Search Results (276)

With the rapid development of energy transformation, the proportion of new energy is increasing, and the efficient trading mechanism of multi-microgrids can realize energy sharing to improve the consumption rate of new energy. A distributed multi-microgrid cooperative energy sharing strategy is proposed based on Nash bargaining. Firstly, by comprehensively considering the adjustable heat-to-electrical ratio, ladder-type positive and negative carbon trading, peak–valley electricity price and demand response, a multi-microgrid system with wind–solar-storage-load and combined heat and power is constructed. Then, a multi-microgrid cooperative game optimization framework is established based on Nash bargaining, and the complex nonlinear problem is decomposed into two stages to be solved. In the first stage, the cost minimization problem of multi-microgrids is solved based on the alternating direction multiplier method to maximize consumption rate and protect privacy. In the second stage, through the established contribution quantification model, Nash bargaining theory is used to fairly distribute the benefits of cooperation. The simulation results of three typical microgrids verify that the proposed strategy has good convergence properties and computational efficiency. Compared with the independent operation, the proposed strategy reduces the cost by 41% and the carbon emission by 18490kg, thus realizing low-carbon operation and optimal economic dispatch. Meanwhile, the power supply pressure of the main grid is reduced through energy interaction, thus improving the utilization rate of renewable energy. Full article

To remain competitive in the decarbonization process of the economy worldwide, energy companies must preserve their market value to attract new investors and remain resilient throughout the transition to net zero. This article examines the market value of US energy companies during the period 2012–2024 in relation to their power generation mix. Panel regression analyses reveal that Tobin’s q and price-to-book ratios increase significantly for solar and wind power, while they experience moderate increases for natural gas power. In contrast, Tobin’s q and price-to-book ratios decline for nuclear and coal power. Furthermore, accounting-based profitability, measured by the return on assets (ROA), does not show significant variation with any type of power generation. The findings suggest that market investors prefer solar, wind, and natural gas power generation, thereby attributing greater value (that is, demanding lower risk compensation) to green companies compared to traditional ones. These insights provide guidance to executives, investors, and policy makers on how the power generation mix can influence strategic decisions in the energy sector. Full article

Demand Side Management (DSM) plays a crucial role in modern energy systems, enabling more efficient use of energy resources and contributing to the sustainability of the power grid. This study examines DSM strategies within a multi-environment context encompassing residential, commercial, and industrial sectors, with a focus on diverse appliance types that exhibit distinct operational characteristics and user preferences. Initially, a single-objective optimization approach using Genetic Algorithms (GAs) is employed to minimize the total energy cost under a real Time-of-Use (ToU) pricing scheme. This heuristic method allows for the effective scheduling of appliance operations while factoring in their unique characteristics such as power consumption, usage duration, and user-defined operational flexibility. This study extends the optimization problem to a multi-objective framework that incorporates the minimization of CO₂ emissions under a real annual energy mix while also accounting for user discomfort. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is utilized for this purpose, providing a Pareto-optimal set of solutions that balances these competing objectives. The inclusion of multiple objectives ensures a comprehensive assessment of DSM strategies, aiming to reduce environmental impact and enhance user satisfaction. Additionally, this study monitors the Peak-to-Average Ratio (PAR) to evaluate the impact of DSM strategies on load balancing and grid stability. It also analyzes the impact of considering different periods of the year with the associated ToU hourly schedule and CO₂ emissions hourly profile. A key innovation of this research is the integration of detailed, category-specific metrics that enable the disaggregation of costs, emissions, and user discomfort across residential, commercial, and industrial appliances. This granularity enables stakeholders to implement tailored strategies that align with specific operational goals and regulatory compliance. Also, the emphasis on a user discomfort indicator allows us to explore the flexibility available in such DSM mechanisms. The results demonstrate the effectiveness of the proposed multi-objective optimization approach in achieving significant cost savings that may reach 20% for industrial applications, while the order of magnitude of the trade-offs involved in terms of emissions reduction, improvement in discomfort, and PAR reduction is quantified for different frameworks. The outcomes not only underscore the efficacy of applying advanced optimization frameworks to real-world problems but also point to pathways for future research in smart energy management. This comprehensive analysis highlights the potential of advanced DSM techniques to enhance the sustainability and resilience of energy systems while also offering valuable policy implications. Full article

