Search Results (208)

In the context of the global response to climate change and the active promotion of energy transformation, a number of low-carbon policies coupled with the development of synergies to help power system transformation is an important initiative. However, the insufficient articulation of the green power market, tradable green certificate (TGC) market, and carbon emission trading (CET) mechanism, and the ambiguous policy boundaries affect the trading decisions made by its market participants. Therefore, this paper systematically analyses the composition of the main players in the electricity-CET-TGC markets and their relationship with each other, and designs the synergistic mechanism of the electricity-CET-TGC markets, based on which, it constructs the optimal profit model of the thermal power plant operators, renewable energy manufacturers, power grid enterprises, power users and load aggregators under the electricity-CET-TGC markets synergy, and analyses the behavioural decision-making of the main players in the electricity-CET-TGC markets as well as the electric power system to optimise the trading strategy of each player. The results of the study show that: (1) The synergistic mechanism of electricity-CET-TGC markets can increase the proportion of green power grid-connected in the new type of power system. (2) In the selection of different environmental rights and benefits products, the direct participation of green power in the market-oriented trading is the main way, followed by applying for conversion of green power into China certified emission reduction (CCER). (3) The development of independent energy storage technology can produce greater economic and environmental benefits. This study provides policy support to promote the synergistic development of the electricity-CET-TGC markets and assist the low-carbon transformation of the power industry. Full article

Renewable Energy Communities (RECs) are voluntary coalitions of citizens, small and medium-sized enterprises and local authorities, which cooperate to share locally produced renewable energy, providing environmental, economic, and social benefits rather than profits. Despite a favorable European and Italian regulatory framework, their development is still limited in the Member States. To this end, this paper proposes a methodology to identify optimal spatial configurations of RECs, based on proximity criteria and maximization of energy self-sufficiency. This result is achieved through the mapping of the demand, expressive of the energy consumption of residential buildings; the suitable areas for installing photovoltaic panels on the roofs of existing buildings; the supply; the supply–demand balance, from which it is possible to identify Positive Energy Districts (PEDs) and Negative Energy Districts (NEDs). Through an iterative process, the optimal configuration is then sought, aggregating only PEDs and NEDs that meet the chosen criteria. This method is applied to the case study of the Avellino Province in the Campania Region (Italy). The maps obtained allow local authorities to inform citizens about the areas where it is convenient to aggregate with their neighbors in a REC to have benefits in terms of energy self-sufficiency, savings on bills or incentives at the local level, including those deriving from urban plans. The latter can encourage private initiative in order to speed up the RECs’ deployment. The presented model is being implemented in the framework of an ongoing research and development project, titled Renewable Energy Communities Monitoring, Optimization, and Planning (RECMOP). Full article

The Carbon Emissions Trading System (ETS) serves as a market-based mechanism to drive renewable energy (RE) investments, yet its heterogeneous impacts on different stakeholders remain underexplored. This paper treats the carbon market as an exogenous shock and develops a multi-agent equilibrium model incorporating carbon pricing, encompassing power generation enterprises, power transmission enterprises, power consumers, and the government, to analyze how carbon prices reshape RE investment layouts under dual-carbon goals. Using panel data from Zhejiang Province (2017–2022), a high-energy-consumption region with 25% net electricity imports, we simulate heterogeneous responses of agents to carbon price fluctuations (CNY 50–250/ton). The results show that RE on-grid electricity increases (+0.55% to +2.89%), while thermal power declines (–4.98% to −15.39%) on the generation side. Transmission-side RE sales rise (+3.25% to +9.74%), though total electricity sales decrease (−0.49% to −2.22%). On the consumption side, RE self-generation grows (+2.12% to +5.93%), yet higher carbon prices reduce overall utility (−0.44% to −2.05%). Furthermore, external electricity integration (peaking at 28.5% of sales in 2020) alleviates provincial entities’ carbon cost pressure under high carbon prices. This study offers systematic insights for renewable energy investment decisions and policy optimization. Full article

Circular economy is a crucial strategy for achieving sustainable development. The use of solar PV, which is a renewable energy source, has been considered a popular indicator to measure and evaluate the circularity of an economy and enterprises. The recycling of solar PV panels optimises resource use and reduces the need for virgin materials. However, it does not automatically indicate an environmental advantage if the recovering and recycling processes are energy- or emission-intensive. The paper applies life cycle assessment to quantify the material demand for the Italian solar PV sector and contributions of solar PV end-of-life strategies to the enhancement of the circular economy. It is identified that the material intensity of the Italian solar PV sector increases from 4.67 g Sb eq to 5.20 g Sb eq per MWh by 2040 due to the change in technology mix. At the same time, the total material demand, as well as demand for specific materials, increases over the years, from 2008 to 2040. The strategy on recovery, recycling and reintegration of materials slightly reduces the material demand, from 816 tonnes Sb eq to 814 tonnes Sb eq in 2040. It also brings the benefits of reducing all the life cycle impacts, such as greenhouse gas emissions, energy demand, etc. Full article

