The future of opencast mining and energy production based on conventional resources is one of the most important issues being discussed in international forums. The whole discussion is becoming increasingly heated and takes on a special significance with the drastic increase in energy commodity prices that has occurred with the outbreak of war in Ukraine. Especially in a country like Poland, these issues are accompanied by heated discussions between miners, the government and citizens. It should be emphasised that Polish lignite mining currently produces about 35% of the cheapest electricity in Poland and also creates many jobs. The aim of this study is to assess the possibility of continuing opencast mining and its impact on rural development—both from an environmental and socio-economic point of view. The study was conducted for two municipalities in Poland where opencast lignite mining plays an important role, namely Kleszczów and Kleczew. As a result, it was found that in the case... [more]

In the present study, energy and exergy analyses of a simple supercritical, a split supercritical and a cascade supercritical CO2 cycle are conducted. The bottoming cycles are coupled with the main two-stroke diesel engine of a 6800 TEU container ship. An economic analysis is carried out to calculate the total capital cost of these installations. The functional parameters of these cycles are optimized to minimize the electricity production cost (EPC) using a genetic algorithm. Exergo-economic and exergo-environmental analyses are conducted to calculate the cost of the exergetic streams and various exergo-environmental parameters. A parametric analysis is performed for the optimum bottoming cycle to investigate the impact of ambient conditions on the energetic, exergetic, exergo-economic and exergo-environmental key performance indicators. The theoretical results of the integrated analysis showed that the installation and operation of a waste heat recovery optimized split supercritical... [more]

In recent years, there has been a dynamic development of photovoltaic materials based on perovskite structures. Solar cells based on perovskite materials are characterised by a relatively high price/performance ratio. Achieving stability at elevated temperatures has remained one of the greatest challenges in the perovskite solar cell research community. However, significant progress in this field has been made by utilising different compositional engineering routes for the fabrication of perovskite semiconductors such as triple cation-based perovskite structures. In this work, a new approach for the rapid analysis of the changes occurring in time in perovskite structures was developed. We implemented a quick and inexpensive method of estimating the ageing of perovskite structures based on an express diagnosis of light reflection in the near-infrared region. The possibility of using optical reflectance in the NIR range (900−1700 nm) to observe the ageing of perovskite structures over ti... [more]

This paper proposes a learning-based finite control set model predictive control (FCS-MPC) to improve the performance of DC-DC buck converters interfaced with constant power loads in a DC microgrid (DC-MG). An approach based on deep reinforcement learning (DRL) is presented to address one of the ongoing challenges in FCS-MPC of the converters, i.e., optimal design of the weighting coefficients appearing in the FCS-MPC objective function for each converter. A deep deterministic policy gradient method is employed to learn the optimal weighting coefficient design policy. A Markov decision method formulates the DRL problem. The DRL agent is trained for each converter in the MG, and the weighting coefficients are obtained based on reward computation with the interactions between the MG and agent. The proposed strategy is wholly distributed, wherein agents exchange data with other agents, implying a multi-agent DRL problem. The proposed control scheme offers several advantages, including pre... [more]

In the publication, the authors put forward a thesis about the low social understanding of the essence of the idea of sustainable development (SD), its assumptions, and difficulties with its implementation. This thesis became the starting point for research on contemporary problems related to the understanding and implementation of the idea of SD in Poland and an inspiration to look at Education for Sustainable Development (ESD). The aim of the study was to get to know the opinions of experts on the statutory definition of SD and social awareness of this idea, and then to relate these opinions to the state of knowledge of students, as well as their opinions and attitudes towards SD. Primary data obtained in the course of surveys among 105 Polish experts (employees of universities, research institutes, government and local government units) and 844 students from several Polish university centres were used. The obtained results indicated gaps in Education for Sustainable Development (ESD... [more]