With the proposal of China’s “dual carbon” goal, the carbon market has become a vital tool for controlling carbon emissions. This study constructs a system dynamics model encompassing carbon trading, the economy, energy, population, and the environment, and conducts simulation analysis against the backdrop of China’s national carbon market’s implementation. The results indicate that the implementation of China’s national carbon market significantly promotes carbon emissions reduction, albeit at the cost of some economic development in the short term. However, the suppressive effect of the carbon market on carbon emissions is stronger than its negative impact on economic growth. The effects of carbon reduction strengthen with increases in carbon price, quota auction, CCER price, penalty severity, and the quota reduction rate and weaken with a higher CCER offset ratio. A moderate reduction in the tightening quota reduction rate is more conducive to achieving coordinated development across the multiple objectives of carbon reduction, economic development, and energy structure. Under the constraints of multiple objectives involving carbon reduction, economic development, and energy structure, the reasonable range for carbon prices is between CNY 77.9 and CNY 118.9 per ton, with the maximum quota auction of 23.4%. Additionally, the reasonable range for the quota reduction rates is between 0.84% and 2.18%, with the penalty severity set at 7. Full article

This study presents a detailed and comprehensive investigation into the macro-scale performance, strength gain mechanisms, environment and economic performance of graphene oxide (GO)-enhanced low-emission concrete. A comprehensive experimental program evaluated fresh and hardened properties, including slump retention, bleeding, air content, compressive, flexural, and tensile strength, drying shrinkage, and elastic modulus. Scanning Electron Microscopy (SEM), energy-dispersive spectroscopy (EDS), Thermogravimetric analysis (TGA) and proton nuclear magnetic resonance (¹H-NMR) was employed to examine microstructural evolution and early age water retention, confirming GO’s role in accelerating cement hydration and promoting C-S-H formation. Optimal performance was achieved at 0.05% GO (by binder weight), resulting in a 25% increase in 28-day compressive strength without compromising workability. This outcome is attributed to a tailored, non-invasive mixing strategy, wherein GO was pre-dispersed during synthesis and subsequently blended without the use of invasive mixing methods such as high shear mixing or ultrasonication. Fourier-transform infrared (FTIR) spectroscopy further validated the chemical compatibility of GO and PCE and confirmed the compatibility and efficiency of the admixture. Sustainability metrics, including embodied carbon and strength-normalized cost indices (USD/MPa), indicated that, although GO increased material cost, the overall cost-performance ratio remained competitive at breakeven GO prices. Enhanced efficiency also led to lower net embodied CO₂ emissions. By integrating mechanical, microstructural, and environmental analyses, this study demonstrates GO’s multifunctional benefits and provides a robust basis for its industrial implementation in sustainable infrastructure. Full article

Against the backdrop of increasingly severe global climate change, the automotive industry, as a carbon-intensive sector, has found its low-carbon transformation crucial for achieving the “double carbon” goals. This paper constructs manufacturer decision-making models under an oligopolistic market scenario for the single dual-credit policy and the “dual-credit + carbon cap-and-trade” policy, revealing the nonlinear impacts of new energy vehicle (NEV) credit trading prices, carbon trading prices, and credit ratio requirements on manufacturers’ pricing, emission reduction effort levels, and profits. The results indicate the following: (1) Under the “carbon cap-and-trade + dual-credit” policy, manufacturers can balance emission reduction costs and NEV production via the carbon trading market to maximize profits, with lower emission reduction effort levels than under the single dual-credit policy. (2) A rise in credit trading prices prompts hybrid manufacturers (producing both fuel vehicles and NEVs) to increase NEV production and reduce fuel vehicle output; higher NEV credit ratio requirements raise fuel vehicle production costs and prices, suppressing consumer demand. (3) An increase in carbon trading prices raises production costs for both fuel vehicles and NEVs, leading to decreased market demand; hybrid manufacturers reduce emission reduction efforts, while others transfer costs through price hikes to boost profits. (4) Hybrid manufacturers face high carbon emission costs due to excessive actual fuel consumption, driving them to enhance emission reduction efforts and promote low-carbon technological innovation. Full article

