Search Results (274)

This paper presents a comprehensive techno-economic assessment of a community battery energy storage system (BESS) participating concurrently in energy arbitrage and frequency control ancillary services (FCAS) markets, while also providing customer savings through coordinated demand management. The proposed framework employs a mixed-integer linear programming (MILP) model to co-optimize the charging, discharging, and reserve scheduling of the battery under dynamic market conditions. The model explicitly incorporates key operational and economic factors such as round-trip efficiency, degradation cost, market-participation constraints, and revenue from multiple value streams. By formulating the optimization problem within this MILP structure, both the operational feasibility and the economic profitability of the system are evaluated over annual market cycles. Simulation results demonstrate that integrating FCAS participation with conventional energy arbitrage substantially enhances total revenue potential and improves asset utilization, compared with single-service operation. Furthermore, the coordinated management of community demand contributes to additional cost savings and supports local grid reliability. The findings highlight the critical role of co-optimized control and multi-market participation strategies in improving the financial viability and grid-support capabilities of community-scale BESS deployments. Full article

A comprehensive assessment of photovoltaic (PV) enhancement technologies requires a metric that incorporates not only performance gains but also economic viability and system compatibility. This paper introduces the Lifespan-, Surface-area-, and Cost-Adjusted Effectiveness factor (${\mathrm{F}}_{\mathrm{L}\mathrm{S}\mathrm{C}\mathrm{A}\mathrm{E}}$), a novel multi-dimensional indicator designed to evaluate the overall effectiveness of PV enhancers—such as passive and active coolers—by jointly accounting for lifespan alignment, spatial integration, and cost-to-performance trade-offs. Unlike conventional performance metrics, ${\mathrm{F}}_{\mathrm{L}\mathrm{S}\mathrm{C}\mathrm{A}\mathrm{E}}$ captures the interdependence between technical and economic parameters by integrating the enhancer’s contribution to net power output, its operational lifespan relative to the PV module, its physical area relative to the PV surface, and the manufacturing cost in relation to the cost per watt of PV power. A series of analytical case studies were conducted involving four PV cooler patterns with varying power outputs, costs, sizes, and lifespans. The findings demonstrate that ${\mathrm{F}}_{\mathrm{L}\mathrm{S}\mathrm{C}\mathrm{A}\mathrm{E}}$ is highly sensitive to power enhancement and cost fluctuations, and it penalizes oversizing or lifespan mismatches. Furthermore, the minimum threshold effectiveness (${\mathrm{F}}_{\mathrm{L}\mathrm{S}\mathrm{C}\mathrm{A}\mathrm{E},\mathrm{m}\mathrm{i}\mathrm{n}}$), derived from the ratio of actual to maximum PV output under standard test conditions, provides a robust baseline for determining system viability. The proposed metric proves to be a reliable and scalable tool for the comparative evaluation of PV enhancement strategies. It enables stakeholders to make informed decisions about design optimization, financial planning, and policy formulation. ${\mathrm{F}}_{\mathrm{L}\mathrm{S}\mathrm{C}\mathrm{A}\mathrm{E}}$ serves as a critical advancement in PV performance analysis, offering a unified framework to assess not only energy gain but also the practicality and sustainability of PV enhancement technologies. Full article

Cross-regional enterprise financial distress can undermine long-term corporate viability, weaken regional industrial resilience, and amplify systemic risk, making robust early-warning tools essential for sustainable financial governance. This study investigates the problem of cross-regional enterprise delisting-related distress identification under heterogeneous economic structures and highly imbalanced risk samples. We propose a cross-domain learning framework that aims to deliver stable, interpretable, and transferable risk signals across regions without requiring access to labeled data from the target domain. Using a multi-source empirical dataset covering Beijing, Shanghai, Jiangsu, and Zhejiang, we conduct leave-one-domain-out evaluations that simulate real-world regulatory deployment. The results demonstrate consistent improvements over representative sequential and graph-based baselines, indicating stronger cross-regional generalization and more reliable identification of borderline and noisy cases. By linking cross-domain stability with uncertainty-aware risk screening, this work contributes a practical and economically meaningful solution for sustainable corporate oversight, offering actionable value for policy-oriented financial supervision and regional economic sustainability. Full article

