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Through extensive data research and analysis, this paper comprehensively summarizes the status and key insights of global carbon dioxide capture and storage (CCS) development. It aims to gain a comprehensive understanding of the relevant policies, technologies, and security measures adopted by major countries in their CCS development processes. Furthermore, it explores the existing status and limitations of China's offshore development efforts, while providing valuable recommendations for enhancing China's offshore CCS initiatives, as well as serving as a reference for other nations worldwide. Offshore CCS plays a crucial role for China to achieve the development target of carbon peak and carbon neutrality, due to its energy structure and industrial distribution. While China possesses significant offshore CCS potential, achieving commercialization still requires substantial efforts. To facilitate the process and draw insights from successful experiences in other countries, this paper illustrates the characteristics and generalizes the experience of offshore CCS industry practices in America, Europe and Japan, respectively. Furthermore, it is recommended that a new round of investigation into offshore CCS potential be conducted, while promoting integrated collaboration between geological surveying and marine scientific research. Additionally, further research on industrial policies and green financial strategies should be undertaken. [ABSTRACT FROM AUTHOR]

The power sector is one of the major CO2-emitting industries in China. It is also the first key emissions control industry included in China's national carbon trading market established in 2021. Therefore, based on the data of 30 provinces and cities in China from 2015 to 2022, this study analyzes the impact of the national carbon market policy on the carbon emissions of the power industry based on the generalized Difference-in-Difference (DID) model. Based on the method of text analysis, this paper constructs the carbon market policy intensity index of each region and incorporates it into the DID model. Empirical analysis finds that the national carbon market policy can significantly inhibit the carbon emissions of the power industry. However, the heterogeneity analysis of 30 provinces and cities shows that the national carbon market policy has a significant impact on the regions that already have a carbon pilot, but not on the non-pilot regions. Therefore, this paper demonstrates the effectiveness of the national carbon market policy in the power industry emissions control, and also exposes the heterogeneity between regions, providing an important empirical basis for the inclusion of other energy-intensive industries. [ABSTRACT FROM AUTHOR]

Low carbon operation of power systems is a key way to achieve the goal of energy power carbon peaking and carbon neutrality. In order to promote the low carbon transition of energy and power and the coordinated and optimized operation of distributed energy sources in virtual power plants (VPP), this paper proposes a framework for collaborative utilization of pumped storage–carbon capture–power-to-gas (P2G) technologies. It also constructs a multi-time scale low carbon economic dispatch model for VPP to minimize the internal resource operation cost of VPP in each time period. During the intraday scheduling stage, the day-ahead scheduling results as the planned output and the energy flow is then dynamically corrected at a short-term resolution in the framework. This allows for the exploration of the low-carbon potential of each aggregation unit within the virtual power plant. The results of the simulation indicate that the strategy and model proposed in this paper can effectively encourage the consumption of renewable energy sources, promote the low-carbon operation of power system power, and serve as a valuable reference for the low-carbon economic operation of the power system. [ABSTRACT FROM AUTHOR]

With the development of global clean energy and the implementation of carbon emission reduction policies, the direct purchase of electricity by large consumers has been increasingly promoted as a special form of electricity trading. Therefore, on the basis of the completion of low-carbon emission reduction targets in each country, how to rationalize the electricity purchase by large consumers in the electricity market so as to reduce their electricity purchase costs has become the main target of attention in each country. Currently, there are fewer studies in existing research on the direct electricity purchase strategy of large consumers under the consideration of the weight of consumption responsibility and risk. Based on this, this paper constructs a dual-game model for direct electricity purchase by large consumers based on the Stackelberg game and non-cooperative game theory. The concept of value at risk is further introduced, and the optimal strategy of direct electricity purchase by large consumers is proposed. The results of this study show that when market players make decisions on the purchase and sale of electricity, power suppliers will increase their biddings to obtain the highest returns, and large consumers can reduce the transaction costs by combining the medium- and long-term market with the spot market to purchase electricity. In the choice of electricity purchase market, with the increasing risk factor, large consumers shift from the risky spot market to the less risky medium- and long-term market and option market. This paper provides a reference for the issues of power suppliers' contract bidding and large consumers' electricity purchase strategy in the medium- and long-term contract transactions. [ABSTRACT FROM AUTHOR]

