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In this paper, an exploratory data analysis method is employed to investigate the impact of different system parameter combinations on the magnitude and stability of power of flow-induced vibration (FIV). Firstly, orthogonal experimental design within exploratory data analysis is used to set up numerical simulations of flow-induced vibration and collect data on FIV power generation characteristics. Then range method is used to select the optimal parameters combination for flow-induced vibration power generation, and the degree of influence of different system parameters on power and stability is quantitatively described by variance and entropy weight methods. Our results reveal that the optimal parameter combination for power corresponds to m* = 1.343, K = 1200 and ζ = 0.08, and the optimal parameter combination for stability is m* = 1.343, K = 1200 and ζ = 0.04. Additionally, the weight relationship of each system parameter affecting power and stability is W K > W ζ > W m* and W ζ > W m* > W K , respectively. These weight relationships allow for the effective adjustment of the parameter levels to quickly achieve the goal of optimizing power and stability. A new parameter P value-stability is proposed to comprehensively evaluate power magnitude and power stability, and optimal parameter combinations in different vibration branches is achieved. This paper provides new ideas and guidance for the design of the FIV energy harvesting device. [ABSTRACT FROM AUTHOR]

Integrating biomass, photovoltaic, and other renewable energy sources for hydrogen production can form a biomass-photovoltaic-hydrogen integrated energy system (BPH-IES). The system features multi-energy storage and joint supply, as well as cascaded utilization, is a promising co-generation way to meet the system's electricity, heat and hydrogen needs, and has significant energy-exergy-economy-environment (4E) performance. Therefore, scientific and effective evaluation of the BPH-IES is an important prerequisite for promoting its development. Firstly, by analyzing the structure of the BPH-IES system, this paper constructs a comprehensive performance evaluation index system of the system from the 4E dimensions. Secondly, a hybrid multi-criterion decision making (MCDM) framework for the 4E comprehensive performance evaluation of the BPH-IES is constructed, in which the anti-entropy weighting method is used to determine the objective weights, the subjective weights are determined by the decision making trial and evaluation laboratory method improved by intuitionistic fuzzy sets, and the final combined weighting results are obtained based on a game-theoretic method that the objective and subjective weights' heterogeneity can be fully minimized. The grey-relation-analysis-based measurement alternatives and ranking according to the compromise solution method is proposed to determine the ranking of alternatives. This paper selected 8 typical BPH-IES cases for 4E evaluation analysis. The results showed that energy performance is the core dimension that reflects the 4E performance of the system, and system's economy indicators such as energy supply income and energy supply cost will also significantly affect the system's 4E performance. Therefore, the 4E performance of BPH-IES can be effectively improved by expanding the system's demand and supply scale and increasing the system's installed proportion of clean energy and hydrogen penetration. Finally, the ranking consistency test, Leave-One-Out analysis and sample separation test demonstrate that the developed hybrid MCDM can ensure robustness meanwhile improve the decision efficiency. [ABSTRACT FROM AUTHOR]

With the increasing demand of users for distributed energy storage (ES) resources and the emerging development of peer to peer (P2P) transaction technology, shared energy storage (SES) has great potential to contribute into new business models of demand-side ES. In order to compromise essential elements like safety, stability and efficiency of P2P trading, as well as to improve the utilization rate of demand-side ES, this paper devotes to construct a P2P transaction framework based on a partially decentralized topology and proposes a two-stage trading optimization strategy of SES in a P2P market, considering the equilibrium state of supply and demand flow. In the first stage, this paper simultaneously balances the interests of buyers and sellers and brings the carbon trading mechanism into the transaction process. The interaction of interests of bilateral parties with consideration of carbon trading mechanism has been investigated, and a SES capacity sharing model is, then, established based on the bargaining game theory. In the second stage, a unique pricing mechanism for SES leasing fee is designed based on a multi-strategy evolutionary game model, considering bounded rational decision-making for SES operators and communities. Finally, numerical simulation verified the feasibility and superiority of the proposed P2P trading strategy of SES. [ABSTRACT FROM AUTHOR]

In recent years, the government has attached great importance to promoting innovation in new energy technologies, particularly in the area of solar power generation. Photovoltaic (PV) power generation has become an essential factor in the promotion of renewable energy due to its inherent safety, environmental sustainability and abundant solar energy resources. The efficiency and stability of PV generation systems are closely related to the accurate prediction of real-time global horizontal irradiance (GHI). However, some existing research methods have made some progress in hourly resolution, but the multi-step prediction accuracy and model generalization ability in high time resolution are still unsatisfactory. Therefore, this paper proposes a novel minutely multi-step irradiance forecasting based on all-sky images using LSTM-InformerStack hybrid model with dual feature enhancement scheme. In this scheme, the advantages of both LSTM and InformerStack models are combined to further enhance the global and local features, which can better capture the short-term time series patterns and long-term dependencies and improve the accuracy of the time series. The experimental validation results show that the performance of this prediction scheme is improved by 11.2%, and 26.0% for nRMSE and R2, respectively, and the 24-step prediction can be improved up to 26.1% vs. the persistent model. Meanwhile, the prediction scheme of this paper is also expected to provide a reference in future multi-step time series accurate prediction with higher resolution. [ABSTRACT FROM AUTHOR]

This paper proposes the use of Artificial Neural Networks (ANNs), specifically Physics-Informed Neural Networks (PINNs), for dynamic surrogate modelling of wind turbines. PINNs offer the flexibility to model complex relationships while incorporating physics-based constraints, enabling accurate representation of wind turbine dynamics. In this paper, a PINN-based surrogate model is developed for the Blade Element Momentum (BEM) aerodynamic model used in state-of-the-art numerical wind turbine simulations. The PINN model replaces the time-consuming root-finding process in BEM with high-dimensional regression, significantly improving computational efficiency. The PINN model is trained using data generated from a numerical model of the IEA-15MW reference wind turbine, and its performance is compared against conventional data-driven Neural Network (DDNN) models. The proposed surrogate model provides more efficient and accurate evaluations of wind turbine responses compared with traditional surrogate modelling approaches. A significant computational advantage is obtained by using the developed surrogate models with a forty-fold speedup demonstrated compared to the BEM model. Replacing the BEM model with the PINN-based surrogate model for load computation in the numerical model used for dynamic analysis results in an overall reduction of 35% in computational time for a complete dynamic simulation. This is a substantial improvement in efficiency without sacrificing accuracy — the maximum Mean Absolute Error (MAE) values for the surrogate models are of the order of 1 0 − 2 , which shows that the surrogate models can predict the angle of attack at any blade node with a discrepancy of less than 0. 5 °. The surrogate models significantly reduce computational time while maintaining high accuracy, making them a promising approach for simulating wind turbine dynamics, especially in fields such as reliability analysis or fatigue estimation where many simulations are necessary. [ABSTRACT FROM AUTHOR]

A rapid-calculation method O (1 0 3) ∼ O (1 0 4) times faster than a typical BEM (Boundary Element Method) model is presented for optimising an array (farm) of dual-purpose wave-energy converters (WECs) that both generate electricity and protect a coast. It is known that fast semi-analytical descriptions of the wave field are available based on the far-field approach for a widely-spaced wave farm involving point-absorber-type WECs of small sizes, for which scattered waves are negligible. However, these approaches are inept at dealing with "non-small" WECs with non-simple shapes, for which scattered waves can be both complicated and non-negligible. For these devices, this paper demonstrates that a fast semi-analytical description based on a "corrected" version of the far-field approach can still be crafted for an isolated device, with the help of a BEM model. This simple description is then used in an interaction theory for an array of devices, which requires no further input from BEM, hence reducing the computation time drastically. In an example, for an array of eight WECs, 1. 6 × 1 0 5 array configurations are calculated using a laptop computer within seven hours (this time included the time required to set up the far-field model for an isolated device), yielding an array featuring the largest "protection factor", which quantifies wave reduction along a given line downwave of the array. The calculated wave fields around the arrays can be validated against BEM results for the same arrays. Note that the time for searching for an optimum layout can further be reduced by two orders of magnitudes when a standard optimisation routine is used, for the wave farms considered in this paper. • A wave farm model based on far-field waves around an individual device. • Far-field waves are corrected by scattering term and involve nonlinear dissipation. • The wave farm model applies to wave energy devices with non-simple geometry. • The wave farm model is 1000–10000 times faster than a conventional simulation. • The fast model is able to optimise wave farms for coastal protection purposes. [ABSTRACT FROM AUTHOR]

