Low-carbon Benefits Research Articles

Bilevel low-carbon coordinated operation of integrated energy systems considering dynamic tiered carbon pricing methodology

The coordinated operation and management of energy and carbon emissions in an integrated energy system (IES) can effectively promote overall energy efficiency and reduce carbon emissions. However, allocating carbon emission responsibilities between transmission-level integrated energy system (TIES) and regional integrated energy system (RIES) is difficult. On the basis of carbon emission flow theory, a model for allocating carbon emission responsibility for IES is developed in this paper. Moreover, the Shapley value method is adopted to obtain the carbon emissions responsibility intervals at the RIES. A dynamic tiered carbon pricing methodology is proposed for the RIES on the basis of equitable carbon emission responsibility intervals. In addition, a bilevel coordinated operation model that imposes carbon price to more fully excavate the low-carbon benefits obtained from operating an IES is proposed. The upper-level model, namely, the TIES, explores the optimal low-carbon schedule for energy networks by imposing fixed carbon price on the energy production costs. The lower-level model, namely, the RIES, investigates the optimal low-carbon energy supply scheme of multienergy coupling equipment and imposes dynamic tiered carbon pricing to adjust the amount of electricity and natural gas consumed. After the whole bilevel model is solved iteratively, equilibrium is reached. Case studies verify the potential and efficacy of the proposed bilevel model, demonstrating superior effectiveness in reducing carbon emissions compared with existing methods.

Evolutionary Game Analysis of Collaborative Prefabricated Buildings Development Behavior in China under Carbon Emissions Trading Schemes

Prefabricated buildings (PBs) are considered a green way to reduce energy consumption and carbon emissions in the construction industry due to their environmental and social benefits. However, PBs have obstacles such as high construction costs, immature technology, and insufficient policy incentives, and developers’ willingness to develop them needs to be higher. Therefore, it is necessary to explore how to motivate more developers to develop PBs. In this paper, we first discuss the impact of the carbon emissions trading scheme (ETS) on the construction industry and then consider the heterogeneity of construction developers, introduce a collaborative mechanism to establish a three-party evolutionary game model between the government and the heterogeneous developers, and explore the evolution of the three-party dynamic strategies through numerical simulation. The results show that developers’ initial development probability affects the system’s evolutionary trend, and the developer who obtains more low-carbon benefits plays a dominant role. Further analyses show that critical factors such as market profitability, synergistic benefits, and carbon tax price positively influence the development of PBs, and the influence of synergistic cooperation mechanisms should be especially emphasized. This study provides practical insights into the sustainable development of the construction industry and the government’s development of a suitable carbon portfolio policy for it. Including the construction industry in the ETS is recommended when carbon prices reach 110 RMB/t. At this point, the government can remove the subsidy for PBs, but the behaviors of the developers who participate in the ETS still need to be supervised.

Enhancing low-carbon building operations leveraging demand response driven by renewable energy consumption contributions

In the pursuit of sustainable low-carbon energy practices, demand response (DR) has emerged as a pivotal strategy, particularly in the management of building energy consumption. However, current demand management methods often lack a thorough evaluation of building carbon reduction benefits and fall short in promoting grid decarbonization. This paper proposes a low-carbon operation optimization method for buildings, with a novel DR strategy aimed at facilitating local renewable energy consumption and system-level renewables integration. Considering local and systemic renewable shares, an evaluation framework is first introduced for quantitative building energy assessment in each period. The building loads with controllable flexibilities are then grouped and aggregated based on their elasticity characteristics and probability distribution. Finally, a low-carbon optimization model is established, leveraging the DR strategy for sustainable building operations through flexible load regulation. Utilizing measured building data in Shanghai, a case study with extensive analysis validates the effectiveness of the methodology. The results suggest that following DR implementation, the similarity between the building load profile and the systemic renewable share improves by 34.48 %. Moreover, carbon emissions decrease by 5.27 % at the same level of building energy consumption. Further analysis highlights that energy storage can enhance load adjustment capabilities and the potential for reducing carbon emissions. Compared to conventional DR programs, the proposed strategy demonstrates significant advantages of abundant flexibility and low-carbon benefits. The widespread implementation of low-carbon operations in large-scale building groups has profound implications for integrating renewable energy and achieving system decarbonization goals.© 2017 Elsevier Inc. All rights reserved.

