Energy Resources Research Articles

Research on coupling coordination and spatial-temporal evolution of hydrogen energy industry in hebei province based on R-P-D chain

In order to promote the sustainable development of the hydrogen energy industry in Hebei Province, this paper investigates the coordinated industrial coupling and spatio-temporal evolution of the "resource conditions-project layout-user demand (R-P-D)" chain within the hydrogen energy industry in Hebei Province. First, a fitness model for the hydrogen energy industry is formulated based on the "(R-P-D)" chain perspective, and a comprehensive evaluation is performed using the AHP entropy weighting method.Subsequently, coupling coordination model of resource condition-project layout (R–P), resource condition-user demand (R-D), project layout-user demand (P-D), and R-P-D chain are constructed. The coupling coordination degree data of the system are then linked with the spatial unit for spatiotemporal evolution and analysis using ArcGIS software. The findings indicate that cities with high levels of economic development, advanced industrialization, abundant renewable energy resources, and well-developed clean energy industries tend to exhibit more harmonious development in the hydrogen energy industry.

Production of cellulose nano/microfibers through simultaneous milling and enzymatic hydrolysis with an optimized cocktail of cellulase/xylanase/LPMO

Cellulose nanofibers (CNF) and microfibrillated cellulose (MFC) are biodegradable micro and nanomaterials derived from plant cellulose. The properties of CNF, influenced by fibril length, impact the strength of cellulose-based nanomaterials. This study uses enzymatic milling to explore pretreatments, enzymatic optimization, and CNF/MFC production. The study found that hammer milling and lamination are effective pretreatments for preserving fibers. The optimal enzymatic mixture contained 75 % cellulase and 25 % xylanase, yielding 68.7 % and 2.86 %/h productivity, respectively. The addition of the LPMO enzyme increased the yield by 10–13 %, depending on its concentration. Enzymatic milling was introduced as an innovative approach to CNF production, reducing hydrolysis time and creating milder processing conditions. The combined process of ball milling and enzymatic hydrolysis on pre-ground pulp in the hammer mill achieved a maximum CNF yield of 45.83 % and productivity of 13.10 %/h. X-ray diffraction showed that the lamination-pre-treated pulp had a high crystallinity index of 84.34 %. Scanning electron microscopy revealed fibers with diameters ranging from 52 nm to 296 nm. These findings support the search for sustainable and eco-friendly alternatives to non-renewable resources, enabling sustainable CNF production at room temperature with reduced processing time.

Assessment of site suitability for centralized photovoltaic power stations in Northwest China's six provinces

Northwest China has abundant solar energy resources and extensive land, making it a pivotal site for solar energy development. However, restrictions on site selection and severe weather conditions have hindered the establishment and operation of photovoltaic (PV) power stations. Previous studies have not considered meteorological factors when evaluating site suitability, leading to research gaps in identifying suitable areas and establishing indicator systems. We aimed to address these gaps by considering seven factors constraining the construction of centralized PV power stations (CPPS) and developing an indicator system based on terrain, climate, soil, and economic factors. Furthermore, we conducted analyses to quantify the solar energy generation potential (SEGP), carbon emissions reduction benefits, and land utilization potential at different sites. The findings indicate that areas rated as very suitable and extremely suitable comprised the largest proportion (62.35%) of site suitability. The correlation between site suitability and electricity consumption was largely non-significant, highlighting the need for enhanced coordination. Additionally, we forecast the electricity consumption in Xinjiang, Gansu, Inner Mongolia, Qinghai, Ningxia, and Shaanxi for 2030 to be 56.62, 19.86, 54.54, 13.59, 15.96, and 33.34 ( × 1011 kWh), respectively, with corresponding carbon emissions reduction potentials of 20.2, 7.1, 19.4, 4.8, 5.7, and 11.9 ( × 109 kg). Consequently, PV carbon reduction and land utilization potential are substantial.

