Search Results (236)

The decarbonization of electricity generation by 2030 and the realization of a net-zero economy by 2050 are central to the United States’ climate strategy. However, large-scale renewable integration introduces operational challenges, including extreme ramping, unsafe dispatch, and price volatility. This review investigates how demand–response (DR) aggregators and distributed loads can support these climate goals while addressing critical operational challenges. We hypothesize that current DR aggregator frameworks fall short in the areas of distributed load operational flexibility, scalability with the number of distributed loads (prosumers), prosumer privacy preservation, DR aggregator and prosumer competition, and uncertainty management, limiting their potential to enable large-scale prosumer participation. Using a systematic review methodology, we evaluate existing DR aggregator and prosumer frameworks through the proposed FCUPS criteria—flexibility, competition, uncertainty quantification, privacy, and scalability. The main results highlight significant gaps in current frameworks: limited support for decentralized operations; inadequate privacy protections for prosumers; and insufficient capabilities for managing competition, uncertainty, and flexibility at scale. We conclude by identifying open research directions, including the need for game-theoretic and machine learning approaches that ensure privacy, scalability, and robust market participation. Addressing these gaps is essential to shape future research agendas and to enable DR aggregators to contribute meaningfully to US climate targets. Full article

As global electricity demand increases and concerns over fossil fuel usage intensify, renewable energy sources have gained significant attention. Solar energy stands out due to its low installation costs and suitability for deployment. However, solar power generation remains difficult to predict because of its dependence on weather conditions and decentralized infrastructure. To address this challenge, this study proposes a flexible hybrid ensemble (FHE) framework that dynamically selects the most appropriate base model based on prediction error patterns. Unlike traditional ensemble methods that aggregate all base model outputs, the FHE employs a meta-model to leverage the strengths of individual models while mitigating their weaknesses. The FHE is evaluated using data from four solar power plants and is benchmarked against several state-of-the-art models and conventional hybrid ensemble techniques. Experimental results demonstrate that the FHE framework achieves superior predictive performance, improving the Mean Absolute Percentage Error by 30% compared to the SVR model. Moreover, the FHE model maintains high accuracy across diverse weather conditions and eliminates the need for preliminary validation of base and ensemble models, streamlining the deployment process. These findings highlight the FHE framework’s potential as a robust and scalable solution for forecasting in small-scale distributed solar power systems. Full article

With a potentially increasing share of the electricity grid relying on wind to provide generating capacity and energy, there is an expanding global need for historically accurate, spatiotemporally continuous, high-resolution wind data. Conventional downscaling methods for generating these data based on numerical weather prediction have a high computational burden and require extensive tuning for historical accuracy. In this work, we present a novel deep learning-based spatiotemporal downscaling method using generative adversarial networks (GANs) for generating historically accurate high-resolution wind resource data from the European Centre for Medium-Range Weather Forecasting Reanalysis version 5 data (ERA5). In contrast to previous approaches, which used coarsened high-resolution data as low-resolution training data, we use true low-resolution simulation outputs. We show that by training a GAN model with ERA5 as the low-resolution input and Wind Integration National Dataset Toolkit (WTK) data as the high-resolution target, we achieved results comparable in historical accuracy and spatiotemporal variability to conventional dynamical downscaling. This GAN-based downscaling method additionally reduces computational costs over dynamical downscaling by two orders of magnitude. We applied this approach to downscale 30 km, hourly ERA5 data to 2 km, 5 min wind data for January 2000 through December 2023 at multiple hub heights over Ukraine, Moldova, and part of Romania. With WTK coverage limited to North America from 2007–2013, this is a significant spatiotemporal generalization. The geographic extent centered on Ukraine was motivated by stakeholders and energy-planning needs to rebuild the Ukrainian power grid in a decentralized manner. This 24-year data record is the first member of the super-resolution for renewable energy resource data with wind from the reanalysis data dataset (Sup3rWind). Full article

In the context of global climate governance and the low-carbon energy transition, virtual power plant (VPP), a key technology for integrating distributed energy resources, is urgently needed to solve the problem of decentralization and lack of synergy in electricity, carbon, and green certificate trading. Existing studies mostly focus on single energy or carbon trading scenarios and lack a multi-market coupling mechanism supported by blockchain technology, resulting in low transaction transparency and a high risk of information tampering. For this reason, this paper proposes a synergistic optimization strategy for electricity/carbon/green certificate virtual power plants based on blockchain cross-chain transactions. First, Latin Hypercubic Sampling (LHS) is used to generate new energy output and load scenarios, and the K-means clustering method with improved particle swarm optimization are combined to cut down the scenarios and improve the prediction accuracy; second, a relay chain cross-chain trading framework integrating quota system is constructed to realize organic synergy and credible data interaction among electricity, carbon, and green certificate markets; lastly, the multi-energy optimization model of the virtual power plant is designed to integrate carbon capture, Finally, a virtual power plant multi-energy optimization model is designed, integrating carbon capture, power-to-gas (P2G) and other technologies to balance the economy and low-carbon goals. The simulation results show that compared with the traditional model, the proposed strategy reduces the carbon emission intensity by 13.3% (1.43 tons/million CNY), increases the rate of new energy consumption to 98.75%, and partially offsets the cost through the carbon trading revenue, which verifies the Pareto improvement of environmental and economic benefits. This study provides theoretical support for the synergistic optimization of multi-energy markets and helps to build a low-carbon power system with a high proportion of renewable energy. Full article