Low-carbon planning of urban charging stations considering carbon emission evolution characteristics and dynamic demand

As a new generation of transportation, electric vehicles play an important role in carbon-peak targets. The development of electric vehicles needs the support of a charging network, and improper planning of charging stations will result in a waste of resources. In order to expand the charging network of electric vehicles and give full play to the low-carbon and efficient characteristics of electric vehicles, this paper proposed a charging station planning method that considers the characteristics of carbon emission trends. This paper combined the long short-term memory (LSTM) network with the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model to predict the carbon emission trend and quantified the correlation between the construction speed of a charging station and the evolution characteristics of carbon emission by Pearson’s correlation coefficient. A multi-stage charging station planning model was established, which captures the dynamic characteristics of the charging demand of the transportation network and determines the station deployment scheme with economic and low-carbon benefits on the spatiotemporal scale. The Pareto frontier was solved by using the elitist non-dominated sorting genetic algorithm. The model and solution algorithm were verified by the actual road network in a certain area of Shanghai. The results showed that the proposed scheme can meet the charging demand of regional electric vehicles in the future, improve the utilization rate of charging facilities, and reduce the carbon emission of transportation networks.

Life cycle assessment of carbon emissions for bridge renewal decision and its application for Maogang Bridge in Shanghai

The renewal of old bridges is sometimes restricted to avoid the high carbon emissions caused by materials and construction, which however might not be conductive to climate change mitigation due to their insufficient functions. In order to facilitate the optimization of renewal timing and strategy from the perspective of reducing the comprehensive global warming impacts, we put forward the low-carbon bridge renewal decision method referring to the ideas of consequential life cycle assessment (LCA) and dynamic LCA. In the proposed method, a comparative system boundary matching the bridge renewal characteristics is constructed, where the carbon emission reduction owing to the traffic efficiency improvement by functional updating is incorporated as the low-carbon benefits of renewal, and three types of time-dependent factors, i.e., time-dependent characterization factor, trend factors and changes of traffic demands, are introduced to characterize the influence of renewal timing. The proposed method provided guidance for the renewal of Maogang Bridge, the first long-span cable-stayed bridge in Shanghai. Results illustrate that the global warming impacts of renewal construction activities and the low-carbon benefits from functional updating decrease with the renewal timing. For Maogang Bridge, the rapidly increasing traffic demands inevitably advocated renewal in advance, and the reduction of global warming impacts from emission reduction or carbon uptake could be manifested for renewal in advance. Adopting material recycling in the disposal of old bridge helped reconstructing a new bridge while deconstructing the old one in 2019 becoming the finally selected low-carbon renewal strategy, which is expected to reduce 15.04 kt CO2e-2019 compared to the essential renewal in 2050 with the landfill disposal method. The robustness of the strategy choice has been justified, given the variations of analytical time horizon, expected emission trends and repair emissions. In this way, the low-carbon renewal decision method could build a quantitative basis for judging the urgency of functional updating and verifying the low-carbon benefits of immediate concrete recycling in up-coming urban renewals.

Electricity-carbon coupling retail package optimization considering low-carbon benefits of distributed renewable energy

Distributed renewable energy has developed rapidly in recent years, but its low-carbon value is usually ignored due to its limited individual capacity. It will be an important business for electricity retailers to aggregate these distributed renewable resources and make use of their carbon emission reduction benefits. Therefore, this paper proposes a business model for electricity retailers based on electricity-carbon coupling retail packages. Firstly, a framework of the business model is proposed to support distributed renewable energy transaction among the electricity retailer, prosumers, and consumers. Secondly, dynamic carbon evaluation mechanism-based electricity-carbon coupling retail packages are designed, which contain three types of generation packages for prosumers (e.g., fixed subsidy package, dynamic subsidy package and daytime generation package) and three types of consumption packages for consumers (e.g., daytime consumption package, nighttime consumption package and minimum consumption package). In addition, a single-leader and multi-followers Stackelberg game model is constructed to optimize the designed packages. Especially, the electricity retailer aims at maximizing its profit considering conditional value at risk (CVaR) as the leader. Meanwhile, prosumers and consumers respectively aim at maximizing their profit satisfaction and comprehensive satisfaction as followers. Finally, the particle swarm optimization (PSO) algorithm and CPLEX commercial solver are both used to obtain the model's Nash equilibrium (NE). Example analysis verifies the designed electricity-carbon coupling retail packages can utilize the low-carbon value of distributed renewable resources and improve the benefits and satisfaction of prosumers and consumers.