Eco-driving algorithms optimize the speed profile to reduce the energy consumption of a vehicle. This paper presents an eco-driving algorithm for battery electric powertrains that applies a split loss integration approach to incorporate the component losses. The algorithm consistently uses loss models to overcome the drawbacks of efficiency maps, which cannot represent no-load losses at zero torque. The use of loss models is crucial since the optimal solution includes gliding, during which there are no-load losses. An analysis shows, that state-of-the-art nonlinear programming algorithms cannot represent these no-load losses at zero torque with a small modeling error. To effectively compute the powertrain losses with only a small error in comparison to the measurement data, we introduce a tailored combination of nonlinear inequality constraints that interleave two polynomial fits. This approach can properly represent reality. We parameterize the algorithm and validate the vehicle model... [more]

In the present study, the co-digestion effectiveness of the selected beverage wastes and municipal sewage sludge in two- and three-component mixtures was evaluated. Orange peels and orange pulp, as well as brewery spent grain were applied as co-substrates to sewage sludge at the following doses: 1.5 and 3.0 g of orange peels, 2.5 and 5 g of orange pulp, and 1.5 g brewery spent grain. Mono-digestion of sewage sludge was used as a control. The experiments were performed under mesophilic conditions in batch reactors. As compared to the control, only in the presence of the highest dose of pulp, brewery spent grain and sewage sludge was the increased methane production of 395 mL CH4 g−1 VS accompanying an additional energy profit of 82% observed. Moreover, in this case, the enhanced volatile solids removal and lower accumulation of p-cymene were found. These results were despite the increased limonene and phenol content in the feedstock, confirming a synergistic effect at the highest dose o... [more]

In the present work, to investigate the hydraulic losses and safe operation of nozzle check valves in industrial piping systems, the static characteristics of the valve and its dynamic behavior in the pipeline system were studied using an experimental bench with a visual DN300 nozzle check valve. Besides, basing on the PIV (Particle Image Velocimetry) technique measures the valve steady-state flow field under the different flow rates. The study has shown that as the flow rate rises, the valve disc displacement slowly increases to 44 mm, then rapidly increases to a maximum displacement of 72 mm. When the Reynolds number exceeds 5 × 105, the relationship between pressure drop and flow obeys a quadratic function. The local vortex area formed by the flow passage near the downstream deflector expands with the flow improvement. As the increase of flowrate, at low flow operating conditions, the downstream flow velocity in the local high-speed area near the valve body increases; at medium oper... [more]

High temperature superconductivity is emerging as a solution for lightweight, cost-effective and high-power wind generators. Current injection and maintainment/sustainment in the field winding are obtained by metal current leads which, due to persistent heat conduction and joule loss, are responsible for a large part of the total cryogenic heat load. Slip rings, which further reduce the overall performance and reliability of the system, are also required. In this paper we assess the viability of the HTS dynamo and the rectifier flux pumps for energizing the field coils of the EcoSwing 3.6 MW HTS wind generator. Both a “warm” solution, with the rectifier at room temperature, and a “cold” solution, in which the latter is integrated into the cryostat, are investigated with regard to the rectifier flux pump. A comparison with the actual, state-of-the-art, system of the EcoSwing machine is carried out in terms of the total required cooling power and the ability to charge the HTS field windi... [more]

A change in thinking has been ongoing in the architecture and building industry in response to growing concern over the role of the building industry in the excessive consumption of energy and its devastating effects on the natural environment. This shift changed the thinking of architects, engineers, and designers in the initial phases of a building’s design, with a change from the importance of geometry and form to assessing a building’s performance, from structure to a building’s skin, and from abstract aesthetics to bio-climatic aesthetics. In this context, sustainable, intelligent, and adaptive building façades were extensively researched and developed. Consequently, several typologies, strategies, and conceptual design frameworks for adaptive façades were developed with the aim of performing certain functions. This study focuses on the biomimetic methodologies developed to design adaptive façades because of their efficiency compared to other typologies. A comprehensive literature... [more]