The transition toward sustainable and decentralized energy solutions necessitates the development of innovative bioelectronic systems capable of harvesting and converting renewable energy. Here, we present a novel photo-bioelectrochemical fuel cell architecture based on a biohybrid anode integrating laser-induced graphene (LIG), poly(3,4-ethylenedioxythiophene) (PEDOT), and isolated thylakoid membranes. LIG provided a porous, conductive scaffold, while PEDOT enhanced electrode compatibility, electrical conductivity, and operational stability. Compared to MXene-based systems that involve complex, multi-step synthesis, PEDOT offers a cost-effective and scalable alternative for bioelectrode fabrication. Thylakoid membranes were immobilized onto the PEDOT-modified LIG surface to enable light-driven electron generation. Electrochemical characterization revealed enhanced redox activity following PEDOT modification and stable photocurrent generation under light illumination, achieving a photocurrent density of approximately 18 µA cm⁻². The assembled photo-bioelectrochemical fuel cell employing a gas diffusion platinum cathode demonstrated an open-circuit voltage of 0.57 V and a peak power density of 36 µW cm⁻² in 0.1 M citrate buffer (pH 5.5) under light conditions. Furthermore, the integration of a charge pump circuit successfully boosted the harvested voltage to drive a low-power light-emitting diode, showcasing the practical viability of the system. This work highlights the potential of combining biological photosystems with conductive nanomaterials for the development of self-powered, light-driven bioelectronic devices. Full article

Ammonia production is a cornerstone of the modern chemical industry, essential for fertilizer manufacturing and increasingly relevant in the energy sector. However, the conventional Haber–Bosch (HB) process is highly energy- and carbon-intensive, contributing significantly to global greenhouse gas emissions, releasing approximately 1.6 tonnes of carbon dioxide for every tonne of ammonia produced. In the context of the ongoing climate crisis, exploring sustainable alternatives that can reduce or even eradicate these emissions is imperative. This review examines the potential of ammonia as a future energy carrier and evaluates the transition to green hydrogen-based HB production. Key technologies for green hydrogen generation are reviewed in conjunction with environmental, energy, and economic considerations. The transition to a green hydrogen-based HB process has been demonstrated to offer significant environmental advantages, potentially reducing carbon emissions by up to eight times compared to the conventional method. Furthermore, the economic viability of this process is particularly pronounced under conditions of low-cost renewable electricity, whether utilizing solid oxide electrolysis cells or proton-exchange membrane electrolyzers. Additionally, two emerging zero-emission, electrochemical routes for ammonia synthesis are analyzed in terms of their methodologies, efficiencies, and economic viability. Promising progress has been made in both direct and indirect nitrogen reduction approaches to ammonia. The indirect lithium-mediated pathway demonstrates the greatest potential, significantly reducing ammonia production costs. Despite existing challenges, particularly related to efficiency, these emerging technologies offer decentralized, electrified pathways for sustainable ammonia production in the future. This study highlights the near-term feasibility of decarbonizing ammonia production through green hydrogen in the HB process, while outlining the long-term potential of electrochemical nitrogen reduction as a sustainable alternative once the technology matures. Full article

This study describes the step-by-step development of a simplified system which can be implemented in industrial facilities with the help of their own surplus of plastic waste, mainly packaging waste, to reach a level of energy autonomy or semi-autonomy. This waste is converted to about 57,500 L of synthetic pyrolysis oil, which can then be used to power industries, being fed into a Combined Heat and Power system. To achieve this goal, the design has hydrocarbon stability at elevated temperature and restricted oxygen exposure, so that they can be converted to new products. Pyrolysis is a key process which causes thermo-chemical changes—ignition and vaporization. The research outlines the complete process of creating a basic small-scale pyrolysis system which industrial facilities can use to generate energy from their plastic waste. The proposed unit processes 360 tons of plastic waste yearly to produce 160 tons of synthetic pyrolysis oil which enables the generation of 500 MWh of electricity and 60 MWh of heat. The total investment cost is estimated at EUR 41,000, with potential annual revenue of up to EUR 45,000 via net metering. The conceptual design proves both environmental and economic viability by providing a workable method for decentralized waste-to-energy solutions for Small and Medium-sized Enterprises. Full article