Amid the escalating global climate crisis, the transition to sustainable energy systems has become imperative. As the world’s largest energy producer and consumer, China has established ambitious dual carbon targets, which present formidable challenges to urban energy systems that remain heavily reliant on conventional energy sources and exhibit inadequate renewable energy development. Drawing on complex adaptive systems theory, this study investigates the extent to which digital finance enhances urban energy resilience, examining both the underlying mechanisms and heterogeneous effects. Employing a multi-period difference-in-differences model with digital finance policies as a quasi-natural experiment, our analysis of panel data from 31 Chinese provinces (2016–2023) demonstrates that digital finance significantly enhances the resilience of urban energy systems and their three constituent subsystems. A mediation analysis reveals the pivotal role of innovative organizations, while machine learning techniques uncover nonlinear relationships moderated by marketization levels, fiscal energy allocations, and initial digital finance development. These findings provide critical insights for policymakers, financial institutions, and energy enterprises seeking to advance sustainable energy governance and foster financial innovation in the energy transition. Full article

This article aims to assess the conditions and prospects for biomass utilization in the Visegrad Group (V4) countries. Additionally, the relationship between biomass energy production and greenhouse gas emissions was examined. A key component of the analysis involved identifying potential directions for the development of biomass utilization in the pursuit of the sustainable development of agricultural enterprises. In relation to these research objectives, a hypothesis was formulated regarding the causal relationship between biomass energy consumption and economic growth, the abundance of natural resources, and income in reference to the European Union economies. Both static and dynamic panel studies were applied. The conducted research revealed the complex nature of the conditions influencing biomass utilization. The study period covered the years 2004–2022. A negative correlation was found between the use of biomass and greenhouse gas emissions. At the same time, factors favoring biomass utilization included economic growth, the level of natural resource consumption per capita, and government policies aimed at increasing the share of renewable resources in the economy. Full article

The bakery industry is undergoing a profound digital transformation driven by the increasing need for enhanced energy efficiency, operational resilience, and a commitment to environmental sustainability. Digital Twin (DT) technology, recognized as a fundamental component of Industry 4.0, provides advanced capabilities for intelligent energy management across bakery operations. This paper utilizes a narrative and integrative review approach, conceptually integrating emerging developments in using DT with respect toenergy management in the baking industry, including real-time energy monitoring, predictive maintenance, dynamic optimization of production processes, and the seamless integration of renewable energy sources. The study underscores the transformative benefits of adopting DT technologies, such as improvements in energy utilization, greater equipment reliability, increased operational transparency, and stronger alignment with global sustainability objectives. It also critically examines the technical, organizational, and financial barriers limiting broader adoption, particularly among small and medium-sized enterprises (SMEs). Future research directions are identified, emphasizing the potential of artificial intelligence-driven DTs, the adoption of edge computing, the development of scalable and modular platforms, and the necessity of supportive policy frameworks. By integrating DT technologies, bakeries can shift from traditional reactive energy practices to proactive, data-driven strategies, paving the way for greater competitiveness, operational excellence, and a sustainable future. Full article

Although the integration of large-scale energy storage with renewable energy can significantly reduce electricity costs for steel enterprises, existing energy storage technologies face challenges such as deployment constraints and high costs, limiting their widespread adoption. This study proposes a gravity energy storage system and its capacity configuration scheme, which utilizes idle steel blocks from industry overcapacity as the energy storage medium to enhance renewable energy integration and lower corporate electricity costs. First, a stackable steel-based gravity energy storage (SGES) structure utilizing idle blocks is designed to reduce investment costs. Second, a gravity energy storage capacity planning model is developed, incorporating economic and structural collaborative optimization to maximize profitability and minimize construction costs. Finally, a Rime and particle swarm optimization (RI-PSO) fusion algorithm is proposed to efficiently solve the optimization problem. The results demonstrate that under equivalent power and capacity conditions, the SGES structure achieves 90.11% lower costs than compressed air energy storage and 59.7% lower costs than electrochemical storage. The proposed algorithm improves convergence accuracy by 21.19% compared to Rime and 4.21% compared to PSO and increases convergence speed by 72.34% compared to Rime. This study provides an effective solution for steel enterprises to reduce costs. Full article