Wind speed multi-step prediction based on the comparison of wind characteristics and error correction: Focusing on periodic thermally-developed winds

To leverage the abundant wind energy resources available in mountainous regions, an increasing number of wind power facilities and associated transportation infrastructure are being constructed in these areas. There are different types of intense winds in mountainous areas and the non-linear characteristics of the different intense winds vary significantly. The periodic thermally-developed winds are the commonly occurring type of intense wind. Based on the comparison of wind characteristics, this research proposes a prediction model for the periodic thermally-developed winds. The research utilizes the Bi-directional Long Short-Term Memory model(Bi-LSTM), which has been optimized by the Bayesian optimization(BO), to predict wind speed. Based on the relationship between wind field characteristics in periodic thermally-developed winds, a regression correction module is proposed using a joint probability model. Additionally, to address the volatility and uncertainty of wind speed, a Gaussian mixture model is employed for probability prediction. The experimental results demonstrate several findings: 1. The BO-Bi-LSTM model accurately and reliably predicts multi-step results for periodic thermally-developed winds in mountainous areas. 2. The proposed correction module, when combined with other models, yields improved wind speed accuracy compared to the uncorrected values. 3. The Gaussian mixture model produces probabilistic prediction results that consider both interval coverage and interval bandwidth simultaneously. 4. The proposed model can successfully predict periodic thermally-developed winds in mountainous areas for practical engineering purposes, resulting in reliable probabilistic prediction outcomes. It is of great significance for the utilization of wind energy resources and the driving safety of vehicles on ancillary structures.

A visual knowledge map analysis of coal mine intensity based on CiteSpace software and web of science core database

ABSTRACT The research on coal mining intensity provides a basis for rational coal resource extraction and mine ecological environment source protection. This study uses the 815 publications and based on CiteSpace’s visualisation software, takes the authors, institutions, and keywords as the nodes, and constructs the related knowledge graph through keyword co-occurrence and other methods. China ranks first in the world in this field; the current research mainly focuses on coal and gas protrusion, carbon dioxide emission, etc.; future research on coal mining intensity should focus on high-intensity mining, factors affecting coal mining intensity, and mining disturbance.

Framework design of distributed P2P2G energy transaction considering photovoltaic power and dispatch of manufacturing facilities

In this paper, a distributed peer-to-peer-to-grid (P2P2G) energy transaction framework considering photovoltaic generation and dispatch of manufacturing facilities is designed to increase the penetration of renewable energy resource. The factory with typical manufacturing assembly production task, photovoltaic panels and battery is regarded as a micro-grid (MG) to participate in the energy transaction market. The designed framework contains two levels. In the upper level, each MG determines the scheduling of manufacturing facilities and battery and the quantities of P2P2G energy transactions based on the given P2P energy transaction price and distribution locational marginal price (DLMP), in which the complex typical manufacturing assembly process is formulated as a kind of deferable load and the DLMP is updated according to the optimal power flow (OPF) of the network. In the lower level, peer-to-peer (P2P) energy transaction prices are updated by non-cooperative games and the homologous Rosen-Nash equilibrium points are obtained by using Nikaido-Isoda relaxation and alternating direction method of multipliers (ADMM) algorithm. The efficacy of the designed framework is demonstrated by a case study, and the results indicate the designed framework can improve the utilisation rate of renewable energy.

Distributed MPC-Based Voltage Control for Active Distribution Networks Considering Uncertainty of Distributed Energy Resources

Distributed MPC-Based Voltage Control for Active Distribution Networks Considering Uncertainty of Distributed Energy Resources

ZIF-67-derived Co-N-C supported nickel cobalt sulfide as a bifunctional electrocatalyst for sustainable hydrogen production via alkaline electrolysis.