Maintaining the stability of the mine roadway is of paramount importance, as it is critical in ensuring the daily operational continuity, personnel safety, long-term economic viability, and sustainability of the entire mining operation. Significant instability can trigger serious disruptions—such as production stoppages, equipment damage, and severe safety incidents—which ultimately compromise the project’s financial returns and future prospects. Therefore, the proactive assessment and rigorous control of roadway stability constitute a foundational element of successful and sustainable resource extraction. In China, thick and extra-thick coal seams constitute over 44% of the total recoverable coal reserves. Consequently, their safe and efficient extraction is considered vital in guaranteeing energy security and enhancing the efficiency of resource utilization. The surrounding rock of gob-side roadways in typical coal seams is often fractured due to high ground stress, intensive mining disturbances, and overhanging goaf roofs. Consequently, asymmetric failure patterns such as bolt failure, steel belt tearing, anchor cable fracture, and shoulder corner convergence are common in these entries, which pose a serious threat to mine safety and sustainable mining operations. This deformation and failure process is associated with several parameters, including the coal seam thickness, mining technology, and surrounding rock properties, and can lead to engineering hazards such as roof subsidence, rib spalling, and floor heave. This study proposes countermeasures against asymmetric deformation affecting gob-side entries under intensive mining pressure during the fully mechanized caving of extra-thick coal seams. This research selects the 8110 working face of a representative coal mine as the case study. Through integrated field investigation and engineering analysis, the principal factors governing entry stability are identified, and effective control strategies are subsequently proposed. An elastic foundation beam model is developed, and the corresponding deflection differential equation is formulated. The deflection and stress distributions of the immediate roof beam are thereby determined. A systematic analysis of the asymmetric deformation mechanism and its principal influencing factors is conducted using the control variable method. A support approach employing a mechanical constant-resistance single prop (MCRSP) has been developed and validated through practical application. The findings demonstrate that the frequently observed asymmetric deformation in gob-side entries is primarily induced by the combined effect of the working face’s front abutment pressure and the lateral pressure originating from the neighboring goaf area. It is found that parameters including the immediate roof thickness, roadway span, and its peak stress have a significant influence on entry convergence. Under both primary and secondary mining conditions, the maximum subsidence shows an inverse relationship with the immediate roof thickness, while exhibiting a positive correlation with both the roadway span and the peak stress. Based on the theoretical analysis, an advanced support scheme, which centers on the application of an MCRSP, is designed. Field monitoring data confirm that the peak roof subsidence and two-side closure are successfully limited to 663 mm and 428 mm, respectively. This support method leads to a notable reduction in roof separation and surrounding rock deformation, thereby establishing a theoretical and technical foundation for the green and safe mining of deep extra-thick coal seams. Full article

This study investigates whether Battery Electric Vehicles (BEVs) or Fuel Cell Electric Vehicles (FCEVs) represent the superior alternative to conventional vehicles for last-mile delivery, with a particular focus on large enterprises that prioritize both economic feasibility and environmental performance. Life Cycle Assessment and Life Cycle Cost methodologies are applied to evaluate both technologies across the full cradle-to-grave life cycle within a unified framework. The functional unit is defined as one kilometer traveled by a BEV or FCEV in last-mile transportation, and the system boundary includes vehicle manufacturing, operation, maintenance, and end-of-life treatment. The environmental impacts are assessed using the ReCiPe 2016 Midpoint (H) method implemented in OpenLCA 2.0.4, and normalization follows the standards provided by the official ReCiPe 2016 framework. The East China Power Grid serves as the baseline electricity mix for the operational stage. Regarding GHG emissions, FCEVs demonstrate a 12.36% reduction in carbon dioxide (CO₂) emissions compared to BEVs. This reduction is particularly significant during the operational phase, where FCEVs can lower CO₂ emissions by 53.51% per vehicle relative to BEVs, largely due to hydrogen energy’s higher efficiency and durability. In terms of economic costs, BEVs hold a slight advantage over FCEVs, costing approximately 0.8 RMB/km/car less. However, during the manufacturing phase, FCEVs present greater environmental challenges. It is recommended that companies fully consider which environmental issues they wish to make a greater contribution to when selecting vehicle types. This study provides insight and implications for large companies with financial viability concerns about environmental impact regarding selecting the two types of vehicles for last-mile transportation. The conclusions offer guidance for companies assessing which vehicle technology better aligns with their long-term operational and sustainability priorities. It can also help relevant practitioners and researchers to develop solutions to last-mile transportation from the perspective of different enterprise sizes. Full article