While digital transformation in e-commerce receives the most publicity, applications in energy and water utilities have been ongoing for decades. Using a methodology based on a systematic review, the paper offers a model of how it occurs in water utilities, reviews experiences from the field, and derives lessons learned to create a road map for future research and implementation. Innovation in water utilities occurs more in the field than through organized research, and utilities share their experiences globally through networks such as water associations, focus groups, and media outlets. Their digital transformation journeys are evident in business practices, operations, and asset management, including methods like decision support systems, SCADA systems, digital twins, and process optimization. Meanwhile, they operate traditional regulated services while being challenged by issues like aging infrastructure and workforce capacity. They operate complex and expensive distribution systems that require grafting of new controls onto older systems with vulnerable components. Digital transformation in utilities is driven by return on investment and regulatory and workforce constraints and leads to cautious adoption of innovative methods unless required by external pressures. Utility adoption occurs gradually as digital tools help utilities to leverage system data for maintenance management, system renewal, and water loss control. Digital twins offer the advantages of enterprise data, decision support, and simulation models and can support distribution system optimization by integrating advanced metering infrastructure devices and water loss control through more granular pressure control. Models to anticipate water main breaks can also be included. With such advances, concerns about cyber security will grow. The lessons learned from the review indicate that research and development for new digital tools will continue, but utility adoption will continue to evolve slowly, even as many utilities globally are too stressed with difficult issues to adopt them. Rather than rely on government and academics for research support, utilities will need help from their support community of regulators, consultants, vendors, and all researchers to navigate the pathways that lie ahead. Full article

Transportation infrastructure systems sit at the nexus of urban economic development and emission mitigation. The primary objective is to identify and quantify the key factors influencing CI, with a focus on both the conventional and emerging indicators through an innovative MLP neural network developed using the data of 20 Chinese transportation enterprises that have a business focus on the construction and operation sector from 2018 to 2022. The hypothesis is that integrating unconventional indicators—such as business model entropy and green revenue share—alongside traditional metrics can significantly enhance the predictive accuracy for CI. The results show that business model entropy explains 42.6% of carbon intensity (Cl) variability through green revenue diversification pathways, while emissions trading system (ETS) exposure accounts for 51.83% of decarbonization outcomes via price-signaling effects. The analysis reveals that a critical operational threshold–renewable energy capacity below 75% fails to significantly reduce Cl, and capex/revenue ratios exceeding 73.58% indicate carbon lock-in risks. These findings enable policymakers to prioritize industries with sub-75% renewable adoption while targeting capex-intensive sectors for circular economy interventions. The novelty of this work lies in the application of advanced machine-learning techniques to a comprehensive, multi-source dataset, enabling a nuanced analysis of CI drivers and offering actionable insights for policymakers and industry stakeholders aiming to decarbonize transport infrastructure. Full article

The buffalo species (Bubalus bubalis) is crucial for the global economy, supplying high-nutritional-value animal proteins vital for children’s growth. These animals efficiently convert fiber into energy and thrive in various harsh environments, from frigid climates to hot, humid areas, including wetlands. They produce milk and meat while supporting the sustainability of ecosystems that other ruminants cannot inhabit. Buffalo offers a unique opportunity to supply resources for both rural communities and larger farms located in specific regions, such as marshlands and humid savannahs. They also thrive on extensive pastures and family farms, thus preserving biodiversity, habitats, and cultural practices. Intensive farming brings distinct challenges and is often criticized for its negative effects on climate change. To counter these impacts, multiple strategies have been researched and implemented. These include enhancing livestock genetics, adopting sustainable agricultural practices, optimizing local feed resources (including by-products), managing manure (with an emphasis on renewable energy), and improving animal health and welfare. This review explores various buffalo farming system applications in different global contexts. It is based on the hypothesis that the adaptable traits of buffalo, as well as the environmental and economic challenges that must be addressed for sustainability, are the key factors in determining the viability of such enterprises. Full article