Cities play a pivotal role in achieving worldwide carbon neutrality due to their significant contribution to global energy consumption and carbon emissions. Therefore, planning effective strategies and guiding evidence-based policymaking at the city scale becomes even more crucial. Composite indices serve as a valuable tool for monitoring urban energy transition trends. This paper aims to present a novel approach, robust and flexible even under conditions of data scarcity, for tracking the energy transition trend of a city by means of a composite index (UETI). The Turin case study is introduced to test the applicability of the proposed approach. Additionally, to demonstrate the robustness of the composite index framework, the paper includes the findings of correlation and sensitivity analyses. This study reveals a significant improvement in Turin's environmental and energy domains, while the socio-economic domain shows more modest improvement. Furthermore, the study highlights the need to address the shortage of urban data to enhance the accuracy and reliability of metric-based frameworks and to extend the assessment to a larger sample of cities. [ABSTRACT FROM AUTHOR]

To advance carbon neutrality policies, many countries are increasingly integrating Renewable Energy Sources (RESs) into their energy mix. However, for harnessing natural energy in power generation, RESs present challenges in output control, potentially leading to power imbalances. Such imbalances, when coupled with an excessive reliance on unpredictable RES, may necessitate the curtailment of grid-integrated renewable generation, halting production despite available capacity. This paper proposes strategies to mitigate the economic and operational efficiency impacts of increased RESs on the power grid. It focuses on the optimal operation of Battery Energy Storage Systems (BESSs) and Power to Gas (P2G) technology, which flexibly converts surplus electricity into hydrogen. By employing Mixed Integer Linear Programming (MILP) for optimization and Stochastic Programming (SP) for the management of the uncertainty of renewable energy output, this paper evaluates the anticipated benefits of BESS and P2G applications. [ABSTRACT FROM AUTHOR]

In order to achieve the ambitious goal of "carbon neutrality", countries around the world are striving to develop clean energy. Against this background, this paper takes China and Italy as representatives of developing and developed countries to summarize the energy structure composition and development overview of the two countries. The paper analyzes the serious challenges facing the future energy development of both countries and investigates the possibilities of energy cooperation between the two countries, taking into account their respective advantages in energy development. By comparing the policies issued by the two governments to encourage clean energy development, this paper analyzes the severe challenges faced by the two countries' energy development in the future and combines their respective energy development advantages to look forward to the possibility of energy cooperation between the two countries in the future. This lays the foundation for China and Italy to build an "Energy Road" after the "Silk Road". [ABSTRACT FROM AUTHOR]

The sustainable implementation of resources and the transition to low-carbon construction is on the world's daily agenda. This paper describes the development of criteria for the efficient management of material resources in low-carbon construction. Net income, gross profit, balance sheets, and equity are proposed as indicators that serve as criteria for assessing the efficient use of resources. Nonlinear regression models were the methodological basis for the establishment of cause-and-effect relationships of the volume of construction of transport structures. It was established that since construction companies do not purchase materials for storage, the cost of materials for use in low-carbon technological construction work is directly proportional to the cost of construction. The volume of production in the construction industry is determined by construction costs. More efficient use of low-carbon materials reduces cost and construction waste. In this paper, we have established the relationship between the indicator of efficiency for the functioning of the construction enterprises in Ukraine and the use of low-carbon materials for the construction of transport structures. The practical value of the obtained results for low-carbon construction management lies in proving the relationship between the performance indicators of the construction enterprise (net profit, gross profit, output volume, balance sheets, and equity capital) and the use of low-carbon material resources. Our results form the basis for future research into the use of a cost-based model for low-carbon economy transition in municipalities and regions. [ABSTRACT FROM AUTHOR]