Research on Carbon Neutral Grid Enterprises’ Low Carbon Transition Strategies and Benefit Assessment

In the context of achieving the dual-carbon goal, the power sector is actively exploring ways to make a low-carbon transition. The transformation of traditional thermal power involves the safety and reliability of electricity supply in the power system, and the low-carbon transformation involves changes and transformations in various aspects, which requires huge investments and costs. Therefore, it is of great significance to study the low-carbon transition strategy of power grid enterprises and assess the benefits generated by low-carbon transition of power grid enterprises. This paper first analyzes the background and transformation objectives of the low-carbon transformation of the power industry. Then it analyzes the potential of low-carbon development on the power generation side, puts forward the path of low-carbon transformation on the power generation side according to the development potential, and analyzes the role mechanism of low-carbon technology to generate low-carbon benefits, and constructs the assessment model based on system dynamics according to the role mechanism of low-carbon benefits. Simulation analysis is carried out through actual data, and the results show that the low-carbon transition strategy can produce more economic and environmental benefits, and can provide suggestions for subsequent development for reference.

Multi-objective cooperative optimization of communication base station and active distribution grid under dual carbon targets

To achieve “carbon peaking” and “carbon neutralization”, access to large-scale 5G communication base stations brings new challenges to the optimal operation of new power systems, but also provides new opportunities for the low-carbon development of distribution networks. This paper develops a method to consider the multi-objective cooperative optimization operation of 5G communication base stations and Active Distribution Network (ADN) and constructs a description model for the operational flexibility of 5G communication base stations. Based on this, a multi-objective cooperative optimization 5G communication base station operating model and active distribution network considering the system operation economy and minimum carbon emissions as the optimization objectives are established. In the above model, by encouraging 5G communication base stations to engage in Demand Response (DR), the Renewable Energy Sources (RES), and 5G communication base stations in ADN are concurrently scheduled, and the uncertainty of RES and communication load is described by using interval optimization method. Finally, the problem is solved by combining the equivalent transformation based on interval analysis and the non-dominated sorting genetic algorithm. The analysis results of the example show that participation in grid-side dispatching through the flexible response capability of 5G communication base stations can enhance the power system’s renewable energy consumption and usage efficiency, resulting in significant low-carbon benefits.

Refined Urban Grid Simulation Planning Based on Low Carbon Goal Achievement

Abstract In this paper, a new grid planning combined with low-carbon operation simulation is proposed, a new grid planning and low-carbon operation simulation model is proposed, and the new grid planning model is investigated and illustrated from the four dimensions of constraints. For the new grid simulation planning model, the solution efficiency of the new grid planning model combined with low-carbon operation simulation is improved by the time series clustering method and the extreme scenario identification method based on the amount of lost load. Starting from the low-carbon benefit dynamics of the generation side and the consumption side, a refined urban new grid low-carbon benefit dynamic evaluation model is constructed, while the model parameters and table functions are set, and the low-carbon urban grid simulation planning based on low-carbon simulation is empirically analyzed by means of simulation analysis. The results show that in grid planning, when the carbon emission intensity is 1000gCO2/kWh, the S4 scenario only needs to add an extreme scenario in the iterative process to achieve a relative error accuracy of 0.1%, and the method of using the new grid planning and the low-carbon operation simulation model is sufficient to achieve the target of the loss of load rate and carbon emission intensity. In the evaluation of the low-carbon effect, with the increase in investment amount, the installed capacity of clean energy and the total CO2 emission reduction of the refined urban grid will show two relatively obvious upward trends.

Promoting the Low-Carbon Transition of Power Construction Projects under MRV: An Evolutionary Game Analysis

The actual situation of carbon-emission reduction in China’s power sector has not yet achieved the expected benefits. The rent-seeking behavior of participants in power construction projects (PCPs) hinders the realization of low-carbon benefits. It is necessary to explore the behavioral strategies of the various participants in the low-carbon transition of PCPs. This paper creatively constructs an evolutionary game model of PCPs’ participants from the perspective of MRV (monitoring, reporting, and verification) and introduces the influence of the public to provide a comprehensive analysis of strategic equilibrium points. Through numerical simulations with MATLAB R2021a software, this paper explores the strategic choices of participants in different situations and gives relevant inferences and proofs. The results show that the grid company dominates at the initial stage and promotes participants to regulate behaviors. Under the premise of satisfying the system-stability requirements, setting the growth rate of the grid company’s punishments to 100% can enhance the willingness for strict supervision, while the growth rate of the supervision costs to 200% significantly decreases the probability of strict supervision. With the integration of MRV and PCPs, participants spontaneously fulfill the carbon-emission-reduction tasks. Reasonable control of input costs can effectively avoid the occurrence of rent-seeking behavior. In addition, this paper sets the public-influence growth rate at 200% and finds that the public plays a greater role in driving participants to fulfill responsibilities. Based on the results, a low-carbon transition mechanism for PCPs under the MRV system is proposed by considering several dimensions, which provides suggestions for participants to fulfill carbon-reduction responsibilities.