As the penetration of distributed renewable energy gradually increases, prosumer groups in high-altitude areas are being expanded. However, the operation of these prosumers in high-altitude areas faces numerous challenges. To address the issue, this paper proposes a double layer energy cooperation framework for high-altitude prosumer groups, considers peer aggregation and shared composite energy storage, aims to adapt to the trend of diversified energy interactions and improve the economic efficiency, maximize social welfare and ensure the continuous growth of the sharing market of prosumers operations in high altitude areas. To meet the diversified energy interaction needs of prosumers, a composite energy storage provider, an energy aggregator, and a two-stage profit clearing scheme are proposed. Furthermore, the overall benefits of the framework and the impact of profit clearing schemes on fairness under various scenarios are studied, and the comprehensive effects of the double layer energy framework are evaluated. The study results show that compared to independent operation by prosumers, under the guidance of shared electricity prices and composite energy storage providers, the economic benefits, evaluation indicators and energy storage utilization efficiency have all been improved. In addition, compared to other profit distribution modes, the two-stage profit clearing scheme proposed in this paper has higher fairness, which greatly encourages the participation of interested entities in energy cooperation. This study provides a feasible framework for energy cooperation among prosumers, and the framework's effectiveness is well-validated. [Display omitted] [ABSTRACT FROM AUTHOR]

Renewable Energy Systems are considered to be a powerful component of local sustainability innovation strategies. This paper uses a policy mix approach to study innovation policy criteria, which include municipalities' location factors, stakeholder collaboration activities, and local knowledge about renewable energy sources and projects. The aim is to study the impact of these factors on decision-making and developing renewable energy projects and their local sources. Moreover, this paper aims to understand the impact of the mix of different policies on the energy sector and technological innovation systems, through the innovation policy criteria that has been identified. These impacts are studied as they constitute the policy mix, and affect the process of developing renewable energy sources in the Palestinian municipalities and local councils. In this study a sample of 216 Palestinian municipalities and local councils is analyzed. The results indicate the need for policymakers to promote cooperation between the public and private sectors, and the importance of focusing on location factors such as energy import reduction, incentives, and emissions that directly affect renewable energy sources. Whereas, local knowledge does not have a direct impact on the process of developing renewable energy systems, as it can constitute indirect support at a later stage for the implementation of other policy criteria discussed in this study. The results confirm that increasing the potential for developing renewable energy sources takes place when policymakers adopt the role of facilitator and establish a local innovation network in which different actors cooperate so that public and private stakeholders can provide support in order to develop local renewable energy systems. • Different policies impact on RE sector by innovation policy criteria are measured. • The policies and practices of 216 Palestinian local government units are analyzed. • Positioning factors, collaborative activities, & local knowledge standards are used.≥. [ABSTRACT FROM AUTHOR]

This paper explores the impact of an environmental tax on carbon emissions for the G7 nations from 1994 to 2014 and the importance of the major drivers of emissions such as energy use, economic complexity, natural resources rent and economic growth. The study also verifies the Environmental Kuznets Curve Hypothesis for the G7 countries and explores the marginal effects of an environmental tax on traditional energy consumption, natural resources rent and renewable energy consumption. This paper's unique contribution is that it investigates for the first time the moderating role of an environmental tax on renewable and non-renewable energy consumption, natural resources rent and CO 2 emissions. The results suggest that environmental taxes effectively reduce emissions for the G7 countries and confirm that the marginal effects of the environmental tax on traditional energy consumption, natural resources rent and renewable energy consumption rise with the level of taxation in a statistically significant way. The findings indicate that strict environmental tax laws will allow businesses to shift production towards cleaner methods. Finally, the paper proposes that redistributing tax revenues to the research and development of sustainable technology programmes would empower the nations to achieve the United Nations' SDG-7 and SDG-13 goals. Flow Diagram on the nexus between emissions, tax, economic complexity, energy and economic growth. [Display omitted] • The paper analyses the effects of economic complexity on carbon emissions. • Environmental tax affects directly carbon emissions. • Environmental tax lessens the effect of energy consumption and natural resources. • Environmental tax amplifies the effect of renewable energy consumption. • The EKC hypothesis is validated for economic complexity in G7. [ABSTRACT FROM AUTHOR]

The transition to renewable energy is key for sustainable development. Therefore, one of the sustainable development goals (SDG) of United Nations (UN) is to shift towards clean energy. However, in many resource-rich countries several factors can stand as barriers towards the transition process. In this regard, this paper examines the influence of higher oil price, CO 2 emissions, and income on renewable energy consumption in Iran from 1980 to 2019, employing General to Specific (Gets) modeling approach. Estimation results indicated that oil price and CO 2 emissions both have statistically significant and negative impact on renewable energy consumption. The negative influence of higher oil prices on renewable energy consumption may be interpreted as sign of satisfaction coming from higher oil prices, which postpones the transition from traditional energy sources to renewable for Iran. Furthermore, we concluded that income does not have a statistically significant influence on renewable energy use. The paper discusses alternative policies to promote renewable energy consumption. • The effect of higher oil price on renewable energy consumption was studied. • A novel version of General to Specific (Gets) modeling approach was employed. • We found significant, negative impact of oil price on renewable energy use in Iran. • The paper discusses alternative policies for Iran to promote renewable energy use. [ABSTRACT FROM AUTHOR]

This paper proposes a cam frequency-increasing hybrid piezoelectric electromagnetic energy harvester with center symmetric structure (C-HEH). The use of the cam structure allows the harvester to increase the efficiency of energy harvester per unit time, while the center symmetric structure of the entire harvester allows for maximum energy output in a limited size. This paper studies the influence of the number of cam protrusions and the length of the cylindrical permanent magnet on the output voltage signal at different rotation speeds. When the number of cam protrusions is 3 and the length of the cylindrical magnet is 10 mm, the maximum peak-to-peak voltages of the piezoelectric and the electromagnetic power generation unit are 53.74 V and 3.16 V, respectively. The effective value power of the hybrid energy harvester can be obtained as 1.49 mW. A series of application experiments were carried out to verify the performance of the C-HEH. The hybrid energy harvester can easily light up 86 light-emitting diodes (LEDs) lights and make the scientific calculators work stably after rectification. These results demonstrate the giant prospect of piezoelectric-electromagnetic energy harvesters for supplying wireless sensor networks and low-power electronic devices. [ABSTRACT FROM AUTHOR]

Financial development and demographic changes have an important impact on the non-hydro renewable energy industry, and this impact is significantly different in countries at different stages of development. This paper studies 10 developed countries and 10 developing countries using annual data from 1990 to 2018. Through the panel cointegration estimation method, the paper evaluates the impact of financial development and demographic changes on the non-hydro renewable energy industry. The empirical results show that the stock market and bank intermediary have a significant role in promoting the growth of the non-hydro renewable energy industry in developing and developed countries. The bond market has a significant positive impact on the growth of the non-hydro renewable energy industry in developed countries only. Foreign direct investment in developing countries significantly promotes the growth of the non-hydro renewable energy industry, while in developed countries it has a negative impact. Population aging has a significant inhibitory effect on the growth of the non-hydro renewable energy industry in developing and developed countries. [ABSTRACT FROM AUTHOR]