As non-renewable resources are finite and cannot be utilized indefinitely, hydrogen (H2) has emerged as a promising alternative for clean and sustainable energy. The cost-effective hydrogen production to meet large-scale commercial demand poses a significant challenge. Water electrolysis, powered by electricity derived from renewable resources, stands out as a viable route towards sustainable hydrogen production, with electrocatalysis playing a pivotal role in this process. Notably, materials derived from metal-organic frameworks (MOFs) exhibit excellent physicochemical properties, making them promising candidates for electrocatalysis. In this study, we synthesized zeolitic imidazolate framework-67 (ZIF-67) and its derived Co-N-doped carbon (Co-N-C) supported NiCo2S4 on nickel foam (NF), namely NF@ZIF-67@NiCo2S4 and NF@Co-N-C@NiCo2S4, using a hydrothermal method. The electrocatalytic activity of these synthesized materials for both oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) was systematically evaluated using various electrochemical techniques. The NF@ZIF-67@NiCo2S4 material demonstrates overpotentials of 248 and 359 mV for OER and HER at the current density of 50 mA cm-2, whereas, NF@Co-N-C@NiCo2S4 exhibits overpotentials of 239 and 351 mV, respectively. Furthermore, the catalysts exhibit excellent stability in both OER and HER even under high applied potentials. Moreover, to assess their catalytic performance in a full-cell configuration, two alkaline electrolyzer cells were assembled: NF@ZIF-67@NiCo2S4(+)∥NF@ZIF-67@NiCo2S4(-) and NF@Co-N-C@NiCo2S4(+)∥NF@Co-N-C@NiCo2S4(-). These two electrolyzers demonstrated cell potentials of 1.62 V and 1.59 V at 10 mA cm-2, respectively, showcasing their efficacy in overall water-splitting.

Modeling Smart electrical microgrid with demand response and storage systems for optimal operation in critical conditions

This study examines the issue in standard and operational scenarios of microgrids that arise during critical conditions. Initially, the ideal energy storage size and discharge depth are identified for optimal microgrid planning under operating conditions. Subsequently, by utilizing the energy storage system and load response, the microgrid's vulnerability is reduced and the cost of load shedding is minimized when in critical conditions, leading to the microgrid being disconnected from the main network and operating in island mode. This model aims to analyze how the system performance is influenced by the presence of storage systems and load response programs in a numerical scenario, particularly during severe weather events. In addition, the study examines the role of advanced control algorithms and communication systems in optimizing the operation of the microgrid. By implementing smart grid technologies, the microgrid can better manage its energy resources, anticipate fluctuations in demand, and respond quickly to changing conditions. This proactive approach helps to ensure the stability and reliability of the microgrid, even in the face of unforeseen challenges. Overall, this research contributes valuable insights into the challenges and opportunities facing microgrids in both normal and emergency situations. By identifying the most effective energy storage solutions, load response strategies, renewable energy integration methods, and advanced control systems, the study aims to enhance the resilience, efficiency, and sustainability of microgrid systems in the future. The results of the proposed approach in critical operational mode represent the optimal condition of the electrical microgrid with minimum cost and load shedding considering storage systems and load response programs.

A Lab-Scale Experiment on the Spontaneous Combustion Behavior of Chronic Naturally–Oxidized Coal in Re-Mining Coal Mine

ABSTRACT Spontaneous combustion of coal in re-mining coal mine is a serious threat to the safety recovery of coal resources. In this paper, six coal samples, including two raw bituminous coal samples from the new mining working face and four oxidized bituminous coal samples from the re-mining working face, are selected. The pore structures, thermogravimetric properties, and spontaneous combustion characteristics of raw coal and oxidized coal are studied. The pore structures show that the surface of oxidized coals has more cracks and higher macropore volume and porosity as compared with raw coal. The thermogravimetric experiments demonstrate that the oxidized coal has a higher combustion rate and turns to the combustion reaction zone in advance. Moreover, the oxidized coals perform a better combustion property by showing a comprehensive combustion index of 6.7 × 10−9 min−2·°C−3 and 8.9 × 10−9 min−2·°C−3, higher than the raw coal of 4.0 × 10−9 min−2·°C−3. The spontaneous combustion characteristics show that the oxidized coal performs a greater rate of oxygen consumption and more oxidation products released than raw coal. The CPT of raw coal is higher than 157°C, while the CPT of oxidized coal is between 132°C and 140°C. The research results can provide a risk assessment method for coal spontaneous combustion in the re-mining coal mine, and provide guidance for avoiding the occurrence of coal fires.