Despite growing technological and economic viability, the adoption of solar energy in the United States remains low. This research synthesizes 96 peer-reviewed publications from 2000 to 2024 to investigate how public perceptions, user psychology, institutional setups, and socioeconomic contexts shape solar energy adoption decisions in the United States. Drawing on a PRISMA systematic review of publications gathered from Scopus and Web of Science databases, the study reveals that solar adoption is influenced not only by environmental concern and perceived economic benefits but also by institutional trust, social norms, cognitive biases, and demographic characteristics. Key findings highlight that while higher income and education levels enable adoption, marginalized communities face persistent barriers, including institutional distrust, limited awareness, and constrained access to financing. Residential rooftop solar projects receive higher public approval than utility-scale developments, with agrivoltaics systems emerging as a promising middle ground. This review identifies critical gaps in public awareness and institutional credibility, calling for integrated policy responses that combine financial incentives with inclusive engagement strategies. By emphasizing the socio-behavioral dimensions of energy transitions, it offers actionable insights for policymakers, energy planners, and researchers aiming to broaden solar accessibility and equity. It underscores the need for future research on identity-driven adoption behavior, participatory energy planning, and depoliticized communication to bridge the intention-action gap and accelerate the just transition to solar energy. Full article

Broccoli waste (Brassica oleracea), comprising non-commercialized stems and leaves, represents a valuable substrate for bioenergy and commodity recovery within agro-industrial systems. This study evaluates the potential of dark fermentation (DF) to produce hydrogen (H₂) and carbon dioxide (CO₂) from unpretreated broccoli residues. Batch experiments (120 mL) yielded maximum gas production rates of up to 166 mL/L·d, with final compositions of 41.43 mol% and 58.56 mol% of H₂ and CO₂, respectively. Based on these results, two biorefinery models were simulated using COCO v3.10 and SuperPro Designer^® v12.0, incorporating absorption and cryogenic separation technologies in the purification stage. Two scenarios were considered: Option A (169.82 kmol/day; H₂: 0.5856 mol fraction, CO₂: 0.4143 mol fraction) and Option B (72.84 kmol/day; H₂: 0.6808 mol fraction, CO₂: 0.3092 mol fraction). In both configurations, the purities of the final streams were the same, being 99.8% and 99.8% for both H₂ and CO₂, respectively. However, energy consumption was 43.76% higher in the cryogenic H₂/CO₂ separation system than in the absorption system. Noteworthily, this difference does not depend on the stream’s composition. Furthermore, from a financial standpoint, the cryogenic system is more expensive than the absorption system. These findings confirm the feasibility of designing biorefineries for H₂ production with high CO₂ recovery from broccoli waste. However, the economic viability of the process depends on the valorization of the secondary effluent from the fermentation reactor, which may require subsequent anaerobic digestion stages to complete the degradation of residual organic matter and enhance overall resource recovery. Full article

The agricultural economic policy in Mexico has inadequately addressed the integrated sustainability needs of the rural sector. This study adopts a sustainability perspective to examine economic policy distortions and market failures in the export-oriented rose cultivation sector, and evaluates their effects on the economic and social sustainability of producers in Tenancingo and Villa Guerrero, Mexico. A Policy Analysis Matrix (PAM) and CONEVAL poverty line metrics were used to evaluate private and social profitability as indicators of financial viability and resource use efficiency. Findings indicate that, despite being supported by distortionary policies, the rose export sector remains competitive and financially viable, constituting a key pillar of economic sustainability. Moreover, the social profitability of rose production exceeded its private profitability, suggesting a net positive socioeconomic benefit and a sustainable allocation of resources from a societal perspective. Furthermore, per capita income in the rose production unit (RPU) exceeded the poverty line established by CONEVAL, directly supporting social sustainability and strengthening livelihood resilience. The study concludes that current resource allocation mechanisms are inefficient for sustainability over the long term. It emphasizes the need for policy shifts toward greater innovation, more effective technology transfer, improved market access, and stronger human capital to strengthen the sustainability of the sector as a whole. Rose cultivation exhibited a significant positive multiplier effect on the regional economy, reinforcing its contribution to sustainable rural development. Full article