A novel practical fixed-time command-filtered backstepping strategy for a hydraulic turbine regulating system (HTRS) is developed in this paper. The developed controller is designed with the help of a combination of command-filtered backstepping and practical fixed-time stability theory. Based on this scheme, the obtained control strategy is utilized to ensure that the equilibrium point is practically fixed-time stable, and all signals of the closed-loop system are bounded within a fixed time. The main contributions of this paper are threefold: (i) The control scheme for frequency regulation of the HTRS is proposed to deal with the problem of the "explosion of terms" caused by conventional backstepping design. (ii) The proposed practical fixed-time control law can guarantee superior stabilization with a more precisely bounded convergence time, and (iii) The proposed controller performs well, simultaneously offers better transient performance, and overcomes three important drawbacks arising in the current results of fixed-time synergetic controllers. The strategy's effectiveness and feasibility are validated in a nonlinear model of the HTRS connected to a single-machine infinite bus power system. The numerical simulation indicates that the frequency regulation and improved transient performances in fixed time are achieved based on the proposed strategy. Further, the presented control reduces the oscillations rapidly and performs better than fixed-time synergetic control and modified fixed-time synergetic control approaches. • A novel fixed-time command-filtered backstepping control scheme for frequency regulation of the HTRS is proposed. • The proposed practical fixed-time control law is capable of guaranteeing superior stabilization with a bounded convergence time. • The obtained bounded convergence time is more accurately computed than the one in the literature. • In comparison with fixed-time synergetic controllers, the proposed control law performs well and offers better transient performances. [ABSTRACT FROM AUTHOR]

Wind turbine power curve cleaning, by way of removing curtailment, stoppage, and other anomalies, is an essential step in making raw data useable for further analysis, such as determining turbine performance, site characteristics, or improving forecasting models. Typically, data comes as SCADA (Supervisory Control and Data Acquisition) data, so contains not only environmental and turbine performance data but also the control action imposed on the turbine by the operator. Many different anomaly detection (AD) methods have been proposed to clean power curves; however, few papers have explored filtering explicit and obvious anomalies from the SCADA prior to running AD. This paper actively explores this filtering impact by comparing the performances of 4 different AD methods with/without filtering. These are: iForest, Local Outlier Factor, Gaussian Mixture Models, and k-Nearest Neighbours. Each approach is evaluated in terms of prediction error, data removal rates, and ability to maintain the underlying wind statistical characteristics. The results show the effectiveness of filtering with every technique showing improvement compared to its unfiltered counterpart. Furthermore, Gaussian Mixture Models are shown to provide favourable accuracy whilst maintaining wind variability, however, with the wide range of performances of methods, a user's choice may be different depending on their needs. [ABSTRACT FROM AUTHOR]

The integration of renewable energy (RE) sources is increasing day by day because of their permanent existence and the limited quantities of fossil fuels. One of the most promising RE sources is photovoltaic (PV) technology, which is developing quickly in many countries worldwide. PV cells generate electricity by converting the sunlight to DC voltage. PV arrays are installed in outdoor areas and on the rooftops of homes to be directly subjected to the sun. Consequently, they are frequently subjected to lightning strikes, which may cause damage to PV arrays, service interruption, and additional cost for PV replacement. Therefore, an adequate lightning protection system (LPS) must be installed to protect the PV panels. In addition, the transient performance of PV panels during lightning strikes must be analyzed well. This paper presents a comprehensive review of the superior modeling methods of PV systems during lightning strikes. In addition, the paper displays the different platforms to simulate the transient effects of lightning strikes on PV systems. The lightning transient effects on PV arrays are studied based on the system modeling to assess the recommended LPS designs studied in the literature. The paper also gives some recommendations about the modeling methods and protection of PV systems during lightning strike. [ABSTRACT FROM AUTHOR]

The increasing biodiesel production generates important amounts of glycerol, by-product that require the development of new and sustainable processes in order to be converted into value added chemicals. In this paper special attention was given to possibility to transform glycerol into solketal, a promising fuel additive able to enhance stability to oxidation and increase the octane number of fuels. Given that the chemical reaction is thermodynamically limited, the current paper proposes a conceptual design of an industrial scale process flowsheet based on a modified structure of a catalytic distillation dividing wall column (CDDWC) in which acetone is used as a stripping agent, in an integrated reaction-separation structured-packing system. The modeling and simulation results performed in Aspen Hysys shown the technical feasibility, the glycerol conversion in the proposed process being over 99% and the purity of the solketal product over 99.5% (wt) with a high-quality utility (16 barg pressure steam) consumption of 2441 kJ/kg close to other values reported in the literature and an acetone specific consumption of 0.495 kg/kg solketal. [ABSTRACT FROM AUTHOR]

In this paper, the day-ahead optimal dispatching model of power system that is combined by wind-photovoltaic-hydropower-thermal-pumped storage is established. Firstly, according to the characteristics of the short-term hydropower system dispatching problem, a new mathematical model of the cascade hydropower group system with pumped storage power stations is proposed. The coordinated optimized dispatching model of the hydropower group system formed by the cascading of pumped storage power plants and conventional hydropower in the power system is studied. Secondly, the opportunity constraint programming model of forecast error reserve is used to deal with the output uncertainty of wind power and photovoltaic. The randomness and intermittency of renewable energy on the stability of the power system are overcame by the combination of wind-photovoltaic-pumped storage. Thirdly, the model for the joint optimal dispatch of short-term wind, photovoltaic, hydropower and thermal power systems with pumped storage is developed with system economics as the goal. Fourthly, the operation volatility coefficient of thermal power units is proposed to study the impact of renewable energy on the operation of thermal power. Finally, an example system is used to verify the correctness of the proposed dispatching optimal scheduling model, and the results prove that the daily dispatch optimization model proposed in this paper can increase the economic efficiency of the power system by 5%, reduce the start-stop times of thermal power units by 36.55%, and reduce the fluctuation coefficient of the unit by 2.8. • A new mathematical model of the cascade hydropower group system is proposed. • The integral flow constraint of lag time in the daily scheduling is considered. • The operation volatility coefficient of thermal power units is proposed. [ABSTRACT FROM AUTHOR]

Offshore wind turbines (OWTs) must withstand harsh environmental loads over their 20- to 30-year design life. Fragility analysis investigates the probability of damage over a range of hazard intensities and is integral to a performance-based engineering approach. The focus of this paper is on monopiles, which are widely used to support OWTs in water depths up to around 40m. The paper presents a fragility analysis of monopiles in extreme storms in terms of geotechnical performance, measured by permanent rotation of the foundation. Geotechnical fragility has so far not been comprehensively addressed due to the challenge of predicting soil behaviour under cyclic loading and estimating the probability of extreme responses. On the latter, the paper develops efficient Karhunen-Loeve representations of wind and wave loading that can be combined with inexpensive probabilistic methods to compute fragility. The framework was demonstrated using a representative scenario of a 5 MW OWT installed in clay. Non-linear foundation response was captured by a dynamic 3D finite element model. Fragility curves were generated using subset simulation for storms with return periods (RPs) from 1 to 100 years. Fragility during extreme storms (with 50- and 100-year RPs) was significantly higher than storms with RPs of 10 years or less. • Fragility analysis of monopile foundations for offshore wind turbines. • Geotechnical performance in extreme storms assessed by permanent rotation. • Efficient Karhunen-Loeve representations of wind and wave loading. • Fragility curves generated by subset simulation. • Failure probability increases significantly for storms with 50+ year return periods. [ABSTRACT FROM AUTHOR]

