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The distribution of ground thermal conductivity (λ s) is a significant consideration for the design of ground source heat pump systems. This paper proposed a new method to estimate the layered λ s for U-tube borehole heat exchanger (BHE) using particle swarm optimization (PSO) and distributed thermal response test (DTRT) data. Firstly, a quasi-3D heat transfer model considering geothermal gradient for U-tube BHE had been built to simulate fluid temperature profiles. And the experiment in DTRT was performed using a 45 m sandbox. Then, the layered λ s were estimated through PSO and DTRT data based on the established model. The results showed that the convergent λ s distribution could be reliably obtained by short-term DTRT. Furthermore, the estimation results are independent of the number of layers and data points. The mean difference in λ s distribution between 9 layers and 45 layers is 0.007 W/(m∙K) and the layered λ s also could be obtained when the number of layers is more than the number of temperature data points, and the root mean square error between 30 and 220 points is less than 0.3 W/(m∙K). • Quasi-3D heat transfer model for U-tube BHE is built to estimate layered λ s. • Sensitivity analyses were conducted to investigate parameter impacts. • Novel estimation of layered λ s is presented by using DTRT data and PSO. • Short-term DTRT data is efficient to estimate the layered λ s. • Estimation is independent with layered conditions and number of test points. [ABSTRACT FROM AUTHOR]

In this paper, we utilized a eutectic gallium-indium liquid metal (LM) with high thermal conductivity to immerse carbon-based phase change material (PCM) capsules to acquire a PCM-LM composite. This produced a scalable, thermally stable, mechanically reliable, high thermally conductive, and leakage-free material. This composite was then applied as a heat mitigator for CPU cooling. Results demonstrate that clear improvements could be made compared to traditional pin-fin heat-sink cooling. Here the continuous full-load operating time could be prolonged by 414.3%. Moreover, the temperature difference between the idle and full-load operating states could be significantly decreased, and prevent damage from thermal stress. Significantly, a 23% energy-saving performance was attained because of the thermal buffering effect and high responsive ability of the composite. Guidelines for an effective match between the heat absorption of the composite and the heat generation from the CPU could also be established. Here the proposed PCM-LM composite can be applied to other PCM-based energy storage industries and efficient temperature control applications, contributing to carbon neutralization and global warming mitigation. [ABSTRACT FROM AUTHOR]

Uncertain parameters and factors substantially impact the operational performances of combined cooling, heating, and power (CCHP) systems. This paper constructs a chance-constrained programming model for system design and energy dispatch management of a hybrid solar CCHP system under the uncertainties of solar energy and building loads. The uncertain scenarios with probability distributions are generated in the Latin hypercube sampling and clustering methods. The chance-constrained model transforms stochastic optimization into deterministic optimization based on these scenarios. Then, the multi-objective optimization model of CCHP system considering the performances of economic, energy, emission, and flexibility is established, and the modified ε -constraint method is employed to obtain Pareto solutions. A case study validates the proposed model. The capacities and operational strategies of components in the hybrid CCHP system are optimized, and the impacts of the confidence level of probability distributions of uncertain factors on the optimization results are discussed. The results indicate that the photovoltaic capacity in the hybrid CCHP system declines by 87.5% when the confidence level increases from 0.50 to 0.99. But other components' capacities are raised, and the gas turbine capacity as the key component rises by 10.49%. The energetic and environmental performances of the CCHP system rise with the confidence level, and the operation safety is improved. [ABSTRACT FROM AUTHOR]

Integrated energy systems (IES) with renewable energy systems (RES), carbon capture systems (CCS) and energy storage systems (ESS) are considered efficient in supporting the low-carbon energy supply with both economic and environmental benefits. Effective energy management is required to ensure the economical, environmental and reliable operation of the IES. However, the optimal IES operation is considered a non-trivial task due to the renewable generation uncertainty and the optimization of multiple contradictory objectives (e.g. economic, environmental and risk costs). This paper aims to provide a multi-level optimization model for the real-time optimal IES operation consisting of RES, ESS and CCS. This work quantifies the uncertainty by the Conditional Value at Risk (CVaR) theory in the optimization model. The uncertainty is further reduced by improving the operation strategy through a model predictive control (MPC)-based method. Also, the multi-objective optimization model is adopted to minimize the economic cost, carbon dioxide emissions (CDE) and primary energy consumption (PEC) for optimal energy scheduling in the intra-day stage. Based on the result of the intra-day stage, the feedback correction model is applied to adjust the schedule to balance the difference between the forecasting and actual values. Numerical results show that the proposed solution can provide the trade-off between economical and environmental performance. Through ablation experiments, the proposed method with feedback correction can carry out demand response with lower costs, CDE and PEC. The proposed solution is further confirmed with outperformed performance compared with single-objective optimization methods and other stochastic optimization methods. In addition, a robustness analysis is conducted to quantify the benefits of RES, ESS and CCS in IES. [ABSTRACT FROM AUTHOR]

A Trombe wall with thermal catalytic blinds (TC-Blind/TW) for indoor heating/cooling, air purification and shading was proposed. In this paper, we has fully explored the advancement and feasibility of the system from thermal catalytic material preparation and performance testing, system construction and system steady state experiment testing, system heat-mass transfer model establishment and verification, and finally to the analysis of system operation strategy. The main conclusions are as follows: Firstly, thermal catalytic material MnO x -CeO 2 behaved excellent heating and purification performance, the formaldehyde degradation followed L-H model. Secondly, the thermal efficiency and formaldehyde single-through conversion of system during the daytime were between 35%-55% and 32%–42%, respectively. Thirdly, the established heat-mass transfer model had the high accuracy, with the maximum RSMD of 0.8%. Finally, the blinds turning angle has a great influence on the system performance, then the optimal annual operation angles in four cities were suggested. Take Beijing as an example, the annual generated clean air was 11355.6 m3/m2, the reduced heating and cooling loads were 341.2 and 318.3 MJ/m2, respectively. [ABSTRACT FROM AUTHOR]

Thermal stratification in a storage tank is an important factor affecting hot water output. There are many factors affecting thermal stratification, and the initial temperature in the tank is a notable one. In this paper, a typical solar hot water storage (HWS) tank, which is widely used in practical applications, has been selected to study numerically the effect of the initial temperature on the thermal stratification under the discharging mode. The flow mechanism, temperature distribution, thermal stratification, and thermal mixing mechanism in the tank are analyzed with the numerically simulated results for five initial temperatures in the tank. In addition to the qualitative observation, a quantitative analysis of the effect of the initial temperature in the tank has also been conducted in terms of several key dimensionless parameters which quantify the extent of the thermal stratification in the tank. The results show that the dimensionless exergy decreases with the dimensionless time. When the dimensionless time increases from 0.1 to 0.8, the dimensionless exergy decreases by nearly 0.4. Additionally, a higher initial temperature leads to a smaller extent of the initial mixing and a larger output rate of hot water. When the initial temperature in the tank increases from 313 K to 353 K, the output rate of hot water increases by nearly 11%. Moreover, the extent of the thermal stratification increases almost linearly with the initial temperature in the tank. When the initial temperature in the tank increases from 313 K to 353 K, a 17% increase in the thermal stratification has been achieved indicating that the initial temperature in the tank has a significant effect on the thermal stratification, which will be insightful for the better design of solar hot water systems. [ABSTRACT FROM AUTHOR]