This work presents an assessment focused on technical, economic, and resilience-related aspects applied to a crude palm oil production process using the FP²O methodology, considering a capacity of 30 tons of fresh fruit bunches (FFB) per hour and an annual production of 54,056 tons of oil per year. Operating parameters, capital and input costs, as well as the total investment, which amounts to approximately US$43 million, distributed between fixed capital, working capital, and start-up costs, were established. The analysis identified annual operating costs of US$24.7 million, with a majority share of raw materials. Economic and financial indicators showed positive values, higher than previous studies, highlighting a gross profit of over US$23 million, an after-tax profitability of US$13.7 MM, and an internal rate of return of 25.29%, which demonstrates the economic viability of the process. A simple payback period of 1.62 years and a discounted payback period of 4.88 years were determined, in addition to a positive net present value of $58.74 million, confirming the project’s profitability over a 15-year horizon. Using the FP²O methodology, the technical and economic resilience of the process to variations in product price, raw material costs, processing capacity, and normalized operating costs was evaluated. The results showed sensitivity to reductions in the oil sales price, while also demonstrating high resilience to increases in palm bunch costs and decreases in processing capacity. Furthermore, the break-even analysis revealed that the plant can operate 36.59% below its maximum capacity and maintain positive margins, requiring a minimum of 87,825 tons of raw material per year and a sales price of $482.35 per ton to avoid losses. This research highlights the applicability of the FP²O methodology as a strategic tool for scaling up crude palm oil production processes, guiding investment decisions, and supporting policies that promote more resilient and sustainable agro-industrial systems. Full article

This study assessed the economic and financial viability of representative smallholder dairy farms (RSDFs) by analyzing two farm types: (1) RSDFs that rely exclusively on family labor and milk receipts, and (2) RSDFs that employ hired labor and obtain income from milk in addition to sales of crops and agricultural by-products. A stochastic simulation based on empirical distributions derived from 44 years of historical data was used to project a 10-year horizon. Results indicate a low-to-minimal probability of decapitalization, an overall outlook of economic and financial viability, and a return on assets between 12% and 22%. Net present value (NPV) was positive for all RSDFs except one; however, in every case, NPV was lower than the opening asset value. Under current economic and policy conditions, RSDFs in the highlands of Mexico appear economically and financially viable through 2033. Family labor was associated with stronger economic and financial outcomes among the small-scale dairy farms evaluated. Full article

This study explores the role of decentralized physical infrastructure networks (DePINs) in enhancing solar energy forecasting, focusing on how network density influences prediction accuracy and economic viability. Using machine learning models applied to production data from 47 residential PV systems in Utrecht, Netherlands, we developed a hierarchical forecasting framework: Level 1 (clear-sky baseline without historical data), Level 2 (solo forecasting using only local historical data), and Level 3 (networked forecasting incorporating data from neighboring installations). The results show that networked forecasting substantially improves accuracy: under solo forecasting conditions (Level 2), the Random Forests model reduces Mean Absolute Error (MAE) by 17% relative to the Level 1 baseline, and incorporating all available neighbors (Level 3) further reduces the MAE by an additional 34% relative to Level 2, corresponding to a total improvement of 45% compared with Level 1. The largest accuracy gains arise from the first 10–15 neighbors, highlighting the dominant influence of local spatial correlations. These forecasting improvements translate into significant economic benefits. Imbalance costs decrease from EUR 1618 at Level 1 to EUR 1339 at Level 2 and further to EUR 884 at Level 3, illustrating the financial impact of both solo and networked data sharing. A marginal benefit analysis reveals diminishing returns beyond approximately 10–15 neighbors, consistent with spatial saturation effects within 5–10 km radii. These findings provide a quantitative foundation for incentive mechanisms in DePIN ecosystems and demonstrate that privacy-preserving data sharing mitigates data fragmentation, reduces imbalance costs for energy traders, and creates new revenue opportunities for participants, thereby supporting the development of decentralized energy markets. Full article