Multi-objective Planning for Distributed Power Considering Low Carbon Benefits

Distributed power can effectively alleviate the problems of environmental pollution and energy shortage. Based on the consideration of the low-carbon benefits of DG, a multi-objective mathematical model with minimal system carbon dioxide emissions, minimum annual network loss cost, and minimal system voltage deviation of the distribution network is established for multi-type DG access location and capacity. This model is solved using a MOPSO algorithm, which gives the planners a scientific decision-making basis. The analysis results show that the DG configuration scheme obtained by this method can effectively reduce carbon dioxide emissions, reduce network loss costs, and reduce voltage deviation, which verifies the usefulness of the model and algorithm.

Long-term, multi-stage low-carbon planning model of electricity-gas-heat integrated energy system considering ladder-type carbon trading mechanism and CCS

Integrated energy system (IES) is considered as an effective means to improve efficiency and reduce carbon emissions. To further improve the efficiency and low-carbon benefits of IES, this paper proposes a novel low-carbon planning model for the electricity-gas-heat integrated energy system (EGHIES), in which a long-term, multi-stage planning approach is adopted for configuring energy production, conversion, storage equipment and transmission networks. This model mainly realizes the coupling and energy conversion of power, natural gas and heating systems through the combined heat and power (CHP). And the power-to-gas (P2G) model considering reaction heat is established and introduced into IES planning to deepen the coupling degree of the three subsystems, so as to improve the efficiency of P2G and the system. Considering it is difficult to effectively constrain carbon emissions with a fixed carbon trading price, this paper adopts a ladder-type carbon trading mechanism (LTCTM) to strengthen the effect on carbon emissions. To further improve the low-carbon benefits of IES, the carbon capture system (CCS) model installed in coal-fired generation (CG) and coal-fired boiler (CB) is established, and the CO2 captured by CCS is supplied to P2G for gas production. Finally, the effectiveness of the proposed model is verified by simulation results.

An integrated framework for industrial symbiosis performance evaluation in an energy-intensive industrial park in China.

Industrial symbiosis (IS) is an important tool to achieve green development for industrial parks. It is necessary to evaluate the IS performance for monitoring and managing the development of IS system. This study proposed an integrated framework to assess the IS performance based on the energy-intensive industrial park. Firstly, we established a Conceptual model of symbiotic coupling of three industries (iron and steel, thermal power, and cement). Then, the conceptual model was applied to extend the existing IS system in the energy-intensive industrial park. Finally, the IS performance of the extended IS system was evaluated. We verified this framework in Red flag cannel park (RFCP). The IS performance assessment in RFCP found that the existing IS activities produced significant multiple benefits and environmental impact reduction. For example, the existing IS activities produced 970.20 kt of low-carbon benefits, which accounted for 19% of the CO2 emissions in RFCP. However, after extending the existing symbiotic system combined with the conceptual model proposed in this study, we found that there still was a large amount of symbiotic potential (the reuse of waste heat, BF slag, gypsum) waiting to be developed in RFCP. In addition, we also found that the resilience of existing IS network in RFCP was weak and need to be further perfected. In general, in the further development and perfection of IS system in RFCP, the manager should not only focus on the development of IS activities among energy-intensive enterprises but also strive to foster more influential enterprises to enhance the anti-risk ability of IS network. The result indicates the integrated framework can provide support for the development and perfection of IS system in energy-intensive industrial parks.