The map of radiative cooling potential shows that the radiative cooling power can reach up to 100 W/m2 for its application in different climatic zones. However, the effect of building deployment on the city-scale application of radiative cooling is generally ignored in majority of existing studies, which overestimates the cooling benefit. This paper investigates the cooling benefit of implementing radiative cooling on a city-scale by considering building deployment. To determine the effect of building deployment on the radiative cooling potential, the city of Xi'an in China is modeled using COMSOL and verified with real weather data. Then, the thermal response of buildings with radiative cooling envelopes is discussed in detail. Finally, carbon emission reduction is derived at the city-scale by applying radiative cooling considering building deployment. The results show that the estimated radiative cooling power is approximately decreased by 14.7% for the ideal broadband surface and 47.1% for the ideal selective surface on the selected day by considering building deployment on a city-scale. Furthermore, carbon emission reductions of 0.52 gCO 2 /(m2⋅h) and 0.16 gCO 2 /(m2⋅h) can be achieved from the roof and walls on the selected day by applying radiative cooling material on both the roof and walls. This study can provide guiding significance for the large-scale application of radiative cooling in cities. [ABSTRACT FROM AUTHOR]

The oscillating-water-column (OWC) system is one of the most developed wave energy conversion technologies, and several prototypes have been deployed and tested on the sea. Noise emission is essential to this technology's long-term environmental impact assessment. The power take-off system of an OWC comprises a self-rectifying air turbine that directly drives an electrical generator. The paper compares the noise emission of a biradial turbine with that of a Wells turbine. The noise emission of the biradial turbine was measured at the Instituto Superior Técnico variable-flow test rig, while the Wells turbine data were collected in the literature. Acoustic measurement procedures followed the guidelines of the ISO 3746 Standard. A definition of specific noise level is used to compare the noise emission from geometrically similar air turbines or other air turbines performing the same duty. The results show that the noise levels of the biradial turbine are significantly lower than those of the Wells turbine at off-design conditions for the same pneumatic power. • Methodology for measuring noise emission from air turbines. • Experimental characterisation of the acoustic emission of a biradial turbine. • Use of a specific noise level to compare air turbines. • Comparison of noise emission of a biradial turbine with a Wells turbine. • Wells turbines are significantly noisier than biradial turbines at off-design conditions. [ABSTRACT FROM AUTHOR]

Achieving large-scale commercial exploitation of ocean wave energy inherently encompasses the design and deployment of arrays of wave energy converters (WECs), in an effort to reduce the associated levelised cost of energy. In this context, understanding the interactions between devices in a controlled WEC array is hence essential to achieve optimal layout configurations, as well as to provide guidance on the area required for array installation, reliability, life-time, and overall cost of the farm. Successful achievement of these vital objectives for the wave energy industry has been constantly aided by the use of appropriate numerical models. Regardless of the specific modelling approach adopted, model reliability is always a major concern: Numerical models need to able be to represent reality to be useful in supporting the different stages of development, hence providing significant results for decision making. To test reliability of a model, experimental results are an invaluable asset for validation. Recognising the striking absence of real-world data concerning arrays of WEC systems, and its inherent value for model validation and data-based modelling purposes, we present, in this paper, an experimental campaign fully conducted with the sole objective of generating and providing an open-access dataset on WEC farms: SWELL (Standardised Wave Energy converter array Learning Library). The generated dataset, included alongside this manuscript, comprises an approximate total of ∼ 3000 variables and more than ∼ 1 0 8 datapoints, for up to 5 devices in 9 diverse WEC array layouts with different levels of interaction, and 19 carefully selected operating conditions. Four different categories of tests are considered, providing measures of key variables required for model validation and data-based modelling tasks. As such, SWELL provides a crucial resource to achieve confidence in numerical modelling, helping towards creating reliable tools for decision making in the WEC field, hence effectively supporting the pathway towards effective commercialisation of ocean wave energy. • Current absence of real-world data concerning arrays of WEC systems. • Experimental campaign to generate an open-access dataset on WEC arrays. • Up to 5 devices in 9 diverse layouts, and 19 operating conditions. • Four different tests, ∼ 3000 variables, and more than ∼ 10 8 datapoints. [ABSTRACT FROM AUTHOR]

To improve the renewable energy sources (RES) utilization of isolated microgrids (IMG) in frequency regulation process, an adaptive frequency regulation strategy with high renewable energy participating level is proposed in this paper: 1) an adaptive droop control method is conceived for primary frequency regulation, in which the designed droop coefficients are adjustable with the real-time wind velocity and state of charge (SoC) of energy storage units (ESUs); as the most important contribution, 2) a general flexible model predictive control (FMPC) framework with adaptive cost function and constraints is developed for secondary frequency regulation. For 2), i) the weight coefficients of the cost function can be adaptively adjusted according to frequency deviation through a pre-designed intelligent function, in which the specification of determining the key parameters is involved; ii) the designed constraints' boundaries can dynamically shift with wind velocity and ESU's SoC; iii) the negative impact of model's uncertainties can also be mitigated by implementing the proposed FMPC. Finally, the effectiveness of the proposal is verified by the comprehensive simulation and experimental study, and the results show that the proposal can significantly improve RES's utilization level while guaranteeing frequency regulation performance and operation safety in IMG. [ABSTRACT FROM AUTHOR]

High performance of HVAC connected Building Integrated Photovoltaic/Thermal (BIPV/T) systems relies on appropriate control. However, optimal control is often overlooked, resulting in systems that operate inefficiently. This paper investigates how model predictive control (MPC) can improve the operation of open loop air-based BIPV/T systems connected to multiple thermal applications. The BIPV/T system at the first institutional net-zero energy building in Canada, the Varennes library, is used as an archetype. The BIPV/T covers 16% of the south-facing roof and operates under a simple rule-based control strategy. The developed control and design strategies consider variations of this system, to achieve higher thermal utilization efficiency. A control-oriented BIPV/T model is developed and calibrated using monitored data. The BIPV/T airflow is regulated through MPC for simultaneous heat supply to an Energy Recovery Ventilator and air-to-water heat pump. The BIPV/T air flow is efficiently controlled, considering the connected thermal applications, environmental conditions, and PV temperature. Model-based control for BIPV/T systems can increase the amount of useful heat and reduce PV overheating. The MPC controller for the examined system reduced the building energy consumption compared to the business-as-usual operation by 40% and together with increased BIPV/T area can supply excess heat to adjacent buildings. [ABSTRACT FROM AUTHOR]

This research investigates the asymmetric impact of renewable electricity energy usage and industrialization on the environmental sustainability of South Africa. The load capacity factor (LF) is a more extensive measure of environmental deterioration when compared to carbon emissions and the ecological footprint, which cover a range of both the demand on and supply of nature. The series dataset used for the empirical analysis spans between 1990 and 2019. The study also investigates the effect of human capital, industrialization, and economic growth on load capacity factor. The result of the NARDL estimator reveals that the increase in renewable electricity energy usage increases LF in the long and short term. However, the decline in renewable electricity energy usage has a neutral impact on LF. Furthermore, the results indicate that industrialization and economic growth impact LF negatively. Lastly, human capital improves environmental quality due to the increasing effect on LF. The spectral Granger causality approach outcomes show that all the parameters can forecast load capacity factors in the long term. Some policy implications, restrictions, and potential future study pathways have been explored in light of this paper's results. • The nonlinear autoregressive distributive lag is employed. • Asymmetric impact of renewable electricity consumption on environmental sustainability. • A broad environmental indicator is used, load capacity factor. • The positive change in renewable electricity consumption promotes environmental sustainability. [ABSTRACT FROM AUTHOR]

As the solar energy utilization technology for renewable clean energy, actual parabolic trough receivers are subject to tracking errors and absorber tube installation errors, and the bellows and Kovar ring under these errors have a significant impact on the receiver's safety. Based on the MCRT-FVM-FEM principles in this paper, a receiver's optical-thermal-stress mathematical model is modeled and the thermal-stress performance and safety of the receiver's key components under two errors are evaluated. The correlation between the bellows and Kovar ring's performance and the two errors is analyzed. The results demonstrate that the lower tracking errors and larger installation errors markedly increment the absorber's deformation and have a negative impact on the receiver safety. Bellows and Kovar ring's asymmetrical temperature distribution causes variable swell and uneven stress under tracking and installation errors. Temperature gradient variation of bellows is more sensitive under errors than Kovar rings. Kovar ring's compressive stress rises substantially as the Y-directional installation error varied from −15 mm to 15 mm compared to other errors. With tracking errors exceeding 8 mrad, bellows' tensile stress and Kovar ring's compressive stress diminish under installation error. Thus, larger tracking errors significantly reduce the threat to the receiver when installation errors exist. [ABSTRACT FROM AUTHOR]

