Energy transition in islands constitutes a major challenge. Apart from a necessity, it can also be a great opportunity for sustainable social and economic development. Toward this direction, a new, promising movement has emerged recently in Greek islands. Straight from the roots of the insular population, development of energy communities comes as the result of increased awareness of local people, raised also by the legacy of lighthouse projects and initiatives. Kythnos, Ikaria, Sifnos, Tilos, Agios Efstratios, Crete, and Chalki, are all islands that have embraced the implementation of successful, local-scale innovation projects and/or initiatives, generating meaningful results across different energy aspects and contributing to positive social change. Our study provides an overview of the broader energy transition aspects in Greek islands, discusses the impact of the aforementioned exemplary cases, and further elaborates on the model of energy communities. According to our analysis, l... [more]

In a developing country such as Malaysia, studies of determinants which influence residential consumers of the Battery Energy Storage System (BESS) are limited. This paucity of studies was the catalyst for this study and its aim to investigate the factors affecting acceptance by Malaysian residential consumers of BESS as it relates to the Technology Acceptance Model Theory. A sample of 331 residential consumers indicated that consumer attitudes, social norms and self-efficacy, or the perception of behavioral control, had a positive and significant relationship with the intention to use BESS. Additionally, trust was a factor that had a significant effect on the consumers’ perceptions of cost, benefits and anticipated effects. All these variables significantly affect consumer attitudes. These findings provide important insights into BESS and facilitate the development of policies and practices relating to BESS in developing countries such as Malaysia.

Renewable and clean energy sources are being integrated into the United States’ modern energy industry to mitigate climate change effects, creating a more complex network of energy production, distribution, and consumption. This study defines the state of Maryland’s energy industry as a network of producers and consumers and analyzes the network’s characteristics by using ecological network analysis (ENA), an analytical tool useful for identifying a system’s indirect effects. The energy industry within Maryland is analyzed over a nine-year time span to understand how its evolution is influencing the network’s characteristics. Maryland’s renewable portfolio standard (RPS) for the year 2030 is then simulated by adjusting renewable and non-renewable energy sources according to energy trends and related state policy. Results from the ENA over the nine-year period of 2010−2019 indicate that the energy industry is highly linear. While typical cycling indices range from 5−15% in ecological en... [more]

In this paper, renewable resources, namely photovoltaic panels (PV), are placed in a specific configuration to obtain the maximum reliability and availability of a microgrid and study the subcomponent-level reliability and availability. The reliability of components can be increased by trying different configurations of the components. We identify the preferred configuration used for the PV panels as bridged linked. The overall reliability of the microgrid is increased when component-wise reliability is considered. Even components are further divided into subcomponents, and the multiple faults of each component are considered. The method used for the reliability evaluation and availability study is Markov state transition modeling. The microgrid’s reliability and availability are plotted concerning time using Matlab. The optimization of reliability and availability is conducted through optimization techniques such as the genetic algorithm (GA) and artificial neural networks (ANN). The... [more]

Occupant behavior based on natural ventilation has a significant impact on building energy consumption. It is important for the quantification of occupant-behavior models to select observed variables, i.e., features that affect the state of window opening and closing, and to consider machine learning models that are effective in predicting this state. In this study, thermal comfort was investigated, and machine learning data were analyzed for 30 houses in Gifu, Japan. Among the selected machine learning models, the logistic regression and deep neural network models produced consistently excellent results. The accuracy of the prediction of open and closed windows differed among the models, and the factors influencing the window-opening behaviors of the occupants differed from those influencing their window-closing behavior. In the selection of features, the analysis using thermal indices representative of the room and cooling features showed excellent results, indicating that cooling fe... [more]

The technical focus of drilling operations is changing to oil and gas reservoirs with higher difficulty factors such as low permeability and fracture. During the drilling process, drilling operations in deep complex formations are prone to overflow and leakage complications. Leakage and overflow problems will change the performance of the drilling fluid in the wellbore, impacting the wellbore pressure, and causing complex accidents such as stuck drilling and collapse. In order to improve the level of control over the risk of wellbore overflow and leakage, it is necessary to predict the mud overflow and leakage situation and to arrange and control the risk of leakage and overflow that may occur in advance to ensure the safety of drilling. By using a genetic algorithm to optimize the multi-layer feedforward neural network, this paper establishes a GA-BP Neural Network Drilling overflow and leakage prediction model based on multi-parameter fusion. Through the optimization training of 14 p... [more]

The energy transition towards efficient energy production, transport, and use, renewable energy (RE) technologies and innovative energy management brings benefits to reducing greenhouse gas (GHG) emissions and achieving climate targets [...]