Recently, there has been an increasing effort to promote energy efficiency, using renewable energies and electric mobility to achieve a more sustainable future and even carbon neutrality by 2050. This paper aims to understand if combining these technologies leads to a win–win solution. For that, the system's characteristics that will be used for the simulation were defined as a residential community consumption scenario with and without electric vehicles charging overnight. The simulation was completed in software, and eight scenarios were tested: high population density/low population density with/without electric mobility and hourly tariff/simple tariff. After these scenarios had been tested, the conclusion was that the low population density and hourly tariff without and with electric mobility were the best two cases economically (in terms of levelized cost of energy, net present costs, and savings) and environmentally, and the worst was high population density with hourly tariff and electric mobility. Other scenarios were then tested, including changes in the load curve, namely a commercial load curve, and changes in the load curve of electric vehicle chargers, mainly daytime charging. The conclusion was that even though the initial hypothesis did not lead to a win–win solution, with changes in the hypothesis, the integration of electric mobility in energy communities might lead to that. [ABSTRACT FROM AUTHOR]

With the shortage of fossil energy and the increasingly serious environmental problems, renewable energy based on wind and solar power generation has been gradually developed. For the problem of wind power uncertainty and the low-carbon economic optimization problem of an integrated energy system with power to gas (P2G) and carbon capture and storage (CCS), this paper proposes an economic optimization scheduling strategy of an integrated energy system considering wind power uncertainty and P2G-CCS technology. Firstly, the mathematical model of the park integrated energy system with P2G-CCS technology is established. Secondly, to address the wind power uncertainty problem, Latin hypercube sampling (LHS) is used to generate a large number of wind power scenarios, and the fast antecedent elimination technique is used to reduce the scenarios. Then, to establish a mixed integer linear programming model, the branch and bound algorithm is employed to develop an economic optimal scheduling model with the lowest operating cost of the system as the optimization objective, taking into account the ladder-type carbon trading mechanism, and the sensitivity of the scale parameters of P2G-CCS construction is analyzed. Finally, the scheduling scheme is introduced into a typical industrial park model for simulation. The simulation result shows that the consideration of the wind uncertainty problem can further reduce the system's operating cost, and the introduction of P2G-CCS can effectively help the park's integrated energy system to reduce carbon emissions and solve the problem of wind and solar power consumption. Moreover, it can more effectively reduce the system's operating costs and improve the economic benefits of the park. [ABSTRACT FROM AUTHOR]

Sewage sludge and red mud, as common industrial waste, have become a research hotspot in the field of achieving carbon peaking and carbon neutrality, reducing carbon emissions, and solving environmental problems. However, their treatment and disposal have always been a difficult problem in the environmental field. Utilizing these two materials for thermal energy storage can not only improve energy utilization efficiency but also further reduce carbon emissions during their treatment process, providing a new approach for sustainable development in the industrial sector. This article summarizes the research progress for the resource recovery of sewage sludge and red mud for direct thermal energy recovery and composite phase change energy storage. After proper treatment, sludge and red mud can be directly used as energy storage materials. In addition, sludge and red mud can be combined with phase change materials to prepare composite materials with an excellent energy storage performance. This composite has broad application prospects in fields such as solar energy utilization and building energy efficiency. However, there are still some challenges and issues in this resource recovery and utilization, such as potential environmental pollution during the treatment process, the long-term stability of energy storage materials, and cost-effectiveness, which require further research and resolution. The purpose of this paper is to evaluate the potential of sewage sludge and red mud as energy storage materials, to explore their feasibility and advantages in practical applications, and to reveal the research progress, technical challenges, and future development directions of these two materials in the field of thermal energy storage. [ABSTRACT FROM AUTHOR]