With the high penetration of renewable energy, its intermittency and volatility also bring challenges to traditional power system such as maintaining reliable operation of system and improving the utilization of renewable energy. Under the background of Energy Internet (EI), energy router (ER) emerges as the times require. Aiming to improve the ability of support of energy storage units to DC buses and suppressing power shocks both inside and outside the ER, in this paper, an ER based on multi-hybrid energy storage system (MHESS) is proposed. As the principle of maximizing the utilization of renewable energy, a corresponding energy coordinated management strategy is proposed. Charging/discharging timespan optimization model is established to ensure MHESS as available as possible. The reference power of MHESS is allocated based on the proposed optimization model. Simulation analysis of different working conditions in 4 operation scenarios are carried out and the results show that the power oscillation on different buses of ER can be dampened within 0.1s and the bus voltages fluctuate within 2% while operation scenarios are switched, which verifies the feasibility and effectiveness of the proposed energy coordinated management strategy. [ABSTRACT FROM AUTHOR]

Over the last two decades, there has been a significant interest in developing solutions to improve the efficiency of power systems, such as optimal energy consumption and management. The demand response programs (DRP) have long been one of the most effective strategies to encourage consumers to change their consumption behavior. In this paper, a novel hybrid DRP has been implemented by combining the time of use (TOU) and incentive-based (IB) DRP methods. To meet the load demand, a PV-WT-BESS hybrid renewable energy system (HRES) has been proposed in this work. Further, to analyze the impact of hybrid DRP on the capacity allocation of different system components, optimal sizing has been performed in two scenarios, one with the actual load and the second with the load after considering the hybrid DRP. The optimization has been carried out by using an improved search space reduction (ISSR) algorithm. To demonstrate the effectiveness of the ISSR algorithm, the obtained results are compared with other algorithms such as particle swarm optimization (PSO), grey wolf optimization (GWO), teaching-learning based algorithm (TLBO), seagull optimization algorithm (SOA), and sine cosine algorithm (SCA). Finally, a novel energy management strategy (EMS) is also proposed in this work on the supply side of the HRES, which intelligently uses the variations in the grid tariff to charge the BESS when the tariff is low. To demonstrate the proposed DRP and EMS-based sizing, a case study has been performed for a grid-connected PV-WT-BESS for the location of Kanyakumari, India. From the results obtained, it has been concluded that the hybrid DRP reduces the peak demand up to 5%, which reduces the levelized cost of energy (LCE) by 22%. Furthermore, the proposed novel EMS reduces the LCE further by 5%. The overall cost reduction of up to 25% has been achieved by using both the proposed hybrid DRP and EMS, while satisfying all necessary constraints. [Display omitted] [ABSTRACT FROM AUTHOR]

Porous discs are the experimental counterparts of the numerical actuator disc concept and are frequently used in wind tunnel studies to reproduce the far-wake characteristics of wind turbines. The potential of using porous discs instead of wind turbines comes with the benefits such as operational easiness and design simplicity. This paper presents the results of an experimental study focusing on the wake development characteristics of a single porous disc and a single wind turbine under different freestream turbulence intensities but at similar Reynolds number conditions. The measurements are performed using two-dimensional two-component particle image velocimetry (2D2C PIV) technique up to seven diameters downstream distance in the wake of the models. The wake flows are analyzed in terms of the development of mean wake velocity deficit, wake decay, and wake turbulence characteristics. The results show that the wake recovery occurs faster for both the porous disc and the turbine with increasing freestream turbulence intensity. The wake width increases with the freestream turbulence intensity, indicating faster diffusion of the wake for both models. On the other hand, the wake width of the porous disc and the turbine is similar at the same turbulence intensity conditions, although they operate with slightly different thrust coefficients. Turbulent kinetic energy profiles in the far wake of the porous disc and the turbine, which are significantly different for the low turbulence intensity conditions, become similar for the high turbulence intensity case. The comparison of the turbulent kinetic energy, decay rate and production characteristics points to different turbulence mechanisms in the wake of the porous disc and the turbine. In the near wake, the wake decay rate and turbulent kinetic energy levels are higher in the porous disc case due to enhanced mixing levels associated with the grid-generated turbulence. In the far wake, the decay rate of the turbine wake is higher, most probably due to the breakdown of the tip vortices. When the freestream turbulence is increased, the differences in the turbulent wake flow characteristics diminish in the far wake, particularly after a 4.5-diameter downstream distance. [ABSTRACT FROM AUTHOR]

The paper analyses the spring-like air compressibility effect in coaxial-duct oscillating-water-column (CD-OWC) wave energy converters (WECs). This is accomplished through a novel non-linear time-domain model for OWC WECs implemented in the object-oriented language Modelica. Good agreement was observed between numerical and physical model testing results. The air chamber volume significantly affected the spring-like air compressibility effect and the converter performance. Another significant factor is the damping level of the power take-off system. Both fixed and floating CD-OWC versions were numerically investigated, focusing on the compressibility effect. Differences were found mainly due to the additional degrees of freedom in floating configurations. In general, numerical and experimental results showed that air compressibility might positively or negatively affect device power performance in regular waves, depending on whether the frequency is within or out of an interval defined by critical frequencies. Some particular points were observed and categorised as Equicompressum Nullum and Equicompressum critical points, representing different characteristics. Knowledge of these critical values might be important in OWC control. Finally, some applications of the CD-OWC concept are discussed, including considerations on the power output level provided by biradial and Wells air turbines. • A new time-domain model for OWCs implemented in Modelica language is presented. • Air compressibility effects in fixed and floating CD-OWCs were investigated. • Regions of positive and negative compressibility effects were identified. • Two types of Equicompressum critical points were found. • Air turbine selection and Blue Economy applications for CD-OWCs are discussed. [ABSTRACT FROM AUTHOR]

Pumped hydro energy storage (PHES) can effectively alleviate the renewable curtailment and resource waste caused by expansion of wind and solar-based renewable energy (RE) sources. However, the influences of regional hydrological characteristics, operational characteristics of PHES units, and power supply-demand balance on the regulating effect of PHES have been neglected. In this paper, an improved hybrid power system dispatch model (Dispa-set) that considers regional hydrological characteristics, unit operational characteristics, and RE curtailment penalty is proposed. The potential and limitations of PHES on reducing renewable curtailment and carbon emissions in four Northwest provinces (FNP) during the 14th Five-Year Plan (FYP) are evaluated through 6 sub-scenarios. Studies have shown that increasing PHES can effectively reduce renewable curtailment and carbon emissions, but uncoordinated development of PHES and RE results in resource waste and slows down carbon reduction. For example, a 10% increase in PHES during the 14th FYP could increase renewable curtailment in Qinghai by 1.1% and CO2 emissions in Gansu by 0.05%, due to uncoordinated development, demand for electricity supply, and regulated power sources. Therefore, combining PHES development with regional hydrological and operational characteristics is essential to achieve coordinated development with RE and unlock technology, economic, and environmental benefits. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach for detection and diagnosis of the rotor imbalance types pitch misalignment, yaw misalignment and mass imbalance by monitoring the drivetrain vibration response. Traditionally, only SCADA signals including nacelle accelerations, rotor speed and electrical power are utilized for this purpose, while drivetrain condition monitoring signals are mainly used for fault detection in gears and bearings. A diagnostic method is proposed using statistical change detection methods for fault detection, phase angle estimation for localizing the faulty blade, and physics-based decision criteria for fault classification. The proposed method is tested in a numerical case study with aeroelastic and drivetrain multi-body models of the 10 MW DTU reference wind turbine. The results suggest that drivetrain condition monitoring signals are particularly beneficial for detecting and diagnosing pitch misalignment, since this fault type uniquely induces periodic out-of-plane bending moments that excite drivetrain bending modes. Drivetrain signals improved the detection rate of a 1° pitch error from 19% to near 100% and reduced the standard error in locating the faulty blade from 71. 5 ° to 11. 2 °. In addition, by using drivetrain vibration amplitudes as a decision criterion, all considered pitch error cases are correctly distinguished from other fault types. • Drivetrain CMS outperform SCADA signals for the diagnosis of pitch misalignment. • The detection rate of a 1° pitch error is increased from 19% to near 100%. • The standard error in locating the faulty blade is reduced from 71.5° to 11.2°. • All pitch errors are correctly classified regardless of environmental conditions. [ABSTRACT FROM AUTHOR]