OPLEM: Open Platform for Local Energy Markets

Local Energy Markets (LEMs) have been proposed as an effective solution to coordinate distributed energy resources within emerging smart local energy systems. However, LEMs are still at an early stage of development and are not widely implemented yet. Extensible open-source software tools are needed to simulate different market designs and evaluate their feasibility and effectiveness. This paper presents OPLEM, an open-source Python package for modelling and testing LEM designs. It offers a modular and flexible framework to create and test market designs adapted for distribution networks. OPLEM integrates two distinct models—one for designing and simulating local energy markets, and another for network operation. Unlike existing tools, OPLEM platform offers a comprehensive solution that bridges the gap between market design and network operation assessment, enabling stakeholders to gain deeper insights into the interactions between market dynamics and grid performance. Additionally, the inclusion of participant and asset models further enhances the tool’s versatility, allowing for a holistic analysis. Thanks to its modular structure, OPLEM allows the development of customised LEM designs and initially incorporates four popular LEM designs: Time-of-Use pricing market, centralised dispatch with distribution locational marginal pricing, bilateral peer-to-peer market and auction market. By combining market design and network modelling functionalities, the tool empowers users to explore various scenarios and optimise market clearings to enhance both economic efficiency and grid reliability.

Research on ecological restoration and its impact on society in coal resource-based areas: Lessons from the Ruhr area in Germany and the Liulin area in China

The coal resource-based areas rely on coal resources and primary processing as their pillar industries, such as the old industrial areas in China and Germany. Long-term, large-scale coal mining has significantly damaged the ecological environment of mining areas. Environmental restoration refers to repairing, rehabilitating, or revitalizing ecosystems that have been degraded, damaged, or destroyed by human activities or natural disasters. In fact, ecological restoration is not just an environmental issue and it is a societal problem. Ecological restoration is closely linked to natural resources, the environment, the economy, society, and politics. These factors form a social ecological system and it is the basis for local stability and sustainable development in the coal resource-based areas. In this process, the relationship between government, enterprise, and local people is constantly being reshaped and defined, then it causes changes in the local social ecology and political ecology. The paper researches the Ruhr area in Germany and the Liulin County in China, the former is a world-famous old industrial and the latter is a typical coal mining subsidence district. By analyzing and comparing the ecological restoration and significant social changes in the Ruhr area and the Liulin County at different periods, the findings show the unique ecology— social system of the coal resource-based area, then enhances the effective measures for ecological restoration and sustainable development of the coal resource-based areas.

TRNSYS Simulation of a Bi-Functional Solar-Thermal-Energy-Storage-Assisted Heat Pump System

The escalating energy demands in buildings, particularly for heating and cooling demands met by heat pumps, have placed a growing stress on energy resources. The bi-functional thermal diode tank (BTDT) is proposed as thermal energy storage to improve the heating and cooling performances of heat pumps in both summer and winter. The BTDT is an insulated water tank with a gravity heat pipe (GHP), which can harvest and store heat passively from sun radiation and the external environment during the daytime. In summer, it harvests and stores cold energy from the air and night sky during the daytime. The performance of the BTDT-assisted heat pump (BTDT-HP) system in Adelaide, Australia, during the 2021–2022 summer and winter seasons was evaluated by conducting a TRNSYS simulation. This study revealed that the BTDT-HP system outperformed the reference ASHP system, where up to 8% energy in heating and 39.75% energy in cooling could be saved. An overall reduction in the energy consumption of 18.89% was achieved. Increasing the BTDT volume and GHP panel area enabled the tank to store more thermal and cold energy across the winter and summer seasons, thereby improving the system’s performance. The maximum ESPs were found to be 31.6% and 41.2% for heating and cooling for the study case under optimal conditions. When the GHP panel area was fixed at 15 m2, the BTDT volume should be at least 28 m3 for the BTDT-HP system, boasting cooling and heating capacities of 40 kW and 43.2 kW, to achieve positive energy savings.