The preheating process of the solar receiver in the Concentrated Solar Power (CSP) plant is necessary but dangerous before filling the molten salt, because the empty pipe is easy to overheat, but it is required to heat up quickly to match the preheating requirement. In this paper, a lab-scale receiver was used to study the preheating process, and a transient numerical model was also developed for a better understanding of the preheating process. A detailed description of the receiver's performance on the 20% xenon lamp power was conducted, and the numerical modeling was verified through the comparison with the experimental results. The preheating process of the receiver under different xenon lamp power was performed, and a non-linear relationship existed between the period of the preheating process and the different xenon lamp power. Moreover, this paper also reported that the negative feedback control was used to realize the dynamical preheating process, and the method worked according to the surface temperature of the receiver until the preheating requirement was reached. Finally, the effect of environmental temperature on the preheating process was conducted, and the preheating duration of the receiver with the same heat flux was prolonged by about 30 s with the environment temperature of −2 °C. [ABSTRACT FROM AUTHOR]

With the manufacturing reshoring to the US, increasing attention are focus on its energy consumption and environmental effects and accurate prediction of carbon emissions is vital to controlling growth from the source. Considering the slowing growth in carbon emissions with the Gompertz's law, this paper establishes a Gompertz differential equation. According to the differential information principle and fractional accumulation operator, this differential equation is transformed into a fractional accumulation grey Gompertz model. Furthermore, the chaotic whale optimization algorithm is used to optimize the order of accumulation generation and the grey background value in the proposed model. Then the Gompertz's datasets and six validation cases about carbon emissions are used to show that the proposed model demonstrates better accuracy in all cases and efficiency in the carbon emissions forecasting with several existing models. Three case studies indicate that the proposed model can fit the trend of American industrial carbon emissions better. The model results also reveal the recent policy changes have promoted the uptrend of the industrial and the total carbon emissions in the U.S. The future forecasting suggests that U.S. carbon emission is estimated to be 17.01% (in total emissions) or 17.89% (in industrial emission) percent below 2005 levels by 2025 under current policies, falling short of its commitment submitted to the United Nations Framework Convention on Climate Change. [Display omitted] • This paper discussed the Gompertz's law in carbon emissions. • A FAGGM(1,1) model is created for predicting carbon emissions. • The case study reveals the rising of peak in the industrial carbon emission in U.S. • The reduction percentage of carbon emission on 2005 levels by 2025 will be 17.01% (in total), 17.89% (in industry) and 26.23% (in commerce) in U.S. [ABSTRACT FROM AUTHOR]

A fully-submerged bottom-standing 1.5 MW wave energy converter (WEC) equipped with a membrane-pump system is under development for installation at a test site off the coast of Pembrokeshire, Wales, UK. The system comprises several flexible-membrane air cells that are compressed and sucked by the action of the waves, rectifying valves, low-pressure and high-pressure ducts, and a unidirectional air turbine that drives an electrical generator. This two-part paper reports the design and testing of an effective control law to be implemented into the programmable logic controller of the membrane-pump turbine-generator set, allowing efficient and safe operation for the wave climate at the Pembrokeshire test site. Part 1 of this paper concerns developing the design strategy of the control laws, the numerical model, and the performance evaluation of the WEC power take-off system. A genetic algorithm is used to design control laws to maximise each sea state's WEC time-average efficiency. An adaptive control algorithm is devised by cross-correlating the control laws parameters and the rotational speed. The final result is a control law that uses input the rotational speed signal and airflow density. It adapts to the sea state conditions while maximising the time-average total efficiency of the membrane-pump WEC for deployment off the Pembrokeshire coast. • A genetic algorithm used to design control laws. • Torque versus rotational speed control-laws studied using Bézier curves. • Adaptive control devised by correlating control parameters and rotational speed. • The control law uses as input the rotational speed and airflow density. • A one-parameter adaptive control law provides good performance. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents economically optimized energy and power management strategies for grid-friendly hydrogen based Zero Energy Buildings (ZEBs). The proposed energy management strategy is an adaptative optimization-based strategy that minimizes the operation cost of the facility taking into account RES generation prediction errors. It is shown that with an Adaptative Optimized Five-step Charge Controller (AOFC2) the use of the different equipment is optimized and the overall operation cost is minimized considering the entire life of the facility. The proposed energy management strategy is coordinated with power management strategies to offer advanced functionalities (peak-shaving, reactive power control and back-up service) that provide added-value to the facility. The paper demonstrates by means of offline and real-time simulations, that an adequate energy and power management structure permits the optimal economic exploitation of an advanced ZEB (that includes an energy storage system), providing not only a zero energy annual balance but also interesting added-value features to the grid and to the local consumers. [Copyright &y& Elsevier]

With the increase in solar energy penetration in electric power systems, it is necessary to predict future solar radiation. With this, the solar power generation capacity can be predicted, allowing accurate scheduling for other sources. The solar radiation or the clearness index (CI) prediction was already presented using classical time series methods, artificial intelligence algorithms, among other approaches. In this paper, two methods are proposed to predict the CI. The first one solves a stochastic realization problem to find a mathematical model for the stochastic process that describes the CI. Then, a state observer is implemented to predict its future values. The second one performs the k-Nearest Neighbors (k -NN) regression algorithm for time series forecasting using two different approaches: the traditional k -NN and a recursive version proposed by the authors. As far as the authors know, the statistical and the recursive k -NN methods are different from the ones found in the literature to predict the CI. The methods were implemented and compared for short and long-term predictions. The results illustrate that one approach is more accurate than the other, depending on the prediction horizon. The comparison between the methods for different horizons is another contribution of this paper. • Statistical and AI algorithms were implemented to forecast the Clearness Index. • The statistical algorithm is based on state space stochastic realization theory. • The AI algorithm is the k-NN, implemented in two different versions. • The algorithms were compared for short and long term predictions. [ABSTRACT FROM AUTHOR]

Using delayed detached-eddy simulations, the objective of this paper is to show the effects of some design parameters on the wake recovery of vertical-axis turbines. To that end, the wake dynamics of a single-blade turbine is analyzed and compared for two different positions of blade attachment point and for two designs of blade support structures (struts). The results show that the chordwise position of the blade attachment point affects the temporal evolution of the blade circulation during the turbine revolution. More precisely, we demonstrate that an attachment point positioned near the trailing edge of the blade leads to a temporal vorticity distribution that is detrimental to the wake recovery. Moreover, we show that the use of tip struts, that are highly beneficial to the turbine efficiency, affects the spatial distribution of the vortex structures shed by the turbine as well as the wake recovery. The results presented in this paper suggest that the velocity recovery in the wake is highly dependent on the very near-wake vortex dynamics. Therefore, we can infer that any geometric parameter affecting the temporal and spatial distributions of the vorticity shed by the blades can significantly alter the wake recovery of vertical-axis turbines. [ABSTRACT FROM AUTHOR]

Hydrogen fueling stations (HFSs) with onsite hydrogen production systems, which are usually composed of electrolyzers, hydrogen storage tanks and fuel cells, not only supply hydrogen for hydrogen-powered vehicles but also serve as a dispatchable technology that can bid in electricity markets. Except participating in energy market, joining in reserve market can compensate the cost in energy market and increase the total revenue of HFS. This paper proposes a multi-stage stochastic programming model to find the optimal offering strategy of the HFS in energy, reserve markets taking into account a series of uncertainties: day-ahead price, secondary reserve price, system imbalance price and hydrogen demand. Nonanticipativity constraints are employed to guarantee the decisions are made according to the realized uncertainty information up to the present stage. Compared with traditional stochastic programming model, the proposed model adequately considers the sequential bidding decisions with the gradual revealing of the uncertainty over time. Numerical experiments based on one case study indicate that the participation of reserve market greatly increase the revenue of HFS. In addition, the proposed multi-stage stochastic programming model is effective in characterizing the sequential decision. • This paper proposes a multi-stage stochastic programming model. • To find the optimal offering strategy of the HFS in energy, reserve markets. • A series of uncertainties such as day-ahead price, and hydrogen demand are considered. • Nonanticipativity constraints are employed to guarantee the sequential decisions. [ABSTRACT FROM AUTHOR]