Assessments of the hosting capacity of electricity distribution networks are of paramount importance, as they facilitate the seamless integration of rooftop photovoltaic systems into the grid, accelerating the transition towards a more carbon neutral and sustainable system. This paper employs a deep reinforcement learning-based approach to evaluate the real-time hosting capacity of low voltage distribution networks in a model-free manner. The proposed approach only requires real-time customer voltage data and solar irradiation data to provide a fast and accurate estimate of real-time hosting capacity at each customer connection point. This study addresses the imperative for accurate electrical models, which are frequently unavailable, in evaluating the hosting capacity of electricity distribution networks. To meet this challenge, the proposed approach utilizes a deep neural network-based, data-driven model of a low-voltage electricity distribution network. This proposed methodology incorporates model-free elements, enhancing its adaptability and robustness. In addition, a comparative analysis between model-based and model-free hosting capacity assessment methods is presented, highlighting their respective strengths and weaknesses. The utilization of the proposed hosting capacity estimation model enables distribution network service providers to make well-informed decisions regarding grid planning, leading to cost minimization. [ABSTRACT FROM AUTHOR]

With a significant share of renewable power generation integrated into the power supply, it is crucial to timely adjust the regulating peak load for coal-fired power plants equipped with CO2 capture to ensure the stable operation of the multi-energy supply system. In this paper, the effects of varying boiler loads on the techno-economic performance of the retrofitted power plant were studied. Furthermore, the potential for reducing the cost of CO2 capture was investigated, and early opportunities for demonstration were discussed. Results showed that when the boiler load decreased from 100% turbine heat acceptance condition to 50% turbine heat acceptance condition, the cost of CO2 capture increased from 37.0 $/t CO2 to 57.0 $/t CO2, cost contribution of energy penalty and extra capital investment also increased from 20.6 $/t-CO2 to 25.7 $/t-CO2, and from 16.4 $/t-CO2 to 31.3 $/t-CO2, respectively. Furthermore, by improving separation efficiency from 0.15 to 0.5, a 25% to 30% reduction in CO2 capture cost can be achieved. The cost of CO2 capture could decrease by 42.2–50.5% when the cumulative capacity reaches 250 GW under the high investment learning rate scenario. According to the distribution of coal prices and renewable energy sources in China, the early demonstration projects of multi-energy supply systems should prioritize the northern region. The results of this work can provide informative references for making roadmaps and policies for CO2 emission reduction toward carbon neutrality. [ABSTRACT FROM AUTHOR]

The use of renewable energy sources to achieve carbon neutrality is increasing. However, the uncertainty and volatility of renewable resources are causing problems in power systems. Flexible and low-carbon resources such as Energy Storage Systems (ESSs) are essential for solving the problems of power systems and achieving greenhouse gas reduction goals. However, ESSs are not being installed because of Korea's fuel-based electricity market. To address this issue, this paper presents a method for determining the optimal investment timing of Battery Energy Storage Systems (BESSs) using the Least Squares Monte Carlo (LSMC) method. A case study is conducted considering the System Marginal Price (SMP) and Capacity Payment (CP), which are electricity rates in Korea. Revenue is calculated through the arbitrage of a 10 MW/40 MWh lithium-ion BESS, and linear programming optimization is performed for ESS scheduling to maximize revenue. The ESS revenue with uncertainty is modeled as a stochastic process using Geometric Brownian Motion (GBM), and the optimal time to invest in an ESS is determined using an LSMC simulation considering investment costs. The proposed method can be used as a decision-making tool for ESS investors to provide information on facility investments in arbitrage situations. [ABSTRACT FROM AUTHOR]

With the objectives of achieving "peak carbon" and "carbon neutrality", accurately quantifying the carbon emissions of road transportation becomes crucial. It is challenging to accurately describe the energy consumption of vehicles at both temporal and spatial scales from a macro perspective. Therefore, focusing on the quantitative model of vehicle micro energy consumption and road meso energy consumption, this paper reviewed and summarized the energy consumption model of road traffic in terms of data collection, quantification accuracy, and scope of application. Based on this analysis, this paper identifies the challenges of the current road traffic energy consumption model. Finally, we look forward to future research directions for studying quantitative models of energy consumption from road transportation. [ABSTRACT FROM AUTHOR]