Solar energy systems have increasingly replaced conventional energy systems, driving global efforts to combat climate change and promote sustainability. This study conducts a comprehensive life-cycle cost analysis (LCCA) of photovoltaic (PV) modules, with a focus on the solar market in Eskisehir, Türkiye. Unlike prior research, this work integrates financial analysis with ecological benefits, offering a localized case study. By leveraging primary data from surveys and government sources, the analyses display that investing in PV equipment generates €883.75 in Net Present Value (NPV) savings through the business-as-usual scenario (−€392 under the worst-case and €2350 under the optimistic scenarios) over a 30-year lifespan, demonstrating the financial viability of these systems. Despite high initial costs, PV modules provide ecological and economic advantages that outweigh maintenance expenses, making them a viable solution for reducing fossil fuel dependence. The findings serve as a guideline for decision-makers, consumers, and producers to foster a sustainable solar energy market in Türkiye and similar developing economies by enabling feasible PV investments through appropriate Feed-in tariff mechanisms. Full article

This paper investigates how the existing pellet plant of the Energy Community of Karditsa (ESEK) can be leveraged to strengthen RESCoop operations by integrating a variety of biomass feedstocks as (i) urban residual biomass, (ii) forest residues, and (iii) alternative sources such as spent coffee grounds (SCGs). The RESCoop envisions an extended role as an Energy Service Company (ESCO) by installing and operating biomass boilers in local public buildings. The paper provides an overview of the technical and business support that was provided to the RESCoop for the development of such new business activities and aggregates the lessons learned from engaging the rural society towards sustainable bioenergy production. More specifically, the study covers the logistical aspects of the new RESCoop value chains, including availability, collection, transportation, and processing of the feedstocks along with their costs. A base case scenario investigates the feasibility of installing biomass boilers in municipal buildings through a detailed financial viability study examining capital and operational expenses, revenues, and key financial indicators. Further, the environmental and socio-economic impacts of the new RESCoop activities are evaluated in terms of CO₂ equivalent savings compared to fossil fuel solutions and new job creation, respectively. This detailed analysis highlights the potential for sustainable bioenergy integration and provides valuable insights for similar initiatives aiming to diversify and enhance sustainable energy practices in local communities. Full article

In recent years, the rapid increase in installed photovoltaic (PV) capacity in Poland has created significant challenges for low-voltage distribution networks. Excess generation during peak solar hours frequently leads to local overvoltage conditions that exceed regulatory limits, causing PV inverters to disconnect from the grid. This phenomenon reduces the efficiency of distributed renewable energy integration and results in direct financial losses for prosumers. The present study quantifies these losses on an annual basis for a single-family household located in southeastern Poland, where overvoltage incidents occurred 614 times over 78 days in 2024. Real operational data from the residential PV installation were analyzed and complemented with detailed PVsyst simulations to determine the amount of energy curtailed due to inverter disconnections. The analysis revealed that daily energy losses can reach up to 22% of potential production, depending on the duration and frequency of overvoltage events. Furthermore, several technical and organizational measures are proposed to mitigate the issue, including grid reinforcement strategies and demand-side management. The findings highlight the necessity of addressing overvoltage in low-voltage distribution networks to ensure system reliability, enhance renewable energy integration, and maintain the economic viability of residential PV investments. Full article

Background: Agricultural production plays a vital role in the global economy by integrating different sectors and promoting capital circulation across industries. In this context, the dairy sector emerges as a promising avenue for investment. This study aims to assess the economic feasibility of establishing a dairy plant for the production of parmesan and mozzarella cheeses in Lavras, MG, considering both deterministic and probabilistic scenarios. Methods: The analysis was conducted in three stages: data collection, deterministic economic feasibility analysis using traditional financial indicators (NPV, IRR, profitability rate, and payback), and a probabilistic assessment using the Monte Carlo simulation with 100,000 iterations to incorporate uncertainty into the model. Results: The deterministic results indicated a positive Net Present Value (NPV), Internal Rate of Return (IRR) exceeding the Minimum Attractiveness Rate (MAR), and a profitability rate above 1.5, validating the investment’s viability. The probabilistic analysis reinforced these findings, with over 80% of simulated scenarios resulting in a positive NPV and over 77% showing IRR above the MAR. Key variables influencing profitability included market share, Class AB cheese consumer percentage, parmesan markup, operational costs, and per capita cheese consumption. Conclusions: The study confirms the economic feasibility of implementing the proposed dairy plant. The integration of Monte Carlo Simulation enhanced the robustness of the analysis by accounting for uncertainty, providing valuable insights for strategic decision-making. The project presents strong potential for regional development, job creation, and income generation. Full article