System risks caused by volatility spillover would possibly threaten the stability of financial markets. Effective control of volatility spillover is conducive to prevent of financial system risks. Therefore, this paper studies volatility spillover in the main renewable energy markets from 2010 to 2019 and analyzes how risks spread in hope of finding effective management to reduce financial system risks. For this purpose, this paper identifies the volatility spillover effect from a multidimensional perspective by using the BEKK model and reveals the risk spread path by using the multidimensional analysis method. Further, the risk spread relationships among the renewable energy markets are comprehensively analyzed. The main findings of the paper are: (1) The volatility spillover in the renewable energy markets tends to exist in the high dimensions. (2) In the renewable energy market system, the volatility spillover relationships involving multiple markets are more complicated than those between two markets. (3) The fuel cell energy market and solar energy markets occupy a significant position in the path of risk spread which should be paid more attention by policymakers to prevent financial system risks. [ABSTRACT FROM AUTHOR]

The challenge of global warming requires deep decarbonization of the electricity system, which can be achieved with a higher share of renewables in the electricity mix. However, the driving mechanism for renewable penetration in electricity production has not been clearly revealed so far. Using the data of the European Union (EU) during 2001–2017, this paper aims to investigate the spatial-temporal heterogeneity and dynamic evolution mechanism of renewable electricity penetration. To this end, from the investment-production-consumption perspective, renewable electricity generation is decomposed into seven factors through temporal and spatial factor decomposition methods. Then, this paper integrates the factor decomposition results into a coupling elasticity analysis to study the dynamic evolution mechanism of renewable penetration in electricity production. The results are as follows. (1) Investment structure contributes the most to increasing renewable electricity generation, while the energy intensity effect and renewable generation-to-capacity ratio effect are the main reasons for the reduction in renewable electricity generation. The effect of technological structure is minor. (2) The economic scale effect and the investment structure effect are dominating factors accounting for the regional difference of renewable power generation between the EU countries and the benchmark region. (3) The progress of renewable electricity penetration accelerates over time for the EU, western EU, and eastern EU. The Western EU has realized remarkable progress in facilitating renewable electricity penetration during 2009–2017. (4) On the whole, the investment effect makes the largest contribution to promoting renewable electricity penetration, while the production effect is the major inhibiting factor, showing that there is considerable potential in renewable generation efficiency improvement in the EU. This paper provides insightful implications for energy policies aimed at the shift towards a low-carbon electricity system in the EU, which also gives a reference for other economies. [ABSTRACT FROM AUTHOR]

To fully extract the potential of offshore wind power, the wind farms are built further from mainland and the capacity is growing larger. Low Frequency AC (LFAC) transmission System is a promising solution to the integration of large offshore wind farms in long distance. This paper conducts a comparative economic analysis of LFAC. Compared to 50 Hz High Voltage AC (HVAC) transmission, LFAC can reduce charging current in AC cables to enhance the transmission ability in long distance. Compared to High Voltage DC (HVDC) transmission, LFAC eliminates the large expense of offshore converter station. In addition, the topologies of AC/AC converter in LFAC also influences the economic performance significantly. By designing typical AC/AC converters based on modular multilevel technique in a unified way, this paper performs a full-scale economic comparison in different voltage level, active power and reactive power cases. Furthermore, the economic comparison based on capital cost of HVAC, HVDC and LFAC is comprehensively studied considering different transmission capacity and the AC/AC converter topologies. The economic range of HVAC, LFAC and HVDC application is obtained, and results show that LFAC is suitable for medium distance circumstances (around 80–200 km). The economic range of LFAC expands when power rating increases. • Economic range of HVAC, HVDC and LFAC is analyzed according to their capital cost. • Converter topologies and transmission capacity is considered in the cost of LFAC. • Comprehensive comparison of four AC/AC converter topologies for LFAC is conducted. • A unified method is introduced to design four AC/AC converter topologies. [ABSTRACT FROM AUTHOR]

There has been an increase in the use of renewable energy sources over recent years, which has led to a strand of literature examining the determinants of renewable energy consumption. However, most of the research used linear estimation models while reviewing the determinants of renewable energy consumption and ignored the indirect effect of democratic institutions on renewable energy consumption. With the use of a panel threshold model, this paper demonstrates that democratic institutions play a significant role in renewable energy consumption. In countries in which the democratic rights of people are preserved better, higher economic growth leads to increased use of renewable energy consumption; however, there is a negative association between economic growth and renewable energy consumption in less democratic countries. Increased trade openness leads to lower growth rates of renewable energy consumption in less democratic countries, while increases in real oil prices lead to increased renewable energy consumption in less democratic countries but play no significant role in more democratic countries. The findings of this paper suggest that democratic institutions are vital in channelling economic resources (economic growth) to renewable energy, and increased trade openness is associated with lower rates of renewable energy deployment in less democratic countries. [ABSTRACT FROM AUTHOR]

In many countries distributed energy resources (DER) (e.g. photovoltaics, batteries, wind turbines, electric vehicles, electric heat pumps, air-conditioning units and smart domestic appliances) are part of the 'Green Deal' to deliver a climate neutral society. Policy roadmaps, despite providing a framework and penetration targets for DER, often lack the network planning strategies needed to transition from passive to active distribution networks. Currently, DER's dynamic performance parameters and location identification techniques are not fully standardised. In fact, it can be very ad hoc. Standardised distributed load modelling and non-intrusive load monitoring (NILM) for equipment manufacturers, installers and network operators is critical to low and medium voltage network management in order to facilitate better balancing, flexibility and electricity trading across and within the power system for mass DER deployment. The aim of this paper is to fill this load modelling and NILM knowledge gap for DERto inform the 'Green Deal' transition and support standardisation. In the paper, existing load modelling techniques and NILM methodologies are critically examined to inform and guide research activity, equipment development and regulator thinking, as well as network operators. Seven key findings that need urgent attention are identified to support a smooth power system reconfiguration. [Display omitted] • A thorough review of existing monitoring and modelling methods for DER on distribution networks is provided. • Efficacies between 65% and 95% for conventional load identification exist. • Increasing DER penetrations are creating technological challenges in distribution networks. • Optimum DER integration in low voltage networks is vital for electric networks reliability. • Seven aspects to enable massification of DER on distribution networks are established. [ABSTRACT FROM AUTHOR]

This paper presents an experimental study on the effects of joint wind and operating loads (JWOLs) on the long-term performance of monopole-supported wind turbines (MWTs) standing on soils. In this paper, a novel loading method that can apply ambient excitation without constraints and generate random fluctuating loads around a non-zero mean is proposed to simulate JWOLs. The method was realized using a wind tunnel. A series of wind tunnel tests with different JWOLs were designed and performed on a 1:100 MWT model of the NREL 5 MW wind turbine. The effects of the average load in the fore-to-aft (F–A) direction and the fluctuating loads in the F–A and side-to-side (S–S) directions on the long-term performance of MWTs (including the variations in the natural frequency, damping ratio, and the accumulated deformation) were studied. The test results show that the variation in the natural frequency is marginal (within −2.1% to 3.6%), whereas that in the damping ratio is within −63.9% to 38.4%. The accumulated deformation curve under different conditions can be represented using a power function. The long-term performance problems (the frequency shift and the accumulated deformation) of MWTs observed under simple harmonic loads may be high to an extent compared with those observed under certain JWOLs. [ABSTRACT FROM AUTHOR]