The liberalization of energy retail markets empowered consumers with the ability to be part of new emerging entities, such as Citizen Energy Communities. With the increasing penetration of decentralized variable generation, communities have the advantage of incentive local carbon neutrality and sustainability. Local generation reduces transport grid usage and costs to consumers. Furthermore, worldwide legislation incentives energy communities by providing them discounts to other fee parts of the tariff apart from wholesale prices. This paper presents a model of strategic behavior, investment, and trading of energy communities. The model comprises the investment in local renewable generation, the design of competitive tariffs, and strategic bidding on wholesale markets. Consumers have an optimization model that selects the retail tariff that minimizes their costs with energy. These models are tested using data from Portuguese consumers and the Iberian electricity market. Results from the study indicate that inflexible consumers may reduce their costs by 29% by being part of the community. Furthermore, they have the potential to reduce their costs above 50% when using demand–response, adapting themselves to local production and wholesale prices. [ABSTRACT FROM AUTHOR]

Frequency response performance in power systems is becoming vulnerable due to the transition toward the higher penetration of renewable energy such as achieving carbon neutrality. In particular, reducing power system inertia energy as the asynchronous generation increases could result in violating the frequency stability constraint when a disturbance occurs in the power systems. In order to control the rapidly fluctuating frequency of the power system with low inertia, it is necessary to introduce fast frequency response resources such as a Battery Energy Storage System (BESS). This paper proposes a method to calculate the required capacity of BESS for compensating the frequency control performance of the power system using inertia energy. For calculating the required capacity of BESS, the inertia energy in the critical power system, where frequency control performance marginally satisfies frequency stability constraint, should be calculated. Also, the inertia energy in the evaluated power system having deficit inertia energy should be calculated. By comparing power systems that respond with different dynamics when the same disturbance occurs, the proposed calculation corresponds to the ratio of inertia energy deficiency based on critical power system inertia energy within the power imbalance. Through various case studies employing Korean power systems, the effectiveness of the inertia energy-based calculation method for the required BESS is verified by the fact that the BESS integrated power system marginally satisfies the frequency stability constraint. In these study cases, it is found that the instant response of BESS is very effective for compensating the frequency control performance of the low inertia power system. By applying the proposed method, it is also found that about 840 MW of BESS can achieve carbon neutrality in the Korean power system. [ABSTRACT FROM AUTHOR]

This paper presents a quantitative assessment of the value of hydroelectric power plants (HPPs) in power systems with a significant penetration of variable renewable energy sources (VRESs). Through a capacity expansion planning (CEP) model that incorporates a detailed representation of HPP operating principles, the study investigates the construction and application of HPP rule curves essential for seasonal operation. A comparative analysis is also conducted between the proposed rule curve formulation and alternative modeling techniques from the literature. The CEP model optimizes installed capacities per technology to achieve predefined VRES penetration targets, considering hourly granularity and separate rule curves for each HPP. A case study involving twelve reservoir hydropower stations and two open-loop pumped hydro stations is examined, accounting for standalone plants and cascaded hydro systems across six river basins. The study evaluates the additional generation and storage required to replace the hydropower fleet under high VRES penetration levels, assessing the resulting increases in total system cost emanating from introducing such new investments. Furthermore, the study approximates the storage capabilities of HPPs and investigates the impact of simplified HPP modeling on system operation and investment decisions. Overall, the findings underscore the importance of reevaluating hydro rule curves for future high VRES penetration conditions and highlight the significance of HPPs in the energy transition towards carbon neutrality. [ABSTRACT FROM AUTHOR]