The tragedy of the depletion of natural resources led by their overconsumption has posed severe deleterious effects on humanity and the environment. Post-consumption-led waste has worsened the situation, given that unregulated and unscientific waste treatment furthers the criticality of ecological dilapidation. To curb ecological overshoot and restore the full capacity of ecosystem services, we need to focus more on recycling the available resources at their maximum capacity. In other words, we must take a U-turn from the linear economic system to the circular one. The issue is that the number of real-world data-driven scientific studies is very scant in this sphere of literature. Against this milieu, this paper scrutinizes the effect of a circular economy on CO2 emissions intensity among a panel of the top seven CO2 emitters of the world. We have used data from 1990 to 2020 and applied the Augmented Mean Group (AMG) technique to reach our empirical conclusions. By controlling for globalization and renewable energy consumption, we unveil that municipal waste, a crucial component of the circular economy, is positively entangled with CO2 emissions among the designated nations. This observation further reiterates the theoretical underpinning and urges to harness municipal waste as a valuable raw material for a circular economy. Moreover, we disclose that economic growth and globalization boost CO2 emissions intensity among the designated nations. Contrarily, the consumption of renewables helps uplift environmental integrity. Our conclusions also hold after the robustness check. Further, the D-H causality test establishes a bidirectional causality between municipal waste and CO2 emissions. One-lane causality is also observed from a linear economy to a circular economy. More specifically, municipal waste is observed as a critical determinant of pollution and carbon emissions. In light of the findings, the authors provide novel policy recommendations apropos sustainable development goals. [ABSTRACT FROM AUTHOR]

This paper proposes a rotating piezoelectric energy harvester for automotive motion (PEH). A mechanical tuning method is used to optimize the output performance of the harvester, including changing the tip mass of the piezoelectric cantilever beam and the base mass. The motion state and natural frequency were analyzed by simulation. An electromechanical coupling model was established through Hamilton's principle and Bernoulli beam theory to theoretically analyze the movement state of the PEH. The power generation performance of PEH under different environmental excitations was tested by experimental methods, and the effect of self-excited vibration on its power generation performance was investigated to test the output variation of the system under different speed changes. Experiments show that when the pulse frequency of the stepper motor is 1700Hz, the tip mass of the piezoelectric cantilever beam is 5.6g, the rotation angle of the support is 0°, the counterweight of the base is 31.6g, and the resistance is 1kΩ, respectively, the harvester output power can reach 6.25 mW. Finally, Finally, the future development of harvester is discussed. [ABSTRACT FROM AUTHOR]

Using daily data from the beginning of 2018 to the end of 2022 and the Seemingly Unrelated Regression method, this paper sought to determine the relationship between green and non-green cryptocurrency indices as representative of blockchain technologies on three green bond indices in two periods before the outbreak of COVID-19 and the corona period. The preliminary results confirmed that by spreading the coronavirus, the sensitivity of the green bond market has increased to the gold index. In addition, the green cryptocurrency index (Cardano) significantly impacts green bonds more during the Corona era. The negative effect of the Bitcoin index on the index of green bonds in the Corona era is less than its adverse effect in the pre-corona period. Developing green cryptocurrencies and linking cryptocurrencies and digital green financing are two significant recommended policy implications for scholars and policymakers. • Green cryptocurrency has a greater impact on green bonds during the Corona era. • During coronavirus, the sensitivity of the green bond to gold price has increased. • Bitcoin has negative impact on green bond indices before the COVID-19. [ABSTRACT FROM AUTHOR]

This paper investigates the potential of 15 RCEP (The Regional Comprehensive Economic Partnership) member countries to advance green investments from 2000 to 2021. Based on the results from the Panel Pooled Mean Group (PMG) technique, the investment potential has positive short- and long-term coefficients. The EKC (Environmental Kuznets Curve) hypothesis exists, indicating that gross domestic product per capita in the short term is the factor that inhibits the growth of renewable energy consumption. The financial development index has a non-significant coefficient in the short term. However, it has a positive coefficient in the long term. The climate policy uncertainty negatively impacts renewable energy deployment in the short- and long-term. The conclusions provide some policy implications, such as the support of green SMEs, the establishment of a digital green financing market, and the creation of green multilateralism through the establishment of a green investment network. • Environmental Kuznets Curve hypothesis exists in RCEP economies. • Financial development index has a positive and significant effect coefficient. • The climate policy uncertainty negatively impacts renewable energy deployment. [ABSTRACT FROM AUTHOR]

The majority of small district heating systems (DHS) in Poland are supplied with coal and do not have a status of efficient ones according to Energy Efficiency Directive. They should transform into efficient ones by taking an appropriate measures by the end of 2035. At the same time, a significant reduction of CO 2 emissions is expected in this sector. One of the possible solution for such systems is to apply unites fueled with fuels alternative to coal such as biomass. Cost benefits analysis of implementation a biomass ORC (Organic Rankine Cycle) cogeneration unit in municipal district heating system of 22 MW thermal capacity is the subject of the paper. The research included building configuration scenarios of a heat source regarding ORC size and operation modes. Different economic inputs such as electricity, fuel and European Union Allowance (EUA) for CO 2 prices as well as financial support mechanisms were considered. Economic indexes (Net Present Value, Internal Rate of Return and payback times) have been derived for both Polish and German conditions. [ABSTRACT FROM AUTHOR]

Wind speed forecasting is the basis of wind farm operation, which provides a reference for the future operation status evaluation of wind farms. For the wind speed forecast of wind turbines in the whole wind farm, a strategy combining unified forecast and single site error correction is proposed in this paper. The unified forecast framework is composed of a unified forecast model and multiple single site error correction models, which combines the forecasted grids of numerical weather prediction (NWP) with the monitoring data of wind farms. The proposed unified forecast model is called spatiotemporal conversion deep predictive network (STC-DPN), which is composed of temporal convolution network (TCN) and 2D convolution long short-term memory network (ConvLSTM). Firstly, the NWP forecasted grids are interpolated to the fan location, and the sequence matrix is composed of the NWP data and the monitored data of each wind turbine according to the time series, which is entered into the TCN network for time sequence feature extraction. Then, the output of the TCN network is converted into a regular spatio-temporal data matrix, which is entered into the ConvLSTM network for joint learning of spatio-temporal features to obtain the wind speed sequence forecasted in the whole wind farm. Finally, an independent TCN-LSTM error correction model is added for each site. Variational modal decomposition (VMD) is used to process data series, and different processing methods are adopted in unified forecast and single site error correction. In the 96 steps forecast test of a wind farm from Jining City, China, the proposed method is superior to several baseline methods and has important practical application value. [ABSTRACT FROM AUTHOR]