In the context of the intensifying global climate crisis, the power industry, as a significant carbon emitter, urgently needs to promote low-carbon transformation using market mechanisms. In this paper, a multi-objective stochastic optimization scheduling framework for regional power grids integrating carbon trading (CET) and green certificate trading (GCT) is proposed to coordinate the conflict between economic benefits and environmental objectives. By building a deterministic optimization model, the goal of maximizing power generation profit and minimizing carbon emissions is combined in a weighted form, and the power balance, carbon quota constraint, and the proportion of renewable energy are introduced. To deal with the uncertainty of power demand, carbon baseline, and the green certificate ratio, Monte Carlo simulation was further used to generate random parameter scenarios, and the CPLEX solver was used to optimize scheduling schemes iteratively. The simulation results show that when the proportion of green certificates increases from 0.35 to 0.45, the proportion of renewable energy generation increases by 4%, the output of coal power decreases by 12–15%, and the carbon emission decreases by 3–4.5%. At the same time, the tightening of carbon quotas (coefficient increased from 0.78 to 0.84) promoted the output of gas units to increase by 70 MWh, verifying the synergistic emission reduction effect of the “total control + market incentive” policy. Economic–environmental tradeoff analysis shows that high-cost inputs are positively correlated with the proportion of renewable energy, and carbon emissions are significantly negatively correlated with the proportion of green certificates (correlation coefficient −0.79). This study emphasizes that dynamic adjustments of carbon quota and green certificate targets can avoid diminishing marginal emission reduction efficiency, while the independent carbon price mechanism needs to enhance its linkage with economic targets through policy design. This framework provides theoretical support and a practical path for decision-makers to design a flexible market mechanism and build a multi-energy complementary system of “coal power base load protection, gas peak regulation, and renewable energy supplement”. Full article

This study analyzes the configurations and control strategies of hybrid heating systems of air-source heat pumps (ASHPs) and gas boilers for space heating in different climatic regions in China, with the aim of improving the comprehensive energy efficiency. Parallel and series hybrid modes were proposed, and simulation analysis was conducted to analyze the energy performance, energy costs, and CO₂ emissions of different hybrid systems. The results show that the supply water temperatures of ASHPs in series mode are lower than that of ASHPs in parallel mode; thus, the COP of ASHPs in series mode reached 2.73 and was higher than the COP of ASHPs in parallel mode with a value of 2.65. Then, the optimal intermediate temperatures of hybrid system in series mode were analyzed, so as to guide the system control. The results show that compared with series mode with a fixed 50% load distribution, the operational costs and CO₂ emissions were reduced by 10.0% and 10.4% in Harbin, reduced by 6.4% and 8.3% in Beijing, and reduced by 10.0% and 15.1% in Wuhan. Additionally, the optimal intermediate temperature was affected by the building load ratio, supply water temperature, ambient air temperature, and the electricity–gas price ratio. The series-hybrid ASHP and gas boiler system achieves remarkable energy and cost savings across different climatic conditions, providing a scientific basis for promoting low-carbon heating solutions. Full article

Given the widespread use of gas-fired boilers and combined heat and power (CHP) units in existing district heating (DH) systems, this study investigates the integration of medium-scale heat pumps (HPs) into such configurations. Fifteen DH system variants were analysed, differing in installed HP capacity, operational strategies, and the synchronisation of heat and electricity production with thermal demand. A dynamic simulation model incorporating real-world equipment performance was developed to assess energy efficiency, environmental impact, and economic viability under three distinct energy price scenarios. The results demonstrate that an HP sized to 17% of the total heating capacity of the DH system achieves a 54% decrease in primary energy consumption and a 68% decrease in emissions compared to the base system. Larger HP capacities enhance environmental performance and increase the share of renewable energy but also entail higher investment. An economic analysis reveals that electricity-to-gas price ratios strongly influence the cost-effectiveness of HP integration. Under favourable electricity pricing conditions, systems with HP operational priority achieve the lowest levelized cost of heating. The most economically viable configuration consists of 600 kW HP and achieves a payback period of 4.7 years. The findings highlight the potential for HPs to decarbonize DH systems while emphasising the importance of market conditions and system design in ensuring economic feasibility. Full article

Building-integrated photovoltaic (BIPV) systems coupled with energy storage systems offer promising solutions to reduce the dependency of buildings on non-renewable energy sources and provide the building sector with environmental benefits by reducing the buildings’ environmental footprint. Hence, the economic viability of such energy systems must be further assessed, particularly regarding the market price and required initial investments. This paper aims to evaluate the net present cost (NPC) and saving-to-investment ratio (SIR) of the electrical storage system coupled with BIPV in smart residential buildings with a focus on optimum sizing of the battery systems under varying market price scenarios. Therefore, a parametric energy model of a residential building, a life cycle cost analysis approach, and a Monte Carlo analysis are carried out to elaborate the dynamism between the storage size, market price, and net present cost of the system over its life cycle. The results provide a decision-support tool to find the cost-optimum size of the battery systems and to realize the interplay between the battery system size, the market price, and the economic feasibility of the electrical storage system coupled with residential BIPV. In more detail, the results reveal that the economic viability thresholds of the battery systems’ market price are in the range of 250–300 €/kWh depending on the chosen life cycle cost indicators, while the cost-optimum size of the battery systems varies noticeably according to the market price of battery systems. Furthermore, the paper provides insight to designers, policymakers, manufacturers, and the market for developing scenarios to accelerate the implementation of energy storage systems in the building sector. Full article