This paper presents a new metaheuristic approach based on a self-adaptive genetic algorithm (SAGA) for solving the short-term hydro-thermal-solar scheduling with combined-cycle (CCGT) units. First of all, the proposed approach is applied to a test system with different characteristics, considering the valve-point effect. The simulation results obtained from the new SAGA are compared with the results obtained from some other metaheuristic methods, such as AIS, DE, and EP to reveal the validity and verify the feasibility of the proposed approach. The test results show that the proposed metaheuristic approach proves the effectiveness and superiority of the SAGA algorithm for solving the short-term hydro-thermal-solar scheduling (SHTSS) problem.

Applications of the Internet of Things (IoT) are rapidly utilized in smart buildings and smart cities to reduce energy consumption. This advancement has caused a knowledge gap in applying IoT effectively by experts in the built environment to achieve energy efficiency. The study aims to provide an extensive review of IoT applications for energy savings in buildings and cities. This study contributes to the field of IoT by guiding and supporting built environment experts to utilize IoT technologies. This paper performed a thorough study using a systematic review that covered an overview of IoT concepts, models, applications, trends and challenges that can be encountered in the built environment. The findings indicated limitations in developing IoT strategies in buildings and cities by professionals in this field due to insufficient comprehension of technologies and their applied methods. Additionally, the study found an indefinite implementation and constraints on using IoT when integra... [more]

Membrane distillation (MD) is a thermal-based membrane operation with high potential for the treatment of aqueous streams. However, its implementation is limited and only few examples of MD pilots can be found in desalination. One of the reasons behind this is that MD requires thermal energy for promoting the evaporation of water, which implies higher energy consumption with respect to pressure-driven membrane operations, like reverse osmosis (RO). Recently, among the different methods investigated to improve the thermal efficiency of MD, attempts for obtaining a localized heating of the feed, close to the membrane surface, were carried out. This work reviews experimental activities on the topic, dealing with both modified membranes, used under solar irradiation or coupled to an electric source, and specifically designed heated modules. The main results are reported and points of action for further optimization are identified. In particular, although at an early stage, this type of app... [more]

The use of electric vehicles and their adoption have become imperative due to the policies and goals to reduce harmful emissions emitted by fossil fuel vehicles. The adoption and acceptance of electric vehicles by the public may be determined by several factors, such as the price of the vehicles, the environmental and political costs of vehicle production, infrastructure availability, etc. However, given the diverse context of each country, different factors may have a different impact on customer attitudes. According to that fact, the purpose of this research is to identify which factors influence attitudes towards the purchase of electric vehicles in the Republic of Croatia. In order to identify those factors, this paper is based on a survey in which 578 randomly selected respondents took part. The research was conducted between 1 October 2021 and 1 May 2022. The obtained research results were analyzed using linear regression, i.e., moderation analysis. The results indicated that the... [more]

Direct-drive generators are an attractive candidate for wind power application since they do not need a gearbox, thus increasing operational reliability and reducing power losses. However, this is achieved at the cost of an increased generator size, larger inverter and decreased thermal performance. The associated cooling system is therefore crucial to keep the generator and inverter sizes down and to operate within the safe thermal limits. Various cooling techniques suitable for generators are therefore reviewed and analyzed in this paper. The performance and maintenance requirements are unavoidable compromises that need to be investigated together, especially for large generators. The location of the wind turbine is also important and dictates critical issues such as accessibility and maximum size. The key novelty in this paper is the assessment of the cooling methods based on generator size, reliability and maintenance requirements.

Low resolution Hall-effect sensors have been commonly applied in PMSM drives for the reason of cost and volume. Generally, rotor speed and position are estimated inaccurately due to the installation error of the sensors. The inaccurate position degrades the performance of current control and also increases torque ripples, which aggravates mechanical vibration and noise. An improved dual observer is proposed in this paper to suppress the impact of misplaced Hall-effect sensors and improve estimation accuracy. By a cascading dual Luenberger observer and combining feedback decoupling control, the low-order noises produced by the deviation of Hall signals are effectively suppressed. The effectiveness of the proposed method is verified by experimental results.

The world increasingly requires biodegradable and renewable products in all production fields, with the vast volume of emissions generated by the fuel sector presenting a difficult issue that needs to be addressed [...]