It is becoming increasingly important for human societies to use renewable energy. More effective energy storage solutions are crucial to increase the share of renewable energy in the domestic and industrial sectors, which consumes a large amount of thermal energy for heating and cooling purposes. There has been little quantitative analysis of thermal energy storage in solar-based cold production units. An efficient method of designing heat and/or cold storage systems and smart operation planning can help a cooling/heating system to be smaller for the same capacity of supply and thereby reducing the costs of initial investment and costs of operation. This paper attempts to show how the size of a heat and cold storage system affects its thermal performance and how it can lower costs and emissions. For this, a solar-assisted thermally driven cooling supply system with various designs and integrations of their cold storage unit is simulated dynamically through a whole year in Qassim region as the case study. The results show that a system design with double solar heat storage and double cold storage in parallel arrangement results in the best techno-economic-environmental performance. For this case, the levelized cost of cooling will be 383 USD/MWhr, which will be at least 3% lower than the typical hot/cold buffer tank design scenario. [ABSTRACT FROM AUTHOR]

Condition monitoring (CM) of wind turbines (WTs) is commonly accepted as an effective way to increase the availability and reduce the operation and maintenance (O&M) costs of wind farms. CM methods based on data from Supervisory Control and Data Acquisition (SCADA) system have garnered a great deal of interest due to their accessibility and low cost. Existing studies based on SCADA data provide whether the WT is normal or abnormal, and further the fault locations if an anomaly occurs. Nevertheless, few studies have attempted to identify the underlying causes of the anomaly. In this paper, a novel WTCM method utilizing a self-attention-based mechanism embedded with a multivariable query pattern is proposed for the anomaly detection and underlying causes identification. Firstly, an anomaly detection model composed of multiple cascaded encoders and decoders with a multi-head self-attention mechanism is proposed to extract cross-variable correlations. Furthermore, the multivariable query pattern is designed to evaluate the influences of different features on the target, which is essential for fault identification. Finally, the relative anomaly index (RAI) is proposed for each feature to quantify the impact of each feature on the anomaly. RAIs are adopted to analyze the underlying causes of anomalies. Experimental results confirmed the effectiveness of the proposed method for the WT fault early detection and identification of anomaly causes. [ABSTRACT FROM AUTHOR]

Developing new technologies is a key to achieve renewable energy utilization. The near-field thermo-photovoltaics (NFTPV), an emerging power generation device, is investigated from the energy perspective in this paper. A novel oxy-enrich NFTPV system is proposed, and a thermo-physical model is established for sustainable fuel gas based on energy balance. The effects of parameters on system performance are numerically explored, including the furnace size, oxygen ratio, voltage and vacuum gap, etc. Moreover, special attention is paid to the effects of oxygen ratio on system performance under 2 atm of O 2 /N 2 and O 2 /CO 2. Besides, exergy analysis is conducted. The results show that it is more appropriate to control the power density of furnace at 50 kW/m2 in system design. The efficiency of NFTPV system is about twice greater than that of far-field TPV system. The power density of NFTPV system increases by more than 2.5 times when the oxygen ratio increases; the TPV volume can increase by 2–3 times and the efficiency is also improved. The results indicate that oxy-enrich combustion with higher oxygen ratio matches a larger NFTPV system, which reduces the manufacturing difficulty and is significant in engineering. This study provides new ideas and references for NFTPV practical application. [ABSTRACT FROM AUTHOR]

An advanced enhanced geothermal system (EGS) is capable of unlocking many thousands of megawatts of power in hot dry rocks, and the fracture configuration is a critical factor influencing its efficiency. A flyover-crossing fracture (FCF) configuration for EGS was proposed in this paper, to enhance heat transfer between the working fluid and reservoir and thus the productivity of EGS. A 3D transient thermal-hydraulic model was established to analyze the heat extraction of the FCF-EGS, and the effects of intersection angles of the FCF on the heat and mass transfer as well as the productivity of the EGS were examined. The FCF-EGS was found to bring higher production temperature and thermal power output than the conventional double-horizontal-well EGS during a 30-year heat recovery period, and the heat extraction capacity of the FCF-EGS was found to increase with the intersection angle. It was also found that the FCF with a 90°cross-angle has the best heat extraction performance, with the output thermal power increased by 5.12% compared to the conventional double-horizontal-well EGS, due to the enhancement of heat transfer between the working fluid and rock. Although this fracture system requires more investment in fracturing and larger pressure in production, the increase in heat production far outweighs this input. This study provides a novel potential fracture configuration for exploiting HDR geothermal energy. [ABSTRACT FROM AUTHOR]

This paper studies the time-scale characteristics, model reduction, and oscillation stability of the grid-connected variable speed pumped storage unit (VSPSU). Firstly, a method based on the modal analysis and time-scale separation ratio indicator is established to analyze the time-scale characteristics of VSPSU. The results indicate that the state variables of VSPSU can be approximately separated on four-time scales. On this basis, the singular perturbation method (SPM) is applied to obtain the reduced-order model (ROM) of VSPSU under different conditions. The results show that the accuracy of ROMs can be affected by changes in operating conditions. To balance the complexity and accuracy of ROM, a model reduction strategy combining SPM and reduction margin is proposed. The results indicate that the proposed method enables the order minimization of ROM while the selected oscillation mode reaches a given accuracy condition. Finally, the feasibility of ROM for oscillation stability analysis is verified. The ROMs obtained with the proposed strategy are more accurate than those obtained with SPM for oscillation stability analysis of VSPSU. The influence of grid strength, turbine speed, and torque conditions on system oscillation stability is also revealed. This study provides new insights for model order reduction and stability analysis of VSPSU. [ABSTRACT FROM AUTHOR]

Bulb turbines are used to generate electric power, usually in low-head hydropower as a renewable source of energy. Flows in the turbines are typically characterized by low Froude number, so the pressure fields are more governed by the hydrostatic pressure gradient relative to the turbine head. As a result, the head loss mechanism is difficult to be identified by comparing local pressure characteristics, especially for vertical distributions. Furthermore, turbine flows are more sensitive to flows in reservoirs, due to shorter penstock lengths and larger runner diameters. In practice, the performances of each turbine obviously differ in a low-head hydropower station. The present paper analyzes hydraulic performance of a bulb turbine prototype, based on the entropy production theory. The full field reservoir modeling is conducted based on the two-phase flow simulation method and the geometric and environmental factors during multi turbine operation (5 units). The results showed the usefulness of the entropy production analysis for analyzing flow interactions between turbine and reservoir flows but also between each turbine unit. And, it showed that the flow interaction could play a noticeably strong role in determining operating conditions as well as the entire available energy in low-head hydropower stations. [ABSTRACT FROM AUTHOR]

The aim of this study was to verify the possibility of obtaining good-quality pellets from mixtures of materials with different particle structures and shapes. The paper describes the pressure agglomeration of ground walnut shells and coniferous tree cones as well as their three mixtures. The process involved the production of pellets with a diameter of 6 and 8 mm at the temperatures of 95 and 120°C by applying the force of 5 and 6 kN. The fraction distribution of the particles from which the pellets were made was assessed. It was found that the pellets made only of cones, as opposed to those made only of nutshells, have a fairly even distribution, i.e. the particles were of similar size. The size parameters of the pellets (length and diameter) were measured, on the basis of which the density of individual pellets was calculated. Compressive stresses of the pellets were tested on an endurance testing machine. It was found that the pellets with a greater share of nut shells were less durable than those made with the addition of ground cones. The pellets with a diameter of 6 mm and formed at a temperature of 120°C also showed a higher strength than those with a diameter of 8 mm and compacted at a temperature of 95°C. Increasing the force did not statistically significantly improve the compressive strength of the pellets. Tests of the elemental composition and the amount of ash allowed for concluding that pellets are a good energy material, as evidenced by their average calorific value of about 19 MJ kg−1. Due to exceeding the permissible limit of nitrogen content (ISO 17225), the pellets made solely of cones were classified as quality class B, while the addition of ground walnut shells shifted them to class A2. [ABSTRACT FROM AUTHOR]