This paper considers off-grid microgrids (MGs) from the Philippine archipelago and analyses their energy generation in differents aspects. Seven different energy clusters are used, representing realistic configurations and renewable energy shares. A Robust Model Predictive Control (MPC) framework is used for the energy management and coordination task of these island MGs. The MPC is based on a min./max. optimization procedure, which takes into account the whole uncertainty set. The reliability of the MG operations are analysed with respect to the different clusters; this evaluation is conducted using μ -analysis, performed with respect to the baseline model and the uncertainty set. The demand-side compliance of the MG is also investigated, with respect to stochastic behaviours of the demands and of the renewable sources (wind and solar). Numerical simulation results are presented in order to demonstrate that reliable power outlets are produced despite variation in renewables and of the demands. This paper offers a thorough analysis of simple energy system coordinated via MPC, showing how this method can indeed be used for renewable MG management, offering robustness and ensuring reliability. • A generalized model is presented for Off-Grid Microgrids with multiple carriers. • The Philippine Off-grid islands are considered, with diesel, solar, and wind energy. • A Robust Model Predictive Control scheme is proposed to manage these Microgrids. • Demand compliance and operation reliability are assessed through robustness analysis. • Numerical simulation illustrate reliability under multiple scenarios. [ABSTRACT FROM AUTHOR]

The installation of fast electric vehicle charging stations (EVCS) will be essential to promote the acceptance by the users of electric vehicles (EVs). However, if EVCS are exclusively supplied by the grid, negative impacts on its stability together with possible CO 2 emission increases could be produced. Introduction of hybrid renewable energy systems (HRES) for EVCS can cope with both drawbacks by reducing the load on the grid and generating clean electricity. This paper develops a weighted multicriteria methodology to design the most suitable configuration of HRES for EVCS. This method determines the local renewable resources and the EVCS electricity demand. Then, taking into account environmental, economic and technical aspects, it deduces the most adequate HRES power generation planning for EVCS. Besides, an experimental stage to validate the design deduced from the multicriteria methodology is included. Therefore, the final power generation planning for the HRES in EVCS is supported not only by a complete numerical evaluation, but also by an experimental verification of the demand being fully covered. Methodology application to Valencia (Spain) proves that an off-grid HRES with solar PV, wind and batteries support would be the most suitable configuration for the system. This solution was also experimentally verified. • The paper presents a novel multicriteria methodology to design HRES for EVCS. • An experimental stage of the power balance and SOC is included in the methodology. • Valencia (Spain) is chosen as a case study due to its environmental policies. • The best configuration is an off-grid HRES with solar PV, wind resources and batteries. [ABSTRACT FROM AUTHOR]

Trees absorb CO 2 and reduce the impact of GHGs. This paper deals about the carbon uptake dynamics produced by the management of unused lands as tool to help the fulfilment of international commitments on atmospheric CO 2. The paper introduces a new perspective of using the unused lands around Municipalities to compensate the carbon emissions of urban contexts, according to the Sustainable Energy Action Plans as answer to climate change, already approved by the most part of Cities in Europe. The model of the carbon dynamics is based on a genetic algorithm which allows to find the sequence of operations on the unused land in space (portions of the land) and time (rotation of cuts and plantations) to ensure the reaching of a given outcome in terms of carbon captured. The algorithm, therefore, behaves as design support of land management, enriching the literature available for the sector. The paper identifies two possible original scenarios of storing carbon referred as " emergency " and " constant rate "; the first produces after fifty years a maximum carbon uptake of the order of 100 tC/ha while the second a maximum uptake rate of the order of 2 tC/(year ha), after an initial start-up period of 40–50 years. • Mathematical model to evaluate tree growth and carbon sink from reforestation. • Optimization model to manage the carbon uptake in different scenarios. • Forest represents an effective way to remove carbon from atmosphere. • Carbon stock per unit of unused areas around cities and urban area. • Climate mitigation tool suitable by municipality in the context of SECAPs. [ABSTRACT FROM AUTHOR]

The global economic costs of environmental pollution increase the importance of renewable energy sources. This paper analyzes the impact of financial development on renewable energy consumption in 34 upper middle income developing countries from 1994 to 2015. The long-term relationship between variables is estimated by applying Panel Pedroni cointegration and Kao cointegration tests. The long run effect of financial development on renewable energy consumption is investigated by using Fully-Modified OLS (FMOLS) approach. The empirical results indicate the presence of long run relationship between renewable energy consumption and financial development. Moreover, financial development increases the demand for renewable energy. Economic growth has a negative effect on renewable energy consumption, but consumer prices have a statistically insignificant impact on renewable energy consumption. The empirical evidence reveals that financial development triggers in increasing demand for environmentally friendly energy sources, i.e., renewable energy. Renewable energy consumption reduces the amount of greenhouse gases in nature as opposed to fossil energy consumption. Therefore, to achieve sustainable development goals, governments should implement incentives and tax policies that increase the demand of enterprises for renewable energy resources. In addition, investment opportunities in renewable energy resources to be created by public-private cooperation via financial arrangements should be increased. - This paper examines how financial development affects renewable energy consumption? - The panel Pedroni cointegration and Kao cointegration approaches are applied. - The Fully-Modified OLS (FMOLS) approach is employed for long run association. - Financial development promotes renewable energy demand. - Economic growth declines renewable energy consumption. [ABSTRACT FROM AUTHOR]

In this study, projections and current status of municipal solid waste generation worldwide and its collection, final destination, and waste-to-energy technologies are reviewed. Firstly, an overview of waste generation worldwide is presented comparing income levels and the material composition of residues in several regions. This paper focused on contrasting Brazil and Portugal in terms of waste production and its management from generation to disposal or treatment. Furthermore, it is presented a summary of leading waste-to-energy technologies such as incineration, anaerobic digestion, gasification, pyrolysis, co-combustion, co-gasification, among others. Technical aspects of these thermo-chemical, biological, and physic-chemical processes for the production of biofuels such as biogas, syngas, biodiesel, and hydrogen-enriched gases are presented. Additionally, current aspects of the waste-to-energy market are exposed regarding the major players, investments, and expectations for the future of this activity with the elaboration of SWOT analyses. Finally, a review of greenhouse gases emissions worldwide is presented, specifically from Brazil and Portugal, as well as some consequences of these pollutant gases on the society and the environment and which are the main technologies for carbon dioxide capturing and sequestration as promising solutions for lower pollutant gases concentration in the atmosphere. This review paper aims to provide information for the management of municipal solid waste in Brazil and Portugal considering the mutual objective of meeting sustainable development goals. [ABSTRACT FROM AUTHOR]

This paper proposes a unified filtering framework for multi-horizon wind speed prediction. The novelty of this paper focuses on the integration of the short-term prediction model, the Numerical Weather Prediction (NWP) and a smoothing term into a unified framework based on Bayesian filters. In the proposed framework, the system state function of the Bayesian filter is constructed by a pre-trained static model based on Gaussian Process Regression (GPR) to enhance the short-term prediction accuracy. Meanwhile, NWP data is integrated by the system input of the state function of the Bayesian filter. The integration of NWP guarantees the medium/long-term prediction accuracy. The measurement function of the Bayesian filter is constructed as a smoothing term to further improve the overall accuracy of the proposed method. The prediction accuracy of the proposed filtering framework is extensively benchmarked with other existing approaches based on the data from an offshore wind farm. The benchmarking results suggest that the proposed method yields improved prediction performance in short-term horizon. For medium/long-term horizon, the best accuracy of RMSE is improved by about 46% compared with the benchmarks. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate the association between hydroelectric energy consumption and CO 2 emissions in the USA from 1980:1 to 2019:8 by using the wavelet transform model. This research revealed that (a) in the short runs (at higher frequencies), hydro energy uses intensified CO 2 emissions for the periods 1990:01–1992:12, 1994:01–1994:12, and 2002:07–2007:11, and (b) during the longer periods (at lower frequencies), however, hydro energy consumption diminished CO 2 emissions for the periods 1983:01–2001:12 and 2011:01–2017:03. The paper explained as well why hydro energy can yield adverse and affirmative contributions to Greenhouse gas emissions by emphasizing the role of energy generation from hydro plants in shorter runs and longer runs in the USA considering all sub-samples of the sample period 1980:1–2019:8. This research eventually suggests some energy policies to enhance the positive environmental influences of hydropower energy production in the USA. [ABSTRACT FROM AUTHOR]