Wave energy, as a significant renewable and clean energy source with vast global reserves, exhibits no greenhouse gas or other pollution during real-sea operational conditions. However, throughout the entire lifecycle, wave energy convertors can produce additional CO2 emissions due to the use of raw materials and emissions during transportation. Based on laboratory test data from a wave energy convertor model, this study ensures consistency between the model and the actual sea-deployed wave energy convertors in terms of performance, materials, and geometric shapes using similarity criteria. Carbon emission factors from China, the European Union, Brazil, and Japan are selected to predict the carbon emissions of wave energy convertors in real-sea conditions. The research indicates: (1) The predicted carbon emission coefficient for unit electricity generation ( E F co 2 ) of wave energy is 0.008–0.057 kg CO2/kWh; when the traditional steel production mode is adopted, the E F co 2 in this paper is 0.014–0.059 kg CO2/kWh, similar to existing research conclusions for the emission factor of CO2 for wave energy convertor (0.012–0.050 kg CO2/kWh). The predicted data on carbon emissions in the lifecycle of wave energy convertors aligns closely with actual operational data. (2) The main source of carbon emissions in the life cycle of a wave energy converter, excluding the recycling of manufacturing metal materials, is the manufacturing stage, which accounts for 90% of the total carbon emissions. When the recycling of manufacturing metal materials is considered, the carbon emissions in the manufacturing stage are reduced, and the carbon emissions in the transport stage are increased, from about 7% to about 20%. (3) Under the most ideal conditions, the carbon payback period for a wave energy convertor ranges from 0.28 to 2.06 years, and the carbon reduction during the design lifespan (20 years) varies from 238.33 t CO2 (minimum) to 261.80 t CO2 (maximum). [ABSTRACT FROM AUTHOR]

Several northern European countries have announced ambitious plans to become carbon neutral already before the year 2050. Recent research has, however, highlighted how potential bottlenecks in raw material and resource availability could significantly delay or hinder wind and solar photovoltaic (PV) expansion and continued biomass usage in parts of Europe. To address this issue, this paper assesses how exposed the national energy and climate plans (NECPs) of Finland, Estonia, Germany, Sweden, and Denmark are to resource limitations and techno-economic risks by reviewing and analysing 2030 NECP targets compared to statistical energy use data in these countries. The results indicate that the NECPs of Denmark and Germany are particularly exposed to risks related to global raw material availability, as Denmark plans to rapidly grow the share of wind and solar PV in electricity generation to 81% and 13% by 2030, respectively, followed by Germany, which outlines a 39% and 16% share of wind and solar PV in its national climate strategy. The NECPs of Finland and Germany are also shown to be vulnerable to limitations in biomass availability, as there is a significant disparity between the projected biomass usage and legally binding European Union (EU) targets for land use, land use change, and forestry (LULUCF) sector emissions in 2030 in these countries. [ABSTRACT FROM AUTHOR]

Carbon dioxide, the leading contributor to anthropogenic climate change, is released mainly via fossil fuel combustion, mostly for energy generation. Carbon capture technologies are employed for reducing the emissions from existing huge point sources, along with capturing them from direct air, to reduce the existing concentration. This paper provides a quantitative analysis of the various subtypes of carbon capture technologies with the aim of providing an assessment of each from technological, social, geo-political, economic, and environmental perspectives. Since the emissions intensity and quantity, along with the social–political–economic conditions, vary in different geographic regions, prioritising and finding the right type of technology is critical for achieving ambitious net-zero targets. Four main types of carbon capture technology were analysed (adsorption, absorption, membrane, and cryogenic) under four scenarios depending on the jurisdiction. The Technique for Order of Preference by Similarity to Ideal Solution (also known as the TOPSIS method) was used to establish a quantitative ranking of each, where weightages were allocated according to the emissions status and economics of each depending on the jurisdiction. Furthermore, forecasting the trends for technology types vis à vis carbon neutral targets between 2040 and 2050 was carried out by applying regression analysis on existing data and the emissions footprint of major contributing countries. The study found the membrane score to be the highest in the TOPSIS analysis in three of the four scenarios analysed. However, absorption remains the most popular for post-combustion capture despite having the highest energy penalty per ton of CO2 capture. Overall, capture rates are well short of projections for carbon neutrality; the methodology put forward for prioritising and aligning appropriate technologies and the region-by-region analysis will help highlight to technocrats, governments, and policymakers the state of the art and how to best utilise them to mitigate carbon emissions—critical in achieving the net-zero goals set at various international agreements on climate change. [ABSTRACT FROM AUTHOR]