Whether it is economical to use combined heat and power (CHP) system for the efficient utilization of associated petroleum gas in oil extraction sites in China: A cost-benefit analysis considering environmental benefits

The efficient use of associated petroleum gas with combined heat and power (CHP) systems in oil extraction sites has proven to be technically feasible, but its economic inefficiency continues to deter oil companies from using CHP, given that simple fuel cost reductions do not yield significant positive returns in the face of large investments in purchasing and maintaining CHP. This research constructs a cost-benefit analysis model, which includes the monetized environmental benefits generated by CHP. A pilot experiment operated in a certain oilfield in Shandong province shows that the annual difference between the reduction in fuel costs and the investment in purchase and maintenance of CHP is only about ¥210,000 per device. However, when environmental benefits including health benefit and low-carbon benefit are included in the model, the annual environmental benefits of a single equipment update can be about ¥760,000, and the overall annual net benefits will reach about ¥970,000. It is concluded that the application of CHP in oil extraction sites is economically efficient, taking into account the environmental benefit it can produce. The research results will help oil companies use CHP to make more contributions to carbon and air pollutant emission reduction. However, considering that a large number of CHP systems can form a distributed energy structure, the proposed model still has limitations.

Analysis Method and Case Study of the Lightweight Design of Automotive Parts and Its Influence on Carbon Emissions

The automobile industry, as a representative in pursuing the goals of “emission peak” and “carbon neutrality”, has made low carbon a new industrial practice. With regard to low carbon, the lightweight design proves to be an effective approach to reducing carbon emissions from automobiles. Given the state of research, in which the existing lightweight design schemes of automobiles seldom consider the impact of the lightweight quality on carbon emissions during the whole life cycle of the automobiles, this paper proposes a more comprehensive lightweight design method for automobiles in regard to carbon emissions. First, the finite element method was adopted to analyze the stress, strain and safety factors of the automobile parts based on their stress, so as to identify the positions where the lightweight design was applicable. Subsequently, a lightweight scheme was designed accordingly. Next, the finite element method was re-applied to the parts whose weights had been reduced. In this way, the feasibility of the lightweight scheme was verified. In addition, a method of calculating the carbon emissions produced by changes in the mass, manufacturing processes, application and recycling of automobile parts after the application of the lightweight design was also presented. The method can be used for evaluating the low carbon benefits of the lightweight design scheme. To prove the feasibility of the method, the ZS061750-152101 wheel hub designed and manufactured by Anhui Axle Co., Ltd. was taken as an example for the case analysis. The lightweight design changes three structures of the wheel hub, reducing its weight by 1.4 kg in total. For a single wheel hub, the carbon emissions are reduced by 51.22 kg altogether. That is to say, if the lightweight scheme were to be applied to all the wheels produced by Anhui Axle Co., Ltd. (about 500,000 per year), the carbon emissions from the wheel production, application and recycling could be cut by 2.56 × 107 kg, marking a favorable emission reduction effect. The proposed method can not only provide insight into the lightweight design of automobiles and other equipment against the background of low carbon but also provide a channel for calculating the carbon emission changes in the whole process after the application of the lightweight design.

Towards Low Carbon: A Lightweight Design of Automotive Brake Hub

Carbon peaking and carbon neutrality have become important considerations in today’s manufacturing industry. Vehicle lightweight design can reduce carbon emissions and it is an important means to achieve carbon peak and carbon neutrality. In this study, the lightweight design method of automotive brake hub towards low carbon and the calculation method of low-carbon benefit are presented. A brake hub is the core of a drum brake, working together with a friction plate and brake shoe to complete the braking process. The requirements for the safety performance of brake hub are becoming increasingly more stringent in order to improve the stability and safety of the braking process. The brake hub ZD02-151122A manufactured by Anhui Axle Co., Ltd.(Suzhou, China), was used as the research object. The lightweight optimization of the brake hub was designed under the lightweight drive to reduce the shape variables and stress values of the brake hub and to reduce the mass. The proposed optimization scheme changed the chamfering to 45 × 45 and increased the number of bolt holes to eight. Compared with the original brake hub, the maximum strain, maximum stress value, stress concentration coefficient, and mass were reduced by 15.38%, 17.66%, 1.50%, and 17.40%, respectively, which achieved the specified optimization goal of improving mechanical properties and reducing mass. Towards low carbon, the reduction in carbon emissions from the optimized brake hub manufacturer and the vehicle during operation was calculated. For Anhui Axle Co., Ltd., the carbon emission can be reduced by 4.21 × 106 kg per year. Moreover, vehicle exhaust emissions can be reduced by 8.76 × 108 kg if all trucks produced by a medium-sized vehicle assembly company are driven on the road until being scrapped. This study serves as a reference for design optimization and low-carbon benefit analysis of other major automotive components.