Hydropower plants play an integral role in energy supply and are one of the main renewable energy sources. The efficiency of hydropower reservoir systems is controlled by operating rules that need to be optimized to maximize energy production. Here, a novel optimization algorithm, influential flower pollination algorithm (IFPA), is developed in this paper. IFPA has three enhancements: an efficient exploration mechanism based on an adaptive coefficient, a new exploitation mechanism around the best solution, and a rank-based strategy to smoothly transition from exploration to exploitation. IFPA is tested in two benchmark multi-reservoir systems and a real-world five-reservoir hydropower system in Iran. The results show IFPA outperforms other advanced methods in terms of convergence speed and preciseness to achieve the global solution. The tested algorithms include adaptive guided differential evolution (AGDE), composite DE (CODE), hybridizing sum-local search optimizer (HSLSO), improved teaching learning-based optimization (ITLBO), self-adapting control parameters in DE (jDE), self-adaptive TLBO (SATLBO), and a multi-strategy hybrid of DE and particle swarm optimization (MS-DEPSO). IFPA also achieved better total power production in the real-world case study compared to other algorithms. Overall, IFPA can provide better solutions with less power deficit and shows as a promising method for optimizing hydropower reservoir problems. [ABSTRACT FROM AUTHOR]

The increasing penetration of photovoltaic technology in the electricity market requires the development of a methodology that facilitates the optimisation of photovoltaic plants with single-axis trackers. This paper presents an optimisation methodology that takes into account the most important design variables of single-axis photovoltaic plants, including irregular land shape, size and configuration of the mounting system, row spacing, and operating periods (for backtracking mode, limited range of motion, and normal tracking mode). Equations for the determination of the optimal row spacing and operating periods have been developed and is presented in detail. A packing algorithm that takes into account the irregular land shape and the possible configurations of the mounting systems is also presented. The objective function is the total area of the photovoltaic field and the optimisation is performed by a packing algorithm. As the economic aspect of energy generation also plays a key role in decision-making, the levelised cost of energy has been used to assess the economic viability of the optimal layout of the mounting systems. The results show that the proposed methodology and packing algorithm are able to optimise the photovoltaic plant with single-axis solar tracking and provide reliable results after a reasonable computation time. The methodology was demonstrated in detail for a Spanish photovoltaic plant (Granjera photovoltaic power plant), including the optimal layout of the mounting systems and the cost analysis for this layout. The optimal layout of the mounting systems could increase the amount of energy captured by 91.18% in relation to the current of Granjera photovoltaic power plant. The mounting system configuration used in the optimal layout is the one with the best levelised cost of energy efficiency, 1.09. The presented optimisation methodology can be utilised to facilitate the optimal design of commercial photovoltaic plants with single-axis trackers. Therefore, questions such as: what is the optimal distribution of mounting systems?, how much energy will this distribution produce?, and at what cost will it produce it?, can be answered by using the proposed methodology. • The optimal layout of single-axis solar trackers in large-scale PV plants. • A detailed analysis of the design of the inter-row spacing and operating periods. • The optimal layout of the mounting systems increases the amount of energy by 91%. • Also has the best levelised cost of energy efficiency, 1.09. [ABSTRACT FROM AUTHOR]

Accurate prediction of renewable energy generation acts as a critical role which not only provides short-term power generation in the future, but also facilitates scheduling and pre-configuration of energy storage systems. More importantly, the power generation prediction is of great significance to the demand response management (DRM) of renewable energy to participate in the electricity spot market. Therefore, DRM helps improve the stability and reliability of renewable energy systems. This paper presents a novel prediction-smoothing based methodology to reduce and eliminate the influence caused by the uncertainty of renewable energy output. Firstly, the Whale Optimization Algorithm (WOA) is combined with Long Short-Term Memory (LSTM) to predict short-term wind power output. Then, the Hampel-Butterworth-SG filtering strategy with outlier regression and specific risk band elimination is introduced. After that, according to the short-term output forecast results, the scheduling and pre-configuration scheme of peak-filling type energy storage is developed. Finally, based on the predicted renewable energy output and electricity price, the dynamic changes of demand response (DR) are calculated based on Logistics function, optimistic response and pessimistic response factors. Through extensive case studies, it is demonstrated that the assessment deviations in different scenarios is less than 5%, which are 0.64% for Scenario 1 and 3.64% for Scenario 2, and no additional penalty is required at this time. In addition, the proposed Demand Response Load Adjustment Rate (DRLAR) help compare the differences between predicted and actual DR, which are DRLAR = 0.03% in Scenario 1 and DRLAR = 0.01% in Scenario 2. Users are able to adjust the DR dynamically according to the electricity price to realize the optimal scheduling of their renewable resources. The proposed methodology creates a special connection between DRM and renewable energy prediction, which provides a reliable reference for future work. [ABSTRACT FROM AUTHOR]

Vortex flows and pressure fluctuations, especially in the draft tube and vaneless space, have crucial impact on stable and safety operation for a high-head pump-turbine due to be fast adjusted and frequently switched between pump and turbine modes and often down to the deep part load. To more accurately investigate the vortex flows and pressure fluctuations in a high-head pump-turbine with splitter blades runner, a reliable approach by combined experiments with numerical simulations is presented in this paper. Laser Doppler Velocimetry measurements and high-speed camera observations inside the draft tube have been conducted at all the investigated points. Velocity profiles, vortex ropes visualization, the instantaneous tangential velocity and pressure fluctuations in both measured and simulated are presented to validate the numerical simulations and classify the vortex flow patterns. Meanwhile, the relationship between formation, development and breakdown of the vortex rope, the processional frequency and swirl intensity has been linked up and experimentally validated. Variation regularity of pressure fluctuations along the flow passage at different operating conditions has been quantitatively substantiated with measurements and predictions. Validation of predicted results versus experimental data shows that the presented numerical simulations can give very good results of vortex structures and the predicted fluctuation's frequencies. The pressure fluctuations amplitude of both the measured and the predicted in turbine mode agree well in the vortex rope-free zone, but has relatively larger deviations out of the vortex rope-free zone. It also demonstrated that the runner with splitter blades can restrain development of vortex flow and decrease the amplitude of pressure fluctuations for a high-head pump-turbine. The presented approach has been applied to successfully developed the high-head pump-turbines for several Pumped Storage Power Plants in China and demonstrated very useful in hydraulic optimizations. [ABSTRACT FROM AUTHOR]

Floating offshore wind turbines (FOWTs) are the largest rotating structures on the earth. Dynamically sensitive structures such as these must be protected in these environments to ensure that they can continue to operate reliably and safely. In this paper structural dynamic models and probabilistic assessment tools are combined to demonstrate improvements in structural reliability when FOWT towers are equipped with a new type of damper — the tuned mass damper inerter (TMDI). A multi-body dynamic approach is used to model the wind turbine and the TMDI installed in the tower. The model is subjected to stochastically generated wind and wave loads of varying magnitudes to develop wind-induced probabilistic demand models for towers of FOWTs under model and load uncertainties. A focus is placed on the impact of the wind-wave misalignment on the lightly damped side-to-side mode. Numerical simulations are carried out to construct fragility curves which illustrate reductions in the vulnerability of FOWTs to wind and wave loading owing to the inclusion of the new damper. Results show that the TMDI delivers significant increases in structural reliability of FOWT towers. [ABSTRACT FROM AUTHOR]

The proton exchange membrane electrolyzer (PEME) is a promising tool for hydrogen production, and internal two-phase transport significantly influences its performance. In this study, a two-phase analytical PEME model incorporating the liquid saturation jump effect was developed, and intelligent parameter estimation using a genetic algorithm was proposed to achieve high-efficiency model validation. In-house experiments and experimental results from numerous papers in the literature were employed to prove the effectiveness of the proposed intelligent parameter estimation. Moreover, the two-phase simulation results demonstrated that the PEME voltage increased significantly when the current density reached the limiting value, and the liquid saturation in the anode catalyst layer (ACL) dropped to nearly zero. Increasing ACL porosity, decreasing ACL permeability, and decreasing ACL thickness could increase the limiting current density within the investigated range. The simulated limiting current density could be > 5 A cm−2 through proper design of the ACL parameters. For high-pressure cathode operation, increasing the cathode pressure and membrane permeability generally benefits water management inside the PEME and therefore increases the limiting current density. This study provides critical support for the design of cells and operating conditions for future PEME studies. [ABSTRACT FROM AUTHOR]