This paper presents SEAMS (Solar Energy Aggregator Management System), an optimization-based framework for managing solar energy trading in smart communities under Thailand’s regulatory constraints. A major challenge is the prohibition of residential grid feed-in, which limits the use of conventional peer-to-peer energy models. Additionally, fixed pricing is required to ensure simplicity and trust among users. SEAMS coordinates prosumer and consumer households, a shared battery energy storage system (BESS), and a centralized aggregator (AGG) to minimize total electricity costs while maintaining financial neutrality for the aggregator. A mixed-integer linear programming (MILP) model is developed to jointly optimize PV sizing, BESS capacity, and internal buying price, accounting for Time-of-Use (TOU) tariffs and local policy limitations. Simulation results show that a 6 kW PV system and a 70–75 kWh shared BESS offer optimal performance. A 60:40 prosumer-to-consumer ratio yields the lowest total cost, with up to 49 percent savings compared to grid-only systems. SEAMS demonstrates a scalable and policy-aligned approach to support Thailand’s transition toward decentralized solar energy adoption and improved energy affordability. Full article

As an essential platform for aggregating and coordinating distributed energy resources (DERs), the virtual power plant (VPP) has attracted widespread attention in recent years. With the increasing scale of VPPs, energy interaction and sharing among VPP clusters (VPPCs) have become key approaches to improving energy utilization efficiency and reducing operational costs. Therefore, studying the coordinated operation mechanism of VPPCs is of great significance. This paper proposes a two-stage coordinated operation model for VPPCs based on energy interaction to enhance the overall economic performance and coordination of the cluster. In the day-ahead stage, a cooperative operation model based on Nash bargaining theory is constructed. The inherently non-convex and nonlinear problem is decomposed into a cluster-level benefit maximization subproblem and a benefit allocation subproblem. The Alternating Direction Method of Multipliers (ADMM) is employed to achieve distributed optimization, ensuring both the efficiency of coordination and the privacy and decision independence of each VPP. In the intra-day stage, to address the uncertainty in renewable generation and load demand, a real-time pricing mechanism based on the supply–demand ratio is designed. Each VPP performs short-term energy forecasting and submits real-time supply–demand information to the coordination center, which dynamically determines the price for the next trading interval according to the reported imbalance. This pricing mechanism facilitates real-time electricity sharing among VPPs. Finally, numerical case studies validate the effectiveness and practical value of the proposed model in improving both operational efficiency and fairness. 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

This study examines housing affordability trends in Central Europe, focusing on the Czech Republic, Slovakia, Austria, and Poland, in the wake of recent global disruptions including the COVID-19 pandemic, the 2021–2022 energy crisis, and the war in Ukraine. These events have intensified housing affordability challenges by driving up property prices, rental costs, and energy expenses. Using data from December 2022 to March 2023, the paper analyzes wage levels relative to housing costs in major cities—Prague, Brno, Bratislava, Vienna, Graz, Warsaw, and Kraków—through price-to-income and rent-to-income ratios. The findings reveal that affordability is most strained in Czech cities, particularly Prague, where property prices outpace wages, while Vienna demonstrates better affordability due to higher average incomes. The study integrates real estate platform data with official statistics and employs spatial mapping and exploratory econometric testing to identify affordability patterns and disparities. It concludes that affordability outcomes are shaped by wage dynamics, housing supply constraints, migration pressures, and policy responses. The study underscores the importance of targeted housing policies and wage interventions to address these challenges and highlights the need for cross-country policy learning and regional coordination to improve housing affordability and market resilience across Central Europe. Full article

The development of renewable energy in the power industry plays a crucial role in mitigating environmental degradation. The renewable energy (RE) consumption system and green certificate trading market are significant in promoting renewable energy adoption, while energy storage technology has advanced substantially to address power supply instability. Against this backdrop, this study employs a Stackelberg game approach to construct a power supply chain model, with generation companies as leaders and retail companies as followers, examining energy storage cost-sharing mechanisms and retailers’ renewable energy investment decisions. Key findings include the following: (1) a higher RE consumption ratio reduces wholesale prices, power stability, electricity demand, and retailers’ renewable investment; (2) when the energy storage cost coefficient exceeds a threshold, higher green certificate prices increase retailers’ renewable investment; (3) beyond the threshold, a higher RE consumption ratio incentivizes retailers to invest in renewables; (4) proportional cost sharing enhances renewable investment by approximately 15% and maximizes supply chain profits. The study provides decision-making insights for power companies and policy references for governments. Full article