account from the start of the WEC design phase and, ideally, the best control-informed WEC design is then achieved. This paper specifically focuses on CCD for an oscillating-water-column (OWC) WEC, equipped with a Wells turbine and a bypass valve. In essence, a parametric CCD approach is devised to find the optimum (control-informed) turbine rotor diameter, and bypass valve diameter, for the considered OWC WEC. In particular, the optimum design parameters minimise a 'simplified' LCoE, which is chosen as a suitable performance function. Despite the LCoE is primarily sensitive to the power take-off size, rather than to the bypass valve size, peak-shaving control with a bypass valve potentially increases the capacity factor and, consequently, can minimise the LCoE for small-to-medium sized turbines. • A parametric control co-design approach for an OWC with a bypass valve is devised. • A novel sea state based control approach for a bypass valve of an OWC is designed. • Peak-shaving control with a bypass valve potentially increases the capacity factor. • Peak-shaving control can minimise the LCoE for small-to-medium sized turbines. • LCoE is primarily sensitive to the PTO size, rather than to the bypass valve size. [ABSTRACT FROM AUTHOR]

The increasing penetration of renewable energy leads to seasonal fluctuation in the power system. This also results in continuous low-renewable-output events, which pose significant challenges for ensuring adequate renewable energy supply and arouse growing concern. To analyze the seasonal fluctuation characteristics of renewable in different timescales, this paper first decomposes the renewable time series into three components: climate, seasonal, and daily. Then an Itô process is introduced to model the climate and daily components considering the time series' stochastic characteristics and time correlations. Finally, the proposed model is first tested based on case studies on historical data from two selected weather stations in China. Moreover, the method is further applied to analyzing data from 253 weather stations across China at the provincial level. The results indicate that low-renewable-output events are more likely to have a longer duration in central China. [ABSTRACT FROM AUTHOR]

The design of effective and reliable solutions for Offshore Renewable Energy (ORE) technologies greatly relies on accurate metocean data. Uncertainties can significantly impact the design process. This paper presents a thorough evaluation of different bias-correction (BC) techniques applied to re-analysis datasets from diverse locations along the Spanish coast, presenting a multi-level evaluation procedure including novel, more appropriate statistical metrics beyond the traditional assessment techniques. First, the quality of raw ERA5 datasets is demonstrated to be rather poor, especially under extreme events, confirming the need for BC. Once the need is identified, results show that only the most sophisticated distribution-mapping BC techniques present the capacity to significantly improve the quality of the datasets, with the linearly-spaced Quantile-mapping (Q M) showing the best overall performance for power production conditions (PP), reducing the bias by over an order of magnitude. In contrast, the Gumble Quantile-Mapping (G Q M) outperforms the Q M in survivability conditions (Surv). However, when computing overall performance of BC techniques, the predominance of PP hinders the relevance of Surv. Hence, adapted metrics with a more realistic balance between the PP and Surv regions are suggested, which show a better suitability of G Q M providing more accurate estimations of the average power density and variability. [ABSTRACT FROM AUTHOR]

Modified natural ester (MNE) has significant potential for application in transformers as an environmentally friendly and renewable energy source. In comparison to natural esters, MNE offers notable advantages in terms of viscosity and power frequency breakdown voltage. However, the lightning impulse breakdown characteristics of MNE and the atomic-scale microscopic mechanisms related to its discharge characteristics remain unclear. Understanding the lightning impulse breakdown characteristics of MNE is crucial for ensuring the safe operation of transformers. In this paper, the density functional theory is used to calculate the change law of the microscopic parameters related to the discharge characteristics of MNE under the electric field under the action of electric field, so as to theoretically evaluate the lightning impulse discharge behavior of MNE. The results reveal that the electronic and geometric structures of MNE molecules are influenced by electric fields, which is the primary factor contributing to the variations in microscopic parameters under different electric field strengths. As the electric field intensity increases, the dipole moment of MNE tends to increase, while the ionization potential and excitation energy of MNE tend to decrease. The decrease of ionization potential, excitation energy and energy gap of MNE molecules is about 6.61%–68.01%, 4.34%–47.66% and 2.01%–69.23%. By comparing the calculated results of mineral oil, natural ester, and MNE microparameters, it can be inferred that the lightning impulse breakdown behavior of MNE is similar to that of natural ester and lightning impulse breakdown voltage of MNE is higher than that of natural ester but still lower than that of mineral oil. The average negative polarity lightning impulse voltages of MNE, natural ester and mineral oil in the 85 mm oil gap are about 245 kV, 199 kV and 304 kV, respectively. The test results confirmed the simulation conclusions. This study provides robust theoretical support for understanding the lightning impulse breakdown characteristics of MNE and ensuring its safe operation in transformers. [ABSTRACT FROM AUTHOR]

The renewable energy system can stimulate more dynamics and increase the possibility of the oscillatory instability. The dynamic model becomes significantly complicated due to the large numbers of grid-connected renewable energy systems and time-varying features of their control parameters. Therefore, it is critical to investigate the various oscillations of renewable energy systems preferably without the high-dimensional dynamic modeling. The existing monitoring-based methods cannot provide the mechanism analysis of emerging oscillations or quantitative analysis of the damping feature of oscillations of renewable energy systems. In this paper, firstly, the generalized oscillation loop is designed based on the second-order differential operations of a concerned control loop of a renewable energy system to analyze the mechanism of the emerging oscillation associated with this control loop. On this basis, a generalized energy flow analysis is proposed for the quantitative analysis of the damping feature of oscillations in this control loop. Then, taking the grid-side control loops of the full converter-based wind generation system as an example, the key physical quantities of emerging oscillations are further derived and the damping feature assessment of concerned oscillations is conducted. Finally, the developed methodology is verified to investigate the various oscillations of the full converter-based wind generation system in the case studies. The results demonstrate that the eigenvalues of concerned oscillations can be accurately estimated through the generalized energy flow analysis without the whole grid modeling; additionally, the oscillatory stability of a RES can be enhanced by improving the damping performance of emerging oscillations with the help of the mechanism analysis, which lays a foundation for setting converter control parameters and configuring additional damping devices. [ABSTRACT FROM AUTHOR]