Buildings account for 40% of the European Union’s energy consumption. Deep energy renovation of residential buildings is key for decarbonization and energy poverty alleviation. However, renovation is occurring at far below the needed pace and depth. In this context, building renovation one-stop shops, which bring all project phases under one roof and provide advice, support, and finance to households, are highlighted as a promising solution. Nevertheless, this model is still absent or under-developed in most European countries and remains understudied in the scientific literature. Therefore, the present research goals are as follows: (i) to provide a critical review of emerging one-stop shop models; (ii) to streamline the deployment of building renovation digital one-stop shops by piloting a sequential multi-staged approach for Portuguese households and proposing it for replication elsewhere; and (iii) to compare case-study insights with other one-stop shops and discuss the notion in t... [more]

The article is a continuation of the authors’ ongoing research related to power flow and voltage control in LV grids. It outlines how the Distribution System Operator (DSO) can use Machine Learning (ML) technology in a future grid. Based on supervised learning, a Selectively Coherent Model of Converter System Control for an LV grid (SCM_CSC) is proposed. This represents a fresh, new approach to combining off and on-line computing for DSOs, in line with the decarbonisation process. The main kernel of the model is a neural network developed from the initial prediction results generated by regression analysis. For selected PV system operation scenarios, the LV grid of the future dynamically controls the power flow using AC/DC converter circuits for Battery Energy Storage Systems (BESS). The objective function is to maintain the required voltage conditions for high PV generation in an LV grid line area and to minimise power flows to the MV grid. Based on the training and validation data pr... [more]

The world of electrical distribution is rapidly changing and is seeing more and more distributed production and steerable flexibilities. Energy communities are seen as an important innovation for the optimization of electrical consumption at a local level. A central need of the local energy markets inside energy communities is the exchange and circulation of production and consumption data, and therefore the problem of the potential leak of sensitive data must be addressed. In this paper, the context of the Lugaggia Innovation Community, a Self Consumption Community pilot project in southern Switzerland, is introduced together with the blockchain framework that was created for its internal market interaction and the rules designed for its local energy market. A cryptographic protocol from the literature, based on homomorphic encryption, is then proposed for the anonymous aggregation of production and consumption data of the individual households at a resolution of 15 min. The computati... [more]

Anaerobic digestion (AD), microalgae cultivation, and microbial fuel cells (MFCs) are the major biological processes to convert organic solid wastes and wastewater in the agricultural industry into biofuels, biopower, various biochemical and fertilizer products, and meanwhile, recycle water. Various nanomaterials including nano zero valent irons (nZVIs), metal oxide nanoparticles (NPs), carbon-based and multicompound nanomaterials have been studied to improve the economics and environmental sustainability of those biological processes by increasing their conversion efficiency and the quality of products, and minimizing the negative impacts of hazardous materials in the wastes. This review article presented the structures, functionalities and applications of various nanomaterials that have been studied to improve the performance of AD, microalgae cultivation, and MFCs for recycling and valorizing agricultural solid wastes and wastewater. The review also discussed the methods that have b... [more]

The parametric variation of nonlinear systems remains a significant drawback of automatic system controllers. The Proportional−Integral(PI) and Proportional−Integral−Derivative (PID) are the most commonly used controllers in industrial control systems. However, with the evolution of these systems, such controllers have become insufficient to compete with the complexity of the systems. This problem can be solved with the help of artificial intelligence, and especially with the use of optimization algorithms, which allow for variable gains in PID controllers that adapt to parametric variation. This article presents an analytical and experimental study of the Direct Torque Control (DTC) of a Doubly-Fed Induction Motor (DFIM). The speed adaptation of the DFIM is achieved using a PID controller, which is characterized by overshoots in the speed and ripples in the electromagnetic torque. The Genetic Algorithm (GA) within the DTC shows very good robustness in speed and torque by reducing torq... [more]