Reducing the peak power demand at the level of a considered factory and setting the proper operating regimes of electrical devices located in a factory are the problems raised in this paper. These are essential challenges in industrial facilities, especially when existing highly variable loads for power demand, highly variable renewable sources for power generation, and electrical energy storage systems are considered. Appropriate studies relating to this question were performed within the DIEGO international research project (Digital Energy Path for Planning and Operation of Sustainable Grid, Products, and Society). First, the paper presents the technical characteristics of the electric power grid in the considered factory and analyses the results of the measurements performed in the scope of the load and generation of electrical energy in the factory. Next, the paper presents considered preventive measures for limiting peak electric loads at the industrial enterprise level and describes the results of the effectiveness evaluation of the defined preventive measures. The issue of setting the proper operating regimes for electrical devices installed in the factory is also presented. Multi-agent systems have been implemented for this purpose. The paper presents and discusses the results of the implementation. Full article

Alfalfa (Medicago sativa L.) plays a crucial role in the revitalization of the dairy industry and grassland agriculture in China. However, regional differences in economic and environmental performance have not been adequately specified or quantified. This study compares alfalfa production in Wuhe County (Southern China) and Ar Horqin Banner (Northern China) by integrating cost–benefit analysis (CBA) with life cycle assessment (LCA). Field data from 22 enterprises were analyzed using one ton of alfalfa hay and a net profit of CNY 10,000 as functional units, over a three-year evaluation period (2017–2019). The assessment encompassed four impact categories: primary energy demand (PED), global warming potential (GWP), acidification potential (AP), and water use (WU). The northern case systems exhibited 67.45% higher production costs but 96.99% greater profitability per ton compared to the southern case, alongside 2.13 × 10⁻² greater environmental impact. Conversely, the southern case systems were less profitable and demonstrated an 18.6% higher environmental impact per CNY 10,000 net profit compared to the northern case. Regional environmental hotspots differed: fertilizer use dominated impact in the south, whereas irrigation and electricity consumption drove burdens in the north. To facilitate a sustainable transition, policymakers should implement region-specific support measures, such as ecological incentives and crop rotation schemes for the south, and water-saving technologies along with renewable energy integration for the north. Farmers and enterprises are encouraged to adopt precision input strategies and climate risk management tools, while researchers should focus on advancing adaptive breeding techniques and optimizing resource utilization. The development of a unified system that integrates economic and environmental metrics is crucial for enabling stakeholders to drive the sustainable transformation of alfalfa production. Full article

The intensifying impacts of climate change induced by carbon emissions necessitate the implementation of urgent mitigation strategies. Given that the power sector is a major contributor to global carbon emissions, strategic decarbonization planning in this sector is of paramount importance. This study proposes a synergistic planning framework for low-carbon power systems that integrates coal-fired power plants (CFPPs) and a carbon and green certificate market coupling mechanism, thereby facilitating a “security–economic–low-carbon” tri-objective transition in power systems. The proposed framework facilitates dynamic decision-making regarding the retrofitting of CFPPs, investments in renewable energy resources, and energy storage systems. By evaluating three distinct CFPP retrofitting pathways, the framework enhances economic efficiency and reduces carbon emissions, achieving reductions of 28.67% in total system costs and 2.96% in CO₂ emissions. Implementing the carbon–green certificate market coupling mechanism further unlocks the market value of green certificates, thereby providing economic incentives for clean energy projects and increasing flexibility in the allocation of carbon emission quotas for enterprises. Relative to cases that consider only carbon trading or only green certificate markets, the coupled mechanism reduces the total cost by 10.96% and 15.56%, and decreases carbon emissions by 27.10% and 47.36%, respectively. The collaborative planning framework introduced in this study enhances economic performance, increases renewable energy penetration, and reduces carbon emissions, thus facilitating the low-carbon transition of power systems. Full article

In contemporary times, energy sustainability and security have become essential economic concerns globally. Nonetheless, in addition to these concerns, inadequate governance inside a corporation within the energy industry may result in corruption and energy instability within the sector. The primary purpose of this study was to examine the influence of a new array of corporate governance controversies on the energy security of 102 listed energy businesses in Europe. To achieve the purpose of this study, entropy weight and TOPSIS multicriteria approaches were used. The data were obtained from the Refinitiv Eikon database for fiscal year 2024. The findings reveal that the most significant influence, among the identified governance concerns that affect the energy security of European energy corporations, is the detrimental effect of the directors’ people. Moreover, the criteria that constitute bribery, corruption, and fraud scandals seem to be the second most significant element affecting the energy security of the enterprises in this industry. The risk of corruption in governance is exacerbated in the realm of renewable energy due to several converging factors: the urgent demands to implement new projects in response to the climate crisis, apprehensions regarding energy security, potential access to lucrative contracts, and the existence of ‘rent-seeking’ gatekeepers within the processes central to the development and operation of renewable energy assets. Full article