Building integration of solar photovoltaic components is a relevant approach for contributing to energy decarbonisation of building applications and so, to reach European climate goals. Thus, in this paper, a large size solar component is studied experimentally and numerically to validate its suitability as building construction element, from the thermal, energy and mechanical points of view. Moreover, a simple linear model of its monthly electrical performance and temperature is developed. After its integration in landscape position using a metal structure on the southern insulated concrete wall of a real building, the solar system was instrumented and monitored during more than one year. Its thermal behaviour and electrical production, and the visible mechanical deformation of the mounting structure were assessed. Monthly photovoltaic performance ratios between 0.5 and 0.7, and efficiencies between 5.9% and 8.3%, were obtained during tests. The module maximum temperature was between 46.5 °C in November 2018 and 63.0 °C in September 2019. No visual degradation was noted. Then, numerical studies of the system in three sites, using the linear model, highlighted most relevant installation configurations, like a south -orientation at Nice. As further study, the system performance reliability will be evaluated after at least three years of operation. [ABSTRACT FROM AUTHOR]

Solar co-generation, i.e., the generation of electricity and heat in a single device by concentrating the sunbeams, has the potential to significantly increase the overall system performance. The main challenge is related to the cooling of solar cells. In order to do so, it is essential to reduce the thermal resistance between the cell and heat transfer fluid. This paper features the optimization procedure of a low-cost custom concentrated photovoltaic thermal (CPV-T) receiver for a parabolic trough collector using silicon solar cells. A finite volume model for the thermal process has been developed. Hence, a fluid dynamic thermal simulation of the receiver is presented. The optimized heat sink tube geometries have been manufactured and tested in a lab environment, allowing for a comparison between modelling and experimental test results. Three possible heat sink geometries have been designed and compared regarding their overall heat transfer coefficient with respect to the non-dimensional pumping power, i.e. the ratio between the overall transferred heat and the energy required for pumping. The overall heat transfer coefficient for a finned heat sink has been increased up to 60% with respect to a baseline case without fins under similar conditions. • Concentrated Photovoltaic Thermal Receiver for Solar Co-Generation applications. • CPV-T 3D conjugate heat transfer numerical modelling. • CPV-T solar collector receiver experimental setup. • CPV-T heat sink geometry numerical and experimental analysis. • Thermal and fluid dynamic CPV-T heat sink geometry study including fins analysis. [ABSTRACT FROM AUTHOR]

Transmembrane ion transportation in the nanofluidic salinity gradient energy conversion process is significantly regulated by the ion characteristics and concentration-depended physical and chemical properties of the electrolyte solution. In this paper, considering the Born and dielectrophoretic forces and nonhomogeneous electrolyte solution, impacts of various electrolytes on the nanofluidic energy conversion performance are systematically investigated under various solution pHs. When the solution pH is less than the isoelectric point (IEP), with BeCl 2 solution employed, where the anion diffusion and concentration coefficient are much larger than those of the anion, significant transmembrane anion diffusion exists, leading to the highest osmotic current and maximum power output, even when the solution pH > IEP where the nanochannel is negatively charged, the ion selectivity is still not altered. At pH < IEP, 2:1 electrolytes, where the cation has small ion diffusion coefficient and the anion has larger diffusion coefficient and hydrated radius could result in upgraded energy conversion performance; At pH > IEP, 1:1 electrolytes where the cation has large ion diffusion coefficient and the anion has small diffusion coefficient and large hydrated radius are more appealing. In addition, the relationships between ion characteristics, power extracted, and energy conversion efficiency are further obtained via machine learning. [ABSTRACT FROM AUTHOR]

Biomass is the only renewable organic material that has high energy content. Due to the significant amount of biomass resources, especially crop residues, the valorization of biomass to fuel or fuel additives have received more attention. In the present paper, biomass-derived butyl levulinate was prepared from starch in the presence of Al-modified mesoporous KIT-5 silica to improve its catalytic activity. Accordingly, the acidity character of KIT-5 was improved by two methods: wetness impregnation and in situ incorporation of aluminum. The essential properties of these catalysts were characterized by different techniques including N 2 adsorption-desorption analysis, ICP-OES, FT-IR, and Pyridine-FT-IR analyses, XRD, SEM, TEM. A series of important parameters influencing the reaction yield was thoroughly investigated. Under the optimized conditions (230 °C, 10 h, 30 mg catalyst, and 70 mg starch), 31% n-butyl levulinate yield and 74% starch conversion were obtained, respectively. Finally, the selected catalyst was regenerated and reused in starch valorization reaction for four successive runs. [ABSTRACT FROM AUTHOR]

Improving the accuracy of photovoltaic (PV) power forecasting is crucial to ensure more effective use of energy resources. Improvements are especially important for regions for which historical solar radiation data do not exist. This paper proposes a cyber-secure forecasting model called federated deep learning (FDL) to forecast PV power generation in various regions across Iran. The training process in each client is done by a convolutional neural network (CNN). Then, a generalizable global supermodel is generated based on the features extracted in each client, which has the ability to generalize and forecast for regions where there is no training data. Preserve data privacy and ideal performance against cyber-attacks are prominent features of the proposed method. The use of the proposed method is illustrated with a case study for Iran. The proposed FDL network is designed with 9 clients and three different scenarios were developed to test the robustness of the suggested method. In the first scenario, the PV power generation forecasting is done via the proposed technique and other conventional methods. The performance accuracy (R 2) of the generated global supermodel in this scenario for PV power generation forecasting in the regions of Khomein, Meybod, Varzaneh, Taleghan, and Shiraz are obtained as 0.981, 0.989, 0.986, 0.983, and 0.987 respectively. However, it was observed that other conventional deep learning-based models such as CNN and long short-term memory were not able to provide any forecasting for these regions. The second scenario models the scaling attack as a specific pattern of false data injection attack, to evaluate the performance of forecasting models against the data integrity attack. In the third scenario, cyber-attack detection is performed based on data visualization and image processing procedures. The results presented in different scenarios emphasize the high accuracy and generalizability of the global cyber-secure supermodel in PV power generation forecasting in different regions of Iran. [ABSTRACT FROM AUTHOR]

World electricity consumption has grown permanently since 1990, dramatically increasing the emission of greenhouse gases. The worldwide efforts to reduce them and address climate change are leading to the massive electrification of different end-users, increasing the power demand. Therefore, achieving Sustainable Development Goals regarding affordable and clean energy requires the extensive availability of capital investments in electricity generation from renewable sources. Project Finance (PF) is a suitable financing alternative for large projects. This paper presents the advantages of PF contracts in allocating risks to appropriate counterparts and reducing the likelihood of default. Additionally, this study analyzes the characteristics that favor PF financing for renewable energy projects. The results reveal that country's governance levels, well-developed financial systems, and project costs affect the financing probability of a PF initiative, particularly for low and middle-income countries. Therefore, public policies aimed at increasing the availability of resources to renewable projects must tackle these factors. • The world requires massive renewable energy investments to meet Sustainable Goals. • Project Finance is a widely financing structure for large investment projects. • We study the determinants of renewable energy Project Finance. • Low governance and financial development hinder renewable energy PF initiatives. • Policies to develop capital markets and PF will help to reach the net zero target. [ABSTRACT FROM AUTHOR]