Thermal power plants, TPP, are one of the main players in the phosphoric acid and fertilizer production value chain. The control of power plant assets involves considerable complexity and is subject to several constraints, affecting the asset’s reliability and, most importantly, plant operators’ safety. The main focus of this paper is to investigate the potential of an agent-based digital twin architecture for collaborative prognostic of power plants. Based on the ISO 13374:2015 scheme for smart condition monitoring, the proposed architecture consists of a collaborative prognostics system governed by several smart DT agents connected to both physical and virtual environments. In order to apprehend the potential of the developed agent-based architecture, experiments on the architecture are conducted in a real industrial environment. We show throughout the paper that our proposed architecture is robust and reproduces TPP static and dynamic behavior and can contribute to the smart monitor... [more]

The karst landscape is widespread in the southern region of China. As a result of underground mining activities, the original stress equilibrium is disrupted, causing the redistribution of stress in the overlying rock layer, inducing the longitudinal fracture of mining to expand and penetrate upwards, resulting in the rupture and destabilization of the karst cave roof, thus triggering a series of engineering problems such as karst cave collapse, landslide, the discontinuous deformation of the ground surface, and soil erosion. In order to study the evolutionary characteristics of buried rock fissures in shallow coal seam mining under the karst landform, taking the shallow coal seam with the typical karst cave development landform in Guizhou as the engineering background, based on the similarity simulation experiment and fractal theory, the evolution law of buried rock fissures and network fractal characteristics under the disturbance of the karst landform mining are analyzed. The resear... [more]

The growing popularity of renewable energy and hydrogen-powered vehicles (HVs) will facilitate the coordinated optimization of energy and transportation systems for economic and environmental benefits. However, little research attention has been paid to dynamic hydrogen pricing and its impact on the optimal performance of energy and transportation systems. To reduce the dependency on centralized controllers and protect information privacy, a time-decoupling layered optimization strategy is put forward to realize the low-carbon and economic operation of energy and transportation systems under dynamic hydrogen pricing. First, a dynamic hydrogen pricing mechanism was formulated on the basis of the share of renewable power in the energy supply and introduced into the optimization of distributed energy stations (DESs), which will promote hydrogen production using renewable power and minimize the DES construction and operation cost. On the basis of the dynamic hydrogen price optimized by DES... [more]

Given the difficulty of early warning of coal spontaneous combustion caused by continuous abnormal exceedance of CO in the tailgate corner of a low metamorphic coal seam and taking the 1305-working face of the Dananhu No.1 coal mine in Hami, Xinjiang as an example, this paper studies the abnormal CO-exceedance phenomenon based on field measurements, experimental research, and numerical simulation. The research shows that the abnormal CO-exceedance phenomenon is not caused by spontaneous combustion oxidation but by ambient-temperature oxidation of coal in the goaf. Factors, such as higher amounts of residual coal and higher degrees of fragmentation of the goaf, provide opportunities for the ambient-temperature oxidation of residual coal in the 1305 goaf. The 1305 coal oxidation characteristics at ambient temperature are examined, and the abnormal CO-exceedance mechanism is analyzed in depth. A CO-early-warning-limit model in the tailgate corner for coal spontaneous combustion in the 130... [more]

In this article, we present the possibility of applying the concept of elasticity in the system of sustainable energy development through the use of wood biomass. We used a dual (socio-ecological and economic) approach to sustainable energy development. The research was carried out using the methods of reduction reasoning, scientific observation, and examination of source documents. We identified crisis threats in the context of sustainable energy development. Then, we analyzed the supply of wood biomass in Poland, taking into account its geographical location. As a result, we identified and characterized the causal relationships between the assumptions of the concept of resistance and the sustainable development of energy with the use of wood biomass. We found that the concepts of resilience can be adapted to assessing energy sustainability. This adaptation is based on resilience, flexibility, and strategic ability to revitalize the country. We found that five key threats (extreme wea... [more]