With the continuous development of global economic and trade activities, environmental problems have become an important factor restricting the sustainable development of all countries. How to realize the coordinated development of international trade and environmental protection has become a major issue facing the international community. Since China joined the WTO, its share of international trade has been increasing continuously. In order to deeply analyze the influence of international carbon emission trading policy on domestic carbon emissions, we use an input–output model and a GTAP analysis method to theoretically calculate the carbon emissions of the international trade of various departments in Shandong Province. At the same time, the implicit carbon emission index of various industries in 2022 is calculated through the direct energy consumption coefficient. The results show that there are significant differences in the impact of the carbon tariff system on different industries. In terms of the carbon emission index, the food processing industry showed a decrease of 18.99 Mt, while the implied carbon emission of the tobacco, textile and leather manufacturing industry reached 30.56 Mt due to the continuous expansion of trade scale. In contrast, the implied carbon emission level of the metal product processing industry reached 5.3 Mt, while the carbon emission of traditional trading industries such as coal mining was almost unaffected by international trade, and its carbon emission index reached the highest level of 5.89 in 2020. In terms of trade impact, high-trade industries such as the food processing industry are significantly affected by the carbon tariff policy, and their share has dropped from 5.89% to 3.95% in the past decade. The carbon emissions generated by GDP growth established by the GTAP model are more convincing. This model can directly reflect the energy efficiency of a region from the side. Based on the present situation of international trade, this paper analyzes the inequality of the current carbon tariff system, and puts forward some policies to optimize the energy structure to reduce carbon emissions and expand domestic demand to reduce the dependence on international trade. Through the GTAP model, we put forward policy suggestions to optimize the energy structure to reduce carbon emissions and the dependence on international trade by expanding domestic demand. [ABSTRACT FROM AUTHOR]

Corporate greenwashing in response to carbon neutrality strategies has received substantial academic attention. Distinct from previous studies, this paper establishes a differential game model incorporating both green and brown enterprise types. The model compares greenness and total profits under two government scenarios: subsidies for green enterprises and the regulation of brown enterprises. It further analyzes the mechanism behind brown enterprise greenwashing formation. The results show that subsidies alone encourage brown enterprises to engage in greenwashing. However, government regulation inhibits such behaviors, with the inhibition effect positively correlated to regulatory intensity. Consumers' green perception of enterprises also significantly drives brown enterprise greenwashing degrees. Higher green enterprise perception coefficients reduce greenwashing, while higher brown enterprise perception coefficients increase it. Differential game and simulation analyses reveal that greenwashing governance should consider both direct policy effects on brown enterprises and indirect subsidy effects on green enterprises. [ABSTRACT FROM AUTHOR]

This paper proposes a practical framework for developing a net-zero electricity mix scenario (NEMS), which considers detailed conditions for supply of each energy. NEMS means a path scenario for power generation amount by year of each generation resource required to achieve carbon neutrality in 2050. NEMS framework refers to a methodological framework that contains procedures and requirements to continuously update the NEMS by comprehensively reflecting policy changes. For evaluation of NEMS, indicators such as a system inertia resource ratio (SIRR) and a fuel conversion rate (FCR) are proposed. The proposed framework and indicators are applied for the 2050 NEMS in Korea's electricity sector. The SIRR, indicating the ratio of inertial resources to total resources, projects values of 49% and 15% for the years 2030 and 2050, respectively. Furthermore, the FCR, reflecting the ratio of fuel conversion for resources undergoing this process, predicts that all targeted resources will have completed conversion by the year 2043. [ABSTRACT FROM AUTHOR]