Occurrence of partial shading and its high impact on the performance of photovoltaic (PV) system have received considerable attention during the last few years. It has forced the researchers to explore more novel PV array configurations to sustain under partial shading conditions (PSCs). To diminish the effects of PSCs, this paper presents an overview of the state-of-the-art developments of various PV array configuration models for PV systems. Different modelling approaches are analyzed while emphasizing their benefits and inadequacies. Different models available in the recent state-of-the-art literatures are studied and categorized according to vital configurations and features. Mainly, various PV array configurations such as advanced, futuristic configurations are also compared with the existing configurations. In this paper, recent research developments (that deserve further examination) are acknowledged and deliberated for the future researchers working in this domain. • Conventional, hybrid and advanced configurations are investigated. • Investigation using P–V profile, power losses, fill factor, performance ratio and shade dispersion is done. • Performance of advanced configuration is compared with the existing and hybrid configurations. • Electrically reconfigured type of advance PV array configuration is found better than physically reconfigured type of advance PV array configuration. [ABSTRACT FROM AUTHOR]

This paper investigates the sustainability of Tabriz City focusing on its decarbonization. Statistical, quantitative, and comparative research methods are used to analyze the total energy consumed, conversion of primary energy, final exergy, and losses analysis according to the renewable and carbon-based energies. Then, the renewable resource potentials of the city are simulated using Grasshopper plug-in-Rhino simulator, THERM, PVSyst photovoltaic software, and ArcMap. In terms of the socio-economic assessment, non-oil Per Capita GDP, emissions, and energy intensities are analyzed concerning the B2DS scenario by 2050. The per capita GDP of the city is 71% of the country's average value. Tabriz's real GDP growth averaged −1.11% per year, primary energy demand increased by an average of 6.1%, CO 2 emissions from energy use grew by an average of 6% annually and the emission intensity of the economy increased by a total of 52.02%, in the period from 2011 to 2019. Finally, it is shown that the city consumes 58050 GWh/year of different carbon-based resources that only produced 20110 GWh/year of useful work with 5.63 MT CO 2 emissions, while the same work could locally be supplied by 30000 GWh/year RE with a minimum rate of 0.18 MT CO 2 emissions. The city Landfill receives 1000 tons/day of MSW, but two-thirds of this amount can be recycled. Regarding different sectors, buildings produce half of the CO 2. The cement industry with dual pollutants (17%) is the most polluting factory. Carbon-based electricity (66%) is the most polluting form of energy. In terms of carbon sequestration requirements with trees, shifting from fossil fuels toward green energies, EE, and recycling MSW can plunge required trees from 81.9 to 1.16 million trees. This paper highlights the importance of electrification of transportation based on RE, energy performance of buildings, and all sectors. • Large city decarbonization strategies • Application of RE according to geographic and climatic factors. • Electrification of sectors based on RE locally. • MSW recycling and sequestration by trees for decarbonization regarding the LULC and NDVI analysis. • Conversion and storage efficiencies of carbon-based fuels vs RE. [ABSTRACT FROM AUTHOR]

Integration of solar photovoltaic systems to low-voltage distribution networks is witnessing an unprecedented growth in many parts of the world. Although solar photovoltaic generation is of significant benefit from a number of angles, exceedance of hosting capacity levels by such installations in low-voltage distribution networks continue to cause significant technical challenges in network operation, especially to the management of network voltage. Modern smart inverters are equipped with Volt-VAr and Volt-Watt control capabilities, which can assist in the management of network voltage levels. This paper provides a detailed analysis of the influence of different connection standards which cover these strategies on solar photovoltaic hosting capacity and their applicability in low-voltage distribution networks. Smart inverters with differing Volt-VAr and Volt-Watt control functions are modelled in the DIgSILENT PowerFactory platform. Influence of different connection standards on solar photovoltaic hosting capacity is analysed to investigate the most beneficial connection approach/es to address the issue of voltage violations. Furthermore, the work presented in this paper provides a greater understanding on the hosting capacity improvement by employing advanced inverter control functions where such improvements are subjected to locational aspects of inverters in low-voltage distribution systems. • Control strategies: Volt-VAr, Volt-Watt and combined Volt-VAr & Volt-Watt were assessed. • Combined Volt-VAr & Volt-Watt control is effective in enhancing hosting capacity. • Hawaii Rule 14 and IEEE 1547 are effective to increase solar PV hosting capacity. • Volt-VAr control is the most effective with bare conductors. • Volt-Watt control is the most effective with bundle cable type feeders. [ABSTRACT FROM AUTHOR]

In recent years, harvesting solar energy as a renewable and sustainable energy source has been studied extensively across engineering fields. Having reviewed more than 50 large-scale projects of Hydronic Asphalt Pavement (HAP), this paper offers a series of findings: the range of construction cost of asphalt collector varies between 25 and 151 €/m2 and 1.760–3.000 €/m2 for the heat exchanger and the total cost. The energy harvest capacity of asphalt solar collector systems (0,6–0,8 GJ/m2/year) and the required amount of heat for snow melting projects (100–900 W/m2) vary significantly in different projects. Using grid supports for easier pipe placement and protection of pipes against heavy loads during and after construction is recommended. Pavement solar collector systems reduced carbon dioxide emissions by 8–100% in different projects by changing their source of energy from fossil fuels to renewable and sustainable sources. Moreover, in order to further evaluate the sustainability of the HAP systems, a detailed life cycle assessment is required, including all available data related to the energy performance, pavement service life, material end-of-life recycling, etc. Finally, the paper identifies the knowledge gaps requiring further research especially in the area of energy output of the HAP systems, pavement service life and life cycle assessment. • A comprehensive review of large-scale hydronic asphalt pavement projects is provided. • Potential challenges in the large-scale hydronic asphalt pavement are investigated. • Technical specifications, operational aspects and performance are explored. • Construction cost and structural response of systems are analyzed. • The projects' performance is evaluated based on energy output and sustainability. [ABSTRACT FROM AUTHOR]

Water and electricity distribution networks are two highly interdependent and critical infrastructures in the world today. This paper investigates the coupling of water and electricity distribution networks through the electrical energy demand of water pumps. Further, with additional variable renewable energy (VRE) sources in the distribution system, utilities face significant challenges stemming from the VRE stochasticity. In this paper, a coordinated operational model of urban water and electricity distribution networks is proposed. Stochastic VRE generation is handled by using a data-driven probability efficient point (PEP) method based on historical wind and solar datasets without the need for any probability distribution function. Case studies are performed on a modified Institute of Electrical and Electronics Engineers (IEEE) 13-node electricity distribution network coupled with a 10-node water distribution network, typical of a small-town setting. Results show the impact of coordinating water and energy networks on the cost of operation and the distribution locational marginal prices (DLMPs). The inclusion of water tanks as alternative storage devices in the electricity distribution network are shown to slightly reduce voltage violations, line congestion, and VRE curtailments in a case with high VRE penetration. [Display omitted] • Propose coordinated water and electricity distribution model. • Stochastic renewable generation is handled by probability efficient point method. • Water tank storage improves network condition, distribution locational marginal price. [ABSTRACT FROM AUTHOR]