Global agriculture remains dependent on nitrogen fertilizers produced through fossil fuel-based processes, contributing to greenhouse gas emissions, energy use, and supply chain vulnerabilities. This review introduces plasma-activated water (PAW) as a novel, electricity-driven alternative for sustainable nitrogen delivery. Generated by non-thermal plasma, PAW infuses water with reactive oxygen and nitrogen species, offering a clean, decentralized substitute for conventional synthetic fertilizers derived from the Haber–Bosch and Ostwald processes. It can be produced on-site using renewable energy, reducing transportation costs and depending on fertilizers. Beyond its fertilizer properties, PAW enhances seed germination, plant growth, stress tolerance, and pest resistance, making it a multifunctional input for controlled environment agriculture. We also assess PAW’s techno-economic viability, including energy requirements, production costs, and potential scalability through renewable energy. These factors are crucial for determining its feasibility in both industrial systems and localized agricultural applications. Finally, the review examines PAW’s contribution to the ten United Nations Sustainable Development Goals, particularly in climate action, clean energy, and sustainable food production. By combining agronomic performance with circular production and emissions reduction, PAW presents a promising path toward more resilient, low-impact, and self-sufficient agricultural systems. Full article

Ghana’s electricity grid remains heavily fossil-fuel dependent (69%), resulting in high costs and unstable low-voltage (LV) networks, exacerbating supply shortages. This study evaluates the technical and economic feasibility of converting the Obaa-Yaa LV substation in Drobo, Ghana, into a solar-powered microgrid. Using the forward–backward method for technical analysis and financial metrics (NPV, IRR, DPP, and PI), the results show that rooftop solar on seven households generates 676,742 kWh annually—exceeding local demand by 115.8 kW—with no voltage violations (240 V ± 6%) and minimal losses (9.24 kW). Economic viability is demonstrated via an NPV of GHS 2.1M, IRR of 17%, and a 10-year payback. The findings underscore solar microgrids as a pragmatic solution for Ghana’s energy challenges, urging policymakers to incentivize decentralized renewable systems. Full article

The integration of non-conventional renewable energy sources (NCRES) plays a critical role in achieving sustainable and decentralized power systems. However, accurately assessing the economic feasibility of NCRES projects requires methodologies that account for policy-driven incentives and financing mechanisms. To support the shift towards NCRES, evaluating their financial viability while considering public policies and funding options is important. This study presents an improved version of the Levelized Cost of Electricity (LCOE) that includes government incentives such as tax credits, accelerated depreciation, and green bonds. We apply a flexible investment model that helps to find the most cost-effective financing strategies for different renewable technologies. To do this, we use three optimization techniques to identify solutions that lower electricity generation costs: Teaching Learning, Harmony Search, and the Shuffled Frog Leaping Algorithm. The model is tested in a case study in Colombia covering battery storage, large- and small-scale solar power, and wind energy. Results show that combining smart financing with policy support can significantly lower electricity costs, especially for technologies with high upfront investments. We also explore how changes in interest rates affect the results. This framework can help policymakers and investors design more affordable and financially sound renewable energy projects. Full article

The decarbonization of the heat supply is crucial for the German energy transition. Integrating Power-to-Heat technologies like heat pumps (HPs) into district heating grids (DHGs) can support this process. The efficiency of HPs can be increased through temperature reduction in the DHG, though decentralized reheating may be required to supply sufficient heat for the end consumers. In order to investigate the associated trade-off, this study evaluates the economic, ecological, and technical effects of temperature reduction in DHGs using the software tool nPro. In a three-step process heat demand, the DHG design and operation are modeled. Three operating temperature scenarios are considered: 60 °C, 50 °C, and an ambient dependent flow temperature varying between 40 and 50 °C. As the temperatures decrease, the balance shifts between centrally produced HP heat and decentralized heat from instantaneous electric water heaters (IEWHs). The initial temperature reduction leads to reduced CO₂ emissions, primary energy demand, heat losses, and total annual cost (TAC). However, with a further reduction in the operating temperature, an increase in these parameters occurs. While the necessary cost and primary energy for central components decrease, an increase in the decentralized heat generation is necessary to properly supply the heat demand. This leads to higher TAC and CO₂ emissions overall. Full article