Duqm is located in the Al Wasta Governorate in Oman and is currently fed by 10 diesel generators with a total capacity of around 76 MW and other rental power sources with a size of 18 MW. To make the electric power supply come completely from renewables, one novel solution is to replace the diesel with hydrogen. The extra energy coming from the PV-wind system can be utilized to produce green hydrogen that will be utilized by the fuel cell. Measured data of solar insolation, hourly wind speeds, and hourly load consumption are used in the proposed system. Finding an ideal configuration that can match the load demand and be suitable from an economic and environmental point of view was the main objective of this research. The Hybrid Optimization Model for Multiple Energy Resources (HOMER Pro) microgrid software was used to evaluate the technical and financial performance. The findings demonstrated that the suggested hybrid system (PV-wind-fuel cell) will remove CO2 emissions at a cost of e... [more]

According to various estimates, street lighting in Poland consumes between 1.500 and 2.500 GWh per year and is responsible for some greenhouse gas emissions from electricity generation. Also on the basis of estimates, it is estimated that approximately 3.3 million road and street luminaires are used in Poland. The increase in electricity costs, on the one hand, and the technical possibilities in the field of lighting, on the other, force the search for new solutions aimed at saving during the operation of electrical devices and installations, including road lighting installations. One of the methods of saving electricity is to replace the luminaires with energy-saving ones with LED sources, but also with new sodium and metal halide sources. The latter solution is cheaper and allows us to keep existing poles, electrical installation and luminaire heads if their technical parameters have not been degraded. The new and already used luminaires with discharge sources can be used in road lig... [more]

Polyphenols that are abundant in various organic wastes can inhibit anaerobic degradation of these wastes. This study investigated the effect of the concentration of individual phenolic acids (p-OH benzoic, vanillic, ferulic, sinapic, syringic, and p-coumaric acids) and their mixture on the methane potential of distillery stillage. An increase in phenolic acid concentration adversely affected biogas production and composition, as well as the methane-production rate. The inhibition constants for methane production were 0.5−1.0 g/L of individual phenolic acids and 1.5 g/L of the mixture of these acids. At lower concentrations, the phenolic acids were utilized as a carbon source, but the process was impeded when their concentrations exceeded the threshold value, due to their negative effect on microbial growth. When distillery stillage was spiked with vanillic acid, two-phase methane production was observed. Spiking distillery stillage with vanillic, p-coumaric, syringic, or ferulic acids... [more]

This article reviews the different topologies compatible with V2G feature and control approaches of integrated onboard charger (iOBC) systems for battery electric vehicles (BEVs). The integrated topologies are presented, analyzed, and compared in terms of component count, switching frequency, total harmonic distortion (THD), charging and traction efficiencies, controllability, reliability and multifunctionality. This paper also analyzes different control approaches for charging and traction modes. Moreover, the performance indices such as setting time, rise time, overshoot, etc., are summarized for charging and traction operations. Additionally, the feasibility of a Level 3 charging (AC fast charging with 400 Vac) of up to 44 kW iOBC is discussed in terms of converter efficiencies with different switching frequencies and switch technologies such as SiC and GaN. Finally, this paper explores the power density trends of different commercial integrated charging systems. The power density t... [more]

The electricity load forecasting plays a pivotal role in the operation of power utility companies precise forecasting and is crucial to mitigate the challenges of supply and demand in the smart grid. More recently, the hybrid models combining signal decomposition and artificial neural networks have received popularity due to their applicability to reduce the difficulty of prediction. However, the commonly used decomposition algorithms and recurrent neural network-based models still confront some dilemmas such as boundary effects, time consumption, etc. Therefore, a hybrid prediction model combining variational mode decomposition (VMD), a temporal convolutional network (TCN), and an error correction strategy is proposed. To address the difficulty in determining the decomposition number and penalty factor for VMD decomposition, the idea of weighted permutation entropy is introduced. The decomposition hyperparameters are optimized by using a comprehensive indicator that takes account of t... [more]