In terms of human needs, water has traditionally been regarded as the most significant bioresource. However, there are still limitations on the quality and mobility of drinking water. Renewable energy technologies are at the forefront of research to bridge the gap between conventional fuels and renewable energy systems. Currently, the main objective is to speed up the solar water disinfection process of contaminated water when hybrid nanofluid mixtures are added. Five hybrid nanofluid mixtures containing different amounts of aluminum oxide (Al2O3) and Titanium oxide (TiO2) nanoparticles were used in this study, focusing on how they affected the solar disinfection of polluted water. Five hybrid nanofluid mixtures of different volumes and volume concentrations were used for this purpose; each one was introduced into a contaminated water-contained glass container with a volume of 500 mL. Additionally, a sixth container, used exclusively for comparison, was filled with tainted water. All c... [more]

To mine the battery’s health factors more comprehensively and accurately identify the lithium battery’s State of Health (SOH), an Improved Douglas−Peucker feature extraction algorithm is proposed, and the LAOS-XGboost model is proposed to be used to predict the SOH of the battery. Firstly, to solve the problem that the traditional Douglas−Peucker algorithm has difficulties extracting curve features in a fixed dimension, the Douglas−Peucker algorithm is improved by de-thresholding. Then, the Wrapper method combined with the Improved Douglas−Peucker algorithm is used to construct the feature engineering of battery life prediction, and the optimal feature subset is obtained. Then, LAOS-XGboost is used to establish a battery SOH prediction model; finally, this model is used to predict the SOH of different batteries and the same battery, and the robustness of the model is analyzed. The experimental results show that the R2 of all XGboost models is higher than 0.97 in the prediction experime... [more]

Concentrated solar power is capable of providing high-temperature process streams to different applications. One promising application is the high-temperature electrolysis process demanding steam and air above 800 °C. To overcome the intermittence of solar energy, energy storage is required. Currently, thermal energy at such temperatures can be stored predominately as sensible heat in packed beds. However, such storage suffers from a loss of usable storage capacity after several cycles. To improve such storage, a one-dimensional packed bed thermal energy storage model using air as a heat transfer medium is set up and used to investigate and quantify the benefit of the incorporation of different thermochemical materials from the class of perovskites. Perovskites undergo a non-stoichiometric reaction extension which offers the utilization of thermochemical heat over a larger temperature range. Three different perovskites were considered: SrFeO3, CaMnO3 and Ca0.8Sr0.2MnO3. In total, 15 vo... [more]

Nitrogen-rich biomass can be suitable for utilization as a substrate in anaerobic co-digestion (AC-D) instead of animal manure. This biomass combined with other substrates could replace animal waste in certain cases in which animal waste cannot be used to obtain methane gas. Methane is the majority component of the biogas produced in AC-D used as an energy source. In this research, a comparative study has been developed between leguminous plant biomass and pig manure in AC-D in a semicontinuous regime at different Organic Load Rate (OLR) values (1.2−1.8 g VS LD−1 d−1). The most elevated methane yield (494 NL CH4 kg VS−1) belongs to assays developed with nitrogen-rich biomass at 1.4 g VS LD−1 d−1. Methane-yield results of nitrogen-rich biomass are higher than pig manure results for all OLR studied values. The digestate obtained in the AC-D is a fertilizer of interest due to its nitrogen content and ability to save energy by replacing mineral fertilizers.

In many competitive electricity markets around the world, the dynamic behavior of hourly electricity prices is subject to significant uncertainty and volatility due to electricity demand, availability of generation sources, fuel costs, and power plant availability. This work is devoted to describing and comparing the dynamics of electricity prices for some markets in Europe, selecting the five countries representing the largest economies in Western Europe (France, Germany, Italy, Spain, and the United Kingdom). Additionally, Denmark is included in the study to assess whether the size of the country is a determinant of price behavior. The six datasets of hourly price series, which exhibits a strong daily seasonality, are modelled using the most relevant well-known statistical models for time series analysis: ARIMA models and different versions of GARCH models. The comparison of the estimated models’ parameters, the analysis of outliers’ rate of appearance and the evaluation of out-of-sa... [more]

A methodology is outlined for equipment selection for the extraction of secondary deposits, supported by the Multiple Criteria Decision Making (MCDM) tool based on the Analytic Hierarchy Process (AHP) method and applied to evaluate its impact on the mining system’s performance and the viability of the rock mining project. The equipment selection analysis affords us the means to explore selected options, taking technological and economic parameters into account, and opening the way for making the decision to begin or discontinue mining operations. The simulation results show how maintaining the mining site in a good condition impacts on the actual duty cycle of mining equipment, the time required to complete the hauling task and the operating costs.