This study presents the development and evaluation of a stand-alone solar dryer designed to improve the efficiency of bee bread dehydration. Unlike the electric prototype powered by conventional energy sources, the proposed system operates autonomously, utilizing solar energy as the primary drying agent. The drying chamber is equipped with solar collectors located in its lower section, which ensure convective heating of the product. Active convection is generated by a set of fans powered by photovoltaic panels, maintaining the drying agent’s temperature near 42 °C. The research methodology integrates both numerical simulation and experimental investigation. Simulations focus on the variations in temperature (288–315 K) and relative humidity (1–1.5%) within the honeycomb structure under convective airflow. Experimental trials examine the relationship between moisture content and variables such as bee bread mass, airflow rate, number of frames (5–11 units), and drying time (2–11 h). A statistically grounded analysis based on an experimental design method was conducted, revealing a reduction in moisture content from 16.2–18.26% to 14.1–15.1% under optimized conditions. Linear regression models were derived to describe these dependencies. A comparative assessment using enthalpy–humidity (I–d) diagrams demonstrated the enhanced drying performance of the solar dryer, which is attributed to its cyclic operation mode. The results confirm the potential of the developed system for sustainable and energy-efficient drying of bee bread in decentralized conditions. Full article

Power systems are currently undergoing a transition from centralized synchronous generators to decentralized non-synchronous generators that rely on renewable energy sources. This shift poses a challenge to system operators, as the high penetration levels of renewable energy introduce variability and changes in the physics of power systems. Load-frequency control is one of the biggest challenges faced by electrical grids, especially with increased wind energy penetration in recent years. The inertial controller is one of the methods used to support system frequency in variable-speed wind turbines. In this study, a proportional resonant (PR) controller was added to an inertial controller to achieve better frequency regulation by controlling the active power of the doubly fed induction generator (DFIG). First, the impact of the PR controller parameters on the frequency deviation, overshoot, settling time, and system stability was investigated to identify the optimal values that achieved the lowest frequency deviation while maintaining system stability. Second, the performance of the proposed method was compared that of the traditional method under different load perturbations. The results prove that improperly determining the proportional gain of the PR controller negatively affects system stability and frequency deviation. In addition, the results validate the hypothesis that the proposed method would provide fast frequency support for all the studied cases. The analysis and simulation of these scenarios were performed using the MATLAB/SIMULINK program. Full article

Future decarbonization targets demand a higher penetration of renewable energy (RE) sources into the system. However, challenges such as an uneven spatial and temporal distribution of various RE sources’ potential for green electricity (GE) generation demand alternative ways to store and later utilize the generated energy. In addition to that, sustainable development goals (SDGs) highlight the need for the responsible use of resources with increased recycling and a reduction in corresponding waste generation while ensuring access to affordable, reliable, sustainable, and modern energy for all. In this paper, an attempt is made to address both the issues of biodegradable waste (BW) processing and sustainable hydrogen (SH) production through it. Thermochemical conversion technology (TCC) and, within that, especially ‘thermocatalytic reforming’ (TCR^®) technology have been explored as options to provide viable solutions. An added advantage of decentralized hydrogen production can be envisioned here that can also contribute to regional energy security to some degree. To analyze the concept, the Bavarian region in Germany, along with open-source data for bio-waste from two main sources, namely domestic household and sewage sludge (SS), were considered. Based on that, the corresponding regional hydrogen demand coverage potential was analyzed. Full article

Carbon nanotubes (CNTs) exhibit high strength and high modulus, excellent electrical and thermal conductivity, good chemical stability, and unique electronic and optical properties. These characteristics make them a one-dimensional nanomaterial with extensive potential applications in fields such as composite materials, electronic devices, energy, aerospace, and medical technology. Cement-based materials are the most widely used and extensively applied construction materials. However, these materials have disadvantages such as low tensile strength, brittleness, porosity, shrinkage, and cracking. In order to compensate for these shortcomings, in recent years, relevant scholars have proposed to integrate CNTs into cement-based materials. Incorporating CNTs into cement-based materials not only enhances the microstructure of these materials but also improves their mechanical, electrical, and durability properties. The characteristics and fabrication process of CNTs are reviewed in this paper. The different effects of CNTs on the physical properties and hydration properties of cement-based materials due to the design parameters, dispersion methods, and temperature were analyzed. The results show that the compressive and flexural strength of CNT cement-based materials with 0.02% content increased by 9.33% and 10.18% from 3 d to 28 d. In terms of reducing the shrinkage and carbonization resistance of the cement base, there is an optimal amount of carbon nanotubes. The addition of dispersed carbon nanotubes reduces the resistivity, and the nucleation of carbon nanotubes promotes the hydration reaction. In general, under the optimal dosage, carbon nanotubes with uniform dispersion and short length–diameter ratio have a significant effect on the cement-based lifting effect. In the future, CNT cement-based materials will develop high strength, multifunctionality, and low cost, realizing intelligent self-sensing and self-repair and promoting green and low-carbon manufacturing. Breakthroughs in decentralized technology and large-scale applications are key, and they are expected to help sustainable civil engineering with intelligent infrastructure. Full article