Capitalizing on natural resources rent and renewable energy in enhancing economic growth—New evidence with MMQR method

AbstractNatural resources are vital resources given by nature and are responsible for promoting a nation's economic development. However, with the existence of two opposing theories, it is essential to provide state‐of‐the‐art research that ascertains the association between natural resources and economic growth. The Rostow hypothesis presents the importance of natural resources in promoting economic growth, while the resources curse hypothesis alludes that natural resources, in the developing countries, reduce economic growth. The present research uses the contemporary Methods of Moments Quantile Regression method to explore on this relationship in the fifteen natural resources‐rich African countries. The data used are annual data for the period 1990 to 2021. The major results presented in this research show that natural resources rent significantly promotes economic growth in this region, supporting the postulations of Rostow's hypothesis. Renewable energy is also observed to play a significant role in raising economic growth of this region. However, labor force participation rate is determined to reduce economic growth and this can be explained by high levels of unemployment in this region. Capital provides a positive but insignificant effect on economic growth of the natural resources‐rich African countries. The study results also show that economic growth, capital, trade openness, and labor force enhance natural resources rent. The study calls for the improvement in the use of renewable energy and natural resources in order to attain sustainable economic development in this region.

An artificial gorilla troops optimizer for stochastic unit commitment problem solution incorporating solar, wind, and load uncertainties.

The unit commitment (UC) optimization issue is a vital issue in the operation and management of power systems. In recent years, the significant inroads of renewable energy (RE) resources, especially wind power and solar energy generation systems, into power systems have led to a huge increment in levels of uncertainty in power systems. Consequently, solution the UC is being more complicated. In this work, the UC problem solution is addressed using the Artificial Gorilla Troops Optimizer (GTO) for three cases including solving the UC at deterministic state, solving the UC under uncertainties of system and sources with and without RE sources. The uncertainty modelling of the load and RE sources (wind power and solar energy) are made through representing each uncertain variable with a suitable probability density function (PDF) and then the Monte Carlo Simulation (MCS) method is employed to generate a large number of scenarios then a scenario reduction technique known as backward reduction algorithm (BRA) is applied to establish a meaningful overall interpretation of the results. The results show that the overall cost per day is reduced from 0.2181% to 3.7528% at the deterministic state. In addition to that the overall cost reduction per day is 19.23% with integration of the RE resources. According to the results analysis, the main findings from this work are that the GTO is a powerful optimizer in addressing the deterministic UC problem with better cost and faster convergence curve and that RE resources help greatly in running cost saving. Also uncertainty consideration makes the system more reliable and realistic.

Packed Bed Thermal Energy Storage System: Parametric Study

The use of thermal energy storage (TES) contributes to the ongoing process of integrating various types of energy resources in order to achieve cleaner, more flexible, and more sustainable energy use. Numerical modelling of hot storage packed bed storage systems has been conducted in this paper in order to investigate the optimum design of the hot storage system. In this paper, the effect of varying design parameters, including the diameter of the packed bed, the storage material, the void fraction, and the aspect ratio of the packed bed, on storage performance was investigated. COMSOL Multiphysics 5.6 software has been used to design, simulate, and validate an axisymmetric model, which was then applied to evaluate the performance of the storage system based on the total energy stored, the heat transfer efficiency, and the capacity factor. In this paper, a novel-packed bed was proposed based on the parametric analysis. This involved a 0.2 void fraction, 4 mm porous media particle diameter, and Magnesia as the optimum storage material with air as the heat transfer fluid.

Augmented Two-Stage Hierarchical Controller for Distributed Power Generation System Powered by Renewable Energy: Development and Performance Analysis

The sustainable development of an area is highly reliant on a reliable electrical energy supply. Microgrids are important in integrating distributed energy resources (DERs) using power electronic converters. However, microgrid control becomes challenging with the increasing number of distributed generators and loads. With the conventional droop control method, power contributions from DER converters cannot be accurately shared due to a mismatch of line impedances. In this paper, an augmented hierarchical control mechanism is proposed to solve the issues mentioned above. This hierarchical control mechanism consists of primary and secondary controllers. The primary stage utilized the droop controller to improve optimal power flow, mainly for the resistive network. The secondary stage is based on an improved methodology to compensate for the voltage and frequency variations during small and large signal disturbances. Moreover, the modelling and analysis for PMSG-based wind energy conversion systems are also presented. The response of the primary controller for active and reactive power sharing is investigated. The analysis emphasizes the demonstration of optimal power-sharing under normal and abnormal conditions for the considered load. Finally, the suggested robust controller’s performance is evaluated in a MATLAB environment, and simulation results show the proposed scheme’s superiority under different operating conditions. The frequency is stable at 50 Hz after a 50 KW load is added.