In pursuit of China's goals for carbon peak and carbon neutrality, wind turbines are continually evolving to achieve a lower levelized cost of energy. The primary technological focus in the wind power industry is on large-scale, lightweight designs for entire turbines to enhance cost competitiveness. However, this advancement has led to an increased risk of blade fractures under extreme operating conditions. This paper addresses this challenging issue by using geometrically exact beam theory to develop a nonlinear simulation model for long, flexible blades. The model accounts for sudden changes in blade properties at the moment of failure, covering both the extensive motions and deformations of the fractured blade. The validation of the proposed model is carried out by comparing the results from power production cases with bladed simulations and further validating the simulations of blade fracture load cases against measurement data. The methodologies and findings presented in this study offer valuable insights for diagnosing faults in wind turbines. [ABSTRACT FROM AUTHOR]

The introduction of distributed generation (DG) into distribution systems is expanding due to carbon neutral policies. DG with intermittent output characteristics brings frequent voltage variations in distribution systems. Generally, a step voltage regulator (SVR) is installed in the long distribution line and controls its voltage, which has limits of stable voltage regulations due to the slow tap-changing rate, switching losses, and short life span. To solve those problems, this paper proposes an IGBT-based SVR using zero-voltage switching. It is verified that the stable operation can be obtained through simulation by PSCAD/EMTDC 4.6 software and empirical experiments. [ABSTRACT FROM AUTHOR]

In order to enhance the carbon emission reduction capability and economy of the microgrid, a capacity optimization configuration method considering laddered carbon trading and demand response is proposed for a grid-connected microgrid consisting of photovoltaic, battery and hydrogen storage devices. Combined with the mathematical model and system structure of each unit in the microgrid, the integrated operation control strategy is determined in this paper. A demand response model containing three load types is developed to reduce the stress on the storage and generation side. A carbon-trading mechanism is introduced into the operating costs to establish a configuration model with annual overall profit and power supply reliability as the optimization objectives. The non-dominated sorting genetic algorithm II is used to optimize the capacity of each unit, and the effectiveness of this model is verified by taking a microgrid in a region in Northwest China as an example to analyze the impacts of ladder carbon trading and demand response on the configuration results and system operation. [ABSTRACT FROM AUTHOR]

Responding to the Paris Agreement and climate change mitigation, Indonesia aims to reach net zero by 2060 or sooner. Due to Indonesia's dependence on coal and growing consumption, alternative sources of clean energy are imperative for meeting its rising energy needs and reducing energy-related greenhouse gas emissions to achieve the energy transition. This project aims to examine Indonesia's opportunities and potential to achieve low carbon ambition in the energy sector and identify alternative pathways for the energy transition in Indonesia. In this study, the open-source energy modelling system (OSeMOSYS), which is a long-term energy system modelling tool, is employed to compare electricity generation, investment, and carbon dioxide emissions between business-as-usual and five alternative scenarios. Six scenarios, including business as usual, least-cost, two coal-phrase out and two net zero aligned with national climate targets and optimal scenarios, were simulated across different target years. The results show that the net zero (NZ) scenario is more cost-effective and emits fewer greenhouse gases than the other scenarios in meeting Indonesia's future energy demand. However, achieving net zero by 2050 (NZ50) results in significantly lower CO2 emissions (10,134 MtCO2), which is less than half of the emissions in the net zero by 2060 (NZ60) scenario (16,849 MtCO2) at a similar cost (6229 and 6177 billion USD, respectively). This paper's insights emphasise that large-scale renewable energy deployment and coal retirement are critical pathways to reaching carbon neutrality and achieving the energy mix transition. [ABSTRACT FROM AUTHOR]