In this paper, the authors present a two-step model to obtain quasi-optimal solutions for the storage and transportation of renewable energy as its installation becomes more widespread in remote areas. The model is formulated as a total cost minimization linear programming problem and considers both renewable energy facilities and the energy supply and demand of the entire country. The first step of the model optimizes the entire country, while the second step determines the marginal capacity of energy storage and transportation facilities when the excess production capacity of remote renewable energy is added. This approximation for reducing computational complexity is shown to be sufficiently accurate under realistic conditions. The authors apply the model to analyze energy storage and hydrogen production at renewable energy power plants in Japan in 2050. The study shows that photovoltaic power generation uses storage batteries attached to the power plant for electricity transmission. In contrast, wind power generation transmits most electricity directly without storage batteries and converts some into hydrogen for consumers. The proposed lightweight model allows for numeral sensitivity analyses, which provide valuable insight into optimizing energy storage and transport of renewable energy. • We developed a 2-step model for quasi-optimization of equipment at VRE site. • This model optimizes energy storage and transport with VRE deployment. • If additional VRE is sufficiently small, the model division retains sufficient accuracy. • Energy supply costs minimized by combining power transmission and H 2 transportation. • PV has large LIB, while WT has direct transmission and H 2 production. [ABSTRACT FROM AUTHOR]

The number and importance of renewable energy communities (RECs) are increasing in all European countries due to the support of EU and national policies in order to foster the energy transition through participatory strategies for distributed energy systems. However, their development is rather slow in some countries, including Italy. The paper addressed the issue of the emergence of these socio-technical configurations in Italy, after the related law which entered into force in 2020 allowing the possibility of creating them. Our study focused on the alliances among different actors (professionals, institutions, NGOs, citizens) highlighting possible trends or models for the future that need to be confirmed in further research. The approach proposed to analyse this current process is the Actor-Network Theory, aiming at drawing the assemblages of human and non-human actants at a general level. Accordingly, we selected three case studies in order to show their different ways of organising, the relevance of trust in establishing each REC and the influence of local context on the composition and features of the actor-networks. [ABSTRACT FROM AUTHOR]

Medium-term optimal scheduling of hydropower plants (MOSHPP) should be frequently updated for recurring extreme precipitation events in China to reduce spillage and increase power generation; however, the curse of dimensionality makes obtaining a satisfactory solution in an acceptable time difficult. In this paper, a parallel improved dynamic programming with successive approximation (PIDPSA) for MOSHPPs is proposed to improve the solution quality and meet time requirements. The solution quality is improved by successive approximation of multiple plants instead of one plant for considering more hydraulic connections, a state space reduction strategy combined with constraint preprocessing is adopted to reduce unnecessary calculations and the fine-grained parallelism based on the fork/join framework is employed to greatly shorten the solution time. The proposed method was applied to 11 hydropower cascade plants in the Lancang River with a time horizon of 30 days. The results showed that higher quality solutions can be obtained by IDPSA than conventional methods and DPSA, and the space reduction strategy can effectively improve the solution efficiency. The computation time of PIDPSA decreased from 81345 s for the single-core environment to 6073 s for the 32-core environment, which proves the high efficiency and practical value of PIDPSA for solving MOSHPP problems. [ABSTRACT FROM AUTHOR]

Developing new technologies to utilize natural renewable energy resources and fluxes is critical to mitigate climate change and energy crisis. As a renewable energy resource, wave energy is more predictable and has a higher power density compared to solar and wind. However, the technology for wave energy harvesting is still relatively nascent. One of the major challenges as the sector developers is the lack of spatial–temporal representation of wave resources, or wave power generation, from a generic WEC. This paper proposes a novel Wave Net Power Assessment (WNPA) method by utilizing the theoretical Wave Energy Converter (WEC) power limits (including the radiation power limits, Budal's limit, and gross wave power), and applies it to a decade of wave conditions across the USA East Coast, West Coast and Hawaiian Islands. The WNPA method assesses the wave resource from device point of view (unlike traditional gross wave resource assessment) and is generally applicable to WECs regardless of dimension, size, and degrees of freedom (DoFs). The geospatial application of the WNPA method allowed for the analysis of wave power production potential along U.S. coastlines and provides WEC developers meaningful data to make decisions about the best spatial region to deploy certain WECs. Numerical simulations are conducted for WECs with 5 different sizes, 3 different operating modes across the West Coast, East Coast, and Hawaii over 10 years. In addition, productivity, efficiency and gross power quality comparisons are made in terms of the size and degree-of-freedom for WECs deployed at certain ocean sites (e.g., PacWave). A few of the most important findings: (1) The net wave power is dramatically smaller than the gross wave power, which indicates the new WNPA method has a more conservative assessment of the wave power potential; (2) A heaving 10 m WEC is found to have the highest (compared to other sizes and degrees of freedom) absorption efficiency on the West Coast and Hawaii; (3) For smaller 2 m surging/pitching WECs, ocean sites on the East Coast (e.g., Diamond Shoals, NC) maximize power production. (4) There are distinct trade-offs between maximizing power or minimizing power quality and dependencies exists between the location of interest, the WEC size, and the priority degree of freedom. The proposed methodology can be utilized by WEC technology and project developers to conduct apriori preliminary analysis of WEC deployment locations and device characteristics. • Introduction of novel Wave Net Power Assessment (WNPA) methodology for assessing the wave energy resource by providing an upper practical limit of WEC power generation. • Derivation of generic methodology to predict the performance of a WEC; depending only on WEC characteristic dimension and mode of motion. • Geospatial analysis of WEC generation across the US West Coast, East Coast and Hawaiian Islands with five differing WEC sizes, with three different degrees of motion, over a 10-yr period. • Quantification of the mean power, conversion efficiency and co-efficient of variation over a decade. • Ability to quickly understand the spatial and temporal monthly variability of various WEC archetypes in specific locations within US waters. [ABSTRACT FROM AUTHOR]

Rapid urbanization is affecting the harmonious development of the environment and economy. Governments are developing new urban planning policies to achieve sustainable urban development. Using the Chinese smart city pilot policy as a natural experimental group, we use a difference-differences model to explore the relationship between smart cities and clean energy development. There are three findings in this paper. First, we find that smart city pilots drive clean energy development. Second, we find that digital technologies can reinforce the positive impact of smart city pilots and that innovation and financial inclusion have a positive mediating role. Third, we find that the impact of smart city pilots has a heterogeneous impact. Namely, pilots in coastal, large, and resource-based cities have a more positive impact on clean energy development. Existing smart city pilots significantly impact energy security and sustainable development. Our study provides a new perspective on urban planning and clean energy development in emerging countries such as China. • A difference-differences model to explore the effect of smart city pilot. • Smart city pilot drives clean energy development. • Innovation and financial inclusion have positive mediating roles. • Digital technology has a positive moderating effect. • Clean energy development in smart cities is distinctly heterogeneous. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the stability of hydro-turbine governing system (HTGS) with sloping ceiling tailrace tunnel (SCTT) and upstream surge tank (UST) considering nonlinear hydro-turbine characteristics (NHTCs). Firstly, the mathematical model of HTGS is presented based on nonlinear seventh-order state equation, which is verified by example analysis so as to study the stability of HTGS. Subsequently, the effect of HTGS parameters on the stability of the system is investigated with numerical simulation. Finally, the coupling effect mechanism of SCTT and UST on stability under the effect of NHTCs is revealed by using contrastive analysis. The results are summarized as follows: (1) T a , K d and T wt perform larger effect on the stability of HTGS, while the influence of F and T wy is mild; (2) the NHTCs are beneficial under negative load disturbance and unfavorable under positive load disturbance for the stability and dynamic performance of HTGS; (3) the coupling effect of SCTT and UST outperforms the results of SCTT or UST alone under all load disturbances; (4) the incorporation of UST to the established model plays a certain role in stability compensation, while the introduction of SCTT not only improves the stability but also achieves smaller amplitude and lower frequency. [ABSTRACT FROM AUTHOR]