Combined heat and power (CHP) plants are known as efficient technologies to reduce environmental emissions, balance energy costs, and increase total energy efficiency. To obtain a more efficient system, various optimization methods have been employed, based on numerical, experimental, parametric, and algorithmic optimization routes. Due to the significance of algorithmic optimization, as a systematic method for optimizing energy systems, this novel review paper is focused on the meta-heuristic optimization algorithms, implemented in CHP energy systems. By considering the applied objective functions, the main sections are divided into single-objective and multi-objective algorithms. In each case, the units’ combination is briefly detailed, the objective functions are introduced, and analyses are conducted. The main aim of this paper is to gather a database for the optimization of CHPs, demonstrate the effect of the applied optimization methods on the objective functions, and finally, in... [more]

Cultivating microalgae requires a nitrogen and phosphorous feed source. Anaerobic digestion waste (digestate) provides a cheap sustainable feedstock for these materials. Previous studies have successfully demonstrated the feasibility of nutrient recovery and subsequent algae growth. There is now a need to fully characterise digestate filtration to improve our understanding of this process prior to its commercialisation. In this work, digestate filtration is characterised at bench scale using frontal (dead-end) filtration and a 100 kDa MWCO ultrafiltration membrane. Our experiments demonstrated rapid cake formation causing significant flux decline. The steady-state permeate flux for digestate was 2.4 to 4.8 L m−2 h−1, a reduction of ~90% compared to clean water flux. The specific cake resistance was ~1015 m kg−1 and the compressibility index 1.07. A series of four filtration and cleaning cycles showed 90% flux recovery following a clean water wash. Digestate filtration was then evaluate... [more]

The effects of hydrogen-enriched biogas on combustion and emissions of a dual-fuel spark-ignition engine with different hydrogen concentration ratios were studied numerically. A 1-cylinder spark ignition was used to perform a numerical simulation. To reveal the influence of the compression ratios on combustion and emissions of a gaseous engine, the crankshaft of the engine was modified to generate different compression ratios of 8.5, 9.0, 9.4, 10.0, and 10.4. The biogas contained 60 and 40% methane (CH4) and carbon dioxide (CO2), respectively, while the hydrogen fractions used to enrich biogas were 10, 20, and 30% of the mixture by volume. The ignition timing is fixed at 350 CA°. The results indicate that the in-cylinder pressure, combustion temperature, and combustion burning speed increase gradually with increasing hydrogen concentration due to the combustion characteristics of hydrogen in blends. As increasing the compression ratio, NOx emissions increase proportionally, while CO2 e... [more]

Based on the synergistic effect of ripening and hydrogen ion etching in a hydrothermal solution, a simple, facile, and low-cost new strategy was demonstrated to prepare multi-channel surface-modified amorphous Fe2O3 nanospheres as anodes for Li-ion batteries in this study. Compared with polycrystalline Fe2O3, the conversion reaction between amorphous Fe2O3 and lithium ions has a lower Gibbs free energy change and a stronger reversibility, which can contribute to an elevation in the cycle capability of the electrode. Meanwhile, there are abundant active sites and more effective dangling bonds/defects in amorphous materials, which is beneficial to promote charge transfer and lithium-ion migration kinetics. The Galvanostatic intermittent titration analysis results confirmed that the amorphous Fe2O3 electrode had a higher Li+ diffusion coefficient. In addition, the surfaces of the amorphous nanospheres are corroded to produce multiple criss-cross channels. The multi-channel surface structu... [more]

Photovoltaic (PV) systems are dependent on solar irradiation and environmental temperature to achieve their best performance. One of the challenges in the photovoltaic industry is performing maintenance as soon as a system is not working at its full generation capacity. The lack of a proper maintenance schedule affects power generation performance and can also decrease the lifetime of photovoltaic modules. Regarding the impact of environmental variables on the performance of PV systems, research has shown that soiling is the third most common reason for power loss in photovoltaic power plants, after solar irradiance and environmental temperature. This paper proposes a new statistical predictor for forecasting PV power generation by measuring environmental variables and the estimated mass particles (soiling) on the PV system. Our proposal was based on the fit of a nonlinear mixed-effects model, according to a log-logistic function. Two advantages of this approach are that it assumes a n... [more]