Multi-objective optimization model of micro-grid access to 5G base station under the background of China’s carbon peak shaving and carbon neutrality targets

Abstract: a large number of 5G base station are connected, which provides a new possibility for the future low-carbon development of power systems. By encouraging 5G base station to participate in demand response and incorporating it into the Microgrid, it can reduce the power consumption cost of 5G base stations and promote the efficient utilization of renewable energy. Based on the microgrid operation structure, 5G base station and multi-objective problem algorithm, a multi-objective optimization operation model of microgrid access to 5G base station is built. Considering the physical constraints of Microgrid, the objective is to minimize the operating cost and carbon emission. Through the joint dispatching of distributed clean energy generation, micro gas turbine, energy storage system and 5G base station in Microgrid, the comprehensive optimization of system economy and low-carbon benefits can be achieved. In this paper, a microgrid in Beijing is taken as the research object, and the Whale Optimization Algorithm algorithm is used to solve the multiobjective problem. The analysis results show that 5G base station can flexibly respond to microgrid scheduling, which helps microgrid to improve the consumption and utilization efficiency of renewable energy, thus bringing higher economic benefits and low-carbon benefits, and helping China to achieve the goal of carbon peak shaving and carbon neutrality at an early date.

Flexible Low-Carbon Optimal Dispatch of Honeycombed Active Distribution Network

Microgrids have a strong ability to generate local power and consume renewable energy, which can solve the problems of power supply shortages and greenhouse gas emissions created in the process of social development. The honeycombed active distribution network (HADN) can flexibly, independently, and interconnectedly operate microgrids through power exchange stations, so appropriate HADN dispatch can produce increased low-carbon benefits than general microgrids. In this study, we first designed a model for optimizing HADN with the lowest carbon emission as the target, then we introduced the concept of carbon emission flow into the optimization process to determine the carbon emission level of each element. Finally, we illustrated and verified the proposed model by a HADN composed of three microgrids. The optimization results of the case study showed that by scheduling the DGs within the microgrids, the total carbon emissions of the system were reduced from 123,328.1 to 117,688 kg CO2; the system with a HADN structure was able to produce only 110,958 kg CO2 and effectively reduce carbon emissions by 10%, which proved that HADN can be scheduled with high flexibility and provides increased low-carbon performance through the proposed optimization dispatch method.

Multi-Time Scale Rolling Optimization Scheduling of “Nealy-Zero Carbon Park” Based on Stepped Carbon Allowance Trading

Aiming at the self-government capacity and multi-time scale energy regulation requirements of “Nearly-zero Carbon Park” (NZCP) under the background of “dual carbon goals” and energy Internet, a day-ahead-intraday rolling optimization scheduling method for NZCP based on stepped carbon allowance trading is proposed. First, the energy supply and demand characteristics of liquid-storage Carbon Capture Gas-fired Power Plants (CCGPP) and Power-to-Gas (P2G) equipment are studied, and a combined system model of CCGPP and P2G is established that takes into account the low-carbon emission requirements of NZCP, and waste pyrolysis power generation facilities and manure treatment facilities are introduced to form a Waste Utilization system (WU) to provide energy support for the power grid and gas network. Second, the carbon allowance offset and low-carbon benefit gains of NZCP are considered, a compensation coefficient is introduced to guide the low-carbon behavior of carbon emitters, and a ladder carbon allowance trading model is established. Then, the influence of the source-load prediction error on the optimal scheduling at different time scales is considered, and a two-stage unit output plan is established. Then, the influence of the source-load prediction error on the optimal scheduling at different time scales is considered, and a two-stage unit output adjustment plan is established. The calculation example results verify that the proposed day-ahead-intraday rolling optimization scheduling model for NZCP can effectively reduce system carbon emissions while reducing system operating costs, and the efficient integration of economic and environmental benefits is achieved.

Behavior Choice and Emission Reduction in a Dynamic Supply Chain with a Capital-Constrained Retailer

This paper studies the dynamic optimization of a low-carbon supply chain consisting of a manufacturer and a capital-constrained retailer. Considering market randomness and accumulation of production experience, a Stackelberg differential game model is constructed. In the game, the manufacturer is the leader and its pricing and emission reduction strategies over time are deduced in farsighted and myopic behaviors, respectively. In both behaviors, the emission reduction increases over time and a relatively low/high carbon price leads to skimming/penetrating pricing strategy of the manufacturer. Numerical study shows that the manufacturer must adopt a farsighted behavior for profit seeking except that consumers’ low-carbon awareness is quite low, and the retailer also prefers the manufacturer to adopt this behavior. Increasing carbon price and consumers