Characterization of Fuel Pellets Made From Rice Husk, Sawdust and Corncob Bond with Cissus Populnea and Manihot Esculenta

There is growing interest in the production of biofuels from biomass wastes. The availability of biomass waste poses the need for technical assessment of pelletisation of biomass waste at industrial production level. The misuse of environmentally friendly and sustainable energy resources and lack of compressed biomass energy products that could enhance fuel quality needs to be addressed. This study intends to determine the energy output from tenary combination of the biomass fuel pellets consisting of rice husks, African birch sawdust, corncobs and their varying mixtures bond with aqueous extract of C. populnea (Cp) and M. esculenta (Me). The combustion characteristics of pellets produced from Rice Husk, African Birch Sawdust, Corncob and their blends (M, M1, M2, M3 and M4) were conducted by the development of an analytical protocol. Pellet admixtures were prepared at each binder ratio of 10% of bulk weight of RH, ABS, corncob and their various blends in the ratios 1:1:1 (M), 1:2:3 (M1), 2:1:3 (M2), 3:1:2 (M3) and 2:3:1 (M4), respectively. The Bulk Density (BD), Ash Contents (AC), Heat Release Rate (HRR) and Calorific Value (CV) of the pellets were measured using established procedures. The result revealed that combustion characteristics of fuel pellets made from Corncob and Blend ratio of 1:2:3 bound with Manihot esculenta gel were enhanced and the fuel pellets possessed sufficient calorific values suitable for energy applications. It was recommended that massive production of fuel pellets from biomass wastes for small and medium scale energy systems could give a positive development to agrarian and rural areas in Nigeria where there is a lot of these resources and lack of stable electrical supply.

Towards Sustainable Energy Communities: Integrating Time-of-Use Pricing and Techno-Economic Analysis for Optimal Design—A Case Study of Valongo, Portugal

This paper presents a comprehensive analysis of optimal energy community design, leveraging time-of-use pricing mechanisms and techno-economic parameters. Focusing on a case study of Valongo, Portugal, this study explores the intricate interplay between energy infrastructure planning, economic considerations, and pricing dynamics. Through a systematic approach, various factors, such as renewable energy integration, demand–response strategies, and investment costs, are evaluated to formulate an efficient and sustainable energy community model. Time-of-use pricing schemes are incorporated to reflect the dynamic nature of energy markets and consumer behavior. By integrating techno-economic analyses, this study aims to optimize energy resource allocation while ensuring cost-effectiveness and environmental sustainability. The influence of optimized sizes of photovoltaics (PV), battery storage, and electrical vehicles (EVs) on self-sufficiency rates, self-consumption rates and CO2 savings is analyzed. The findings offer valuable insights into the design and implementation of energy communities in urban settings, highlighting the importance of adaptive strategies in the transition towards a resilient and low-carbon energy future. The novelty of this paper lies in its comprehensive approach to energy community design, which integrates time-of-use pricing mechanisms with techno-economic parameters. By focusing on the specific case of Valongo, Portugal, it addresses the unique challenges and opportunities present in urban settings. Additionally, the analysis considers the interaction between renewable energy production, demand profiles and investment costs, providing valuable insights for optimizing resource allocation and achieving both cost-effectiveness and environmental sustainability.

Annual Review of Environment and Resources, Volume 48

The Annual Review of Environment and Resources, in publication since 1976, provides authoritative reviews of significant topics within environmental science and engineering, including ecology and conservation science, water and energy resources, atmosphere, oceans, climate change, agriculture and living resources, and human dimensions of resource use and global change. There are 30 articles.