The overall operational costs of home energy systems (HES) has been considered as an objective function (OF) by many articles. This paper shows that considering the energy cost as OF can lead to a decrease in the load elasticity against the electricity price, which can lead to demand response programs failure. So the distribution system operator (DSO) must stop this decline. A new index is introduced to calculate the responsiveness of the PV-integrated HES, based on which a new OF for home energy management system is proposed. This index shows the load elasticity against the electricity price. The relation between energy cost and load responsiveness index is investigated, and several scenarios are analyzed to demonstrate the applicability of the proposed approach in real cases. The proposed method is implemented to a PV- and ESS- integrated HES. The results show the relation between the responsiveness of the loads and the operational costs of home. A sensitivity analysis is added to the paper to show the robustness of the proposed control scheme. • Considering the energy cost leads to a decrease in load elasticity against price. • A new index is proposed to calculate the responsiveness of HEMS, based on a new OF. • Home loads responsiveness index relation with the energy supply cost is discussed. • Roles of ESS to improving the responsiveness of residential loads are investigated. • ESS roles to reduce negative effect of PV in increasing PAR of HES are investigated. [ABSTRACT FROM AUTHOR]

Systems involving more than one energy source, namely hybrid systems, can be arranged in different configurations and layouts depending on the available or used energy source, application and scale of the system. Despite an increasing awareness and penetration of renewable energy sources at different scales in many countries over the world, the adoption of hybrid and novel renewable systems is relatively scarce, especially at a small scale. This scenario is also presented from the point of view of the research of such systems. Therefore, the scope of the paper is to improve the knowledge regarding small-scale hybrid renewable energy systems performance and operation by investigating a novel trigeneration system based on a biomass fired steam cycle, wind turbine, photovoltaic panels and adsorption chiller. In the proposed system, the thermal energy recovered by the steam cycle is used to match the user thermal demand by means of a storage tank supplying directly heat to the user during winter, and driving the adsorption unit during summer. The electrical energy produced by the steam turbine, photovoltaic field and wind turbine is managed by a control system that integrates a bidirectional connection with the electric grid. The grid allows one to virtually store the electrical energy produced in excess and to recover it in part when needed by the user. In order to assess the system performance, a farm and residential buildings are considered as case study. The proposed system is modelled and dynamically simulated by means of Transient System Simulation software. In the paper, the dynamic operation of the system and the energy and economic performance of the system is assessed. The operation of the system is presented in a daily and monthly basis, while the global performance parameters of the system are reported considering a one-year period. The primary energy saving of the system is above 70% when a reference system based on natural gas, electric chiller and grid is considered. For this scenario, the Simple Pay Back of about 10 years is achieved. The results of the analysis show that the system is feasible from the technical and energy point of view, whereas its economic profitability is significantly affected by its cost and the reference system that is adopted by the user. • Modeling and dynamic simulation was performed with TRNSYS software. • Energy and economic performance of the system was assessed. • Different reference systems are considered for heating. • Primary Energy Saving ratio was between 57.4 and 73.3%. • The minimum Simple Pay Back is about 10 years. [ABSTRACT FROM AUTHOR]

Distributed energy systems are becoming increasingly popular worldwide. The 100% renewable energy system can be an important energy supply alternative to reduce the carbon emissions and address energy shortage, especially for remote areas. However, the performance of 100% renewable energy system (RES) at community level needs further detailed analysis, which is affected by the climates, availability of renewable energy and local energy markets. This paper proposes a design optimization framework of 100% renewable energy systems for low-density communities and investigates the system performance. To investigate the integration and performance of 100% RES, thirty typical cities located in different regions of China were chosen considering different climates, geographical features, and renewable energy distributions. By taking the economic performance as the optimization objective, the optimal design for the 100% RES is obtained, and the energy and economic performance is analyzed. Results show that, under the current energy market conditions, the 100% RES is feasible for low-density communities in most regions of China. The payback periods of the systems in most cities are less than six years. When the cost of PV is reduced by half considering future technological developments, the payback period of a 100% RES can be reduced by 30%–60%. This paper would provide design suggestions and application recommendations in regard to promoting 100% RES in China. • Application of 100% renewable energy system at community level is studied. • 30 zones are selected considering climates, renewable energy sources and markets. • Solar energy and biomass can contribute to over 90% of the total energy supply. • Investment of 100% RES can be paid back in 6 years for most regions. • Payback periods can be reduced by 30%–60% when PV technology is further developed. [ABSTRACT FROM AUTHOR]

With the advent of large-scale photovoltaic module decommissioning, China's photovoltaic recycling industry is confronted with numerous challenges. This paper examines the barriers to the recycling of waste photovoltaic modules. First, 11 Barriers affecting the recycling of waste photovoltaic modules were identified through sorting; second, the Decision-making Trial and Evaluation Laboratory (DEMATEL) and Interpretative Structural Modeling (ISM) method was improved by incorporating the Hesitant Fuzzy Linguistic Term Set (HFLTS) and the time factor, and an obstacle analysis framework based on this method was built; finally, the interaction relationship between the obstacles to recycling was investigated. According to the study's findings, the difficulty to do recycling operations in batches for an extended period of time , costly initial investment , lack of incentives and small market size are the major constraints affecting the recycling of waste PV modules. After 10 years, the impact of costly initial investment and small market size will diminish, while the impact of inadequate infrastructure will increase. To eliminate critical impediments and encourage the healthy development of the photovoltaic recycling industry, the government should carry out work in four areas: recycling standards, incentive policies, technology research and development, and demonstration site construction. [ABSTRACT FROM AUTHOR]

Recently, renewable energy generation (REG) forecasting has become a challenging task for effective energy management. To date, a number of time-series models utilizing physical models, statistical techniques, and artificial intelligence algorithms have been proposed to deal with this problem. Fuzzy time series (FTS) models stand out among these methods since they do not need extensive historical data or some statistical assumptions like the normal distribution. Because intuitionistic fuzzy sets incorporate non-membership values in addition to membership values, they provide more information than conventional fuzzy sets do. In this regard, this paper recommends a hybrid methodology that combines the intuitionistic FTS method with the intuitionistic fuzzy c-means method for REG forecasting of Turkey between the years 2000–2020. According to the empirical results, it can be concluded that the presented integrated model showed good performance in terms of accuracy. The suggested framework is a useful tool not only for REG forecasting but also for other time series forecasting problems. [ABSTRACT FROM AUTHOR]

Power-to-ammonia (P2A) technology has attracted more and more attention since ammonia is recognized as a natural zero-carbon fuel. In this context, this paper constructs a renewable energy powered multi-energy hub (MEH) system which integrates with a thermo-electrochemical effect based P2A facility. Subsequently, the energy management of proposed MEH system is casted to a multi-agent coordinated optimization problem, which aims to minimize operating cost and carbon dioxide emissions while satisfying constraints. Then, a novel multi-agent deep reinforcement learning method called CommNet is applied to solve this problem to obtain the optimal coordinated energy management strategy of each energy hub by achieving the distributed computation of global information. Finally, the simulation results show that the proposed method can achieve better performance on reducing operating cost and carbon emissions than other benchmark methods. [ABSTRACT FROM AUTHOR]

Hydraulic structures can be a promising place for tidal energy extraction due to the high flow velocities, easy access to the power grid and easy access for maintenance. However, quantification of the impacts of a tidal power plant in a hydraulic structure is not straight forward. In 2015 a pilot plant consisting of an array of five Tocardo tidal turbines was installed in the Eastern Scheldt Storm Surge Barrier in the Netherlands. This pilot was accompanied by monitoring studies to verify that the operation of the plant had no adverse impact on the barrier and its surroundings. This paper presents the assessment of the hydraulic impact of the tidal power plant in the storm surge barrier based on an analysis of water level and current measurements, combined with numerical modeling and followed by an assessment of the environmental impact with emphasis on the effects on the intertidal areas in the estuary. This validation approach by a pilot plant is imperative to understand the interaction between tidal turbines and the hydraulic structure on the local scale. This understanding gives extra credibility to the predictions of the extrapolated large-scale and large array assessments which will always be fully numerical. [ABSTRACT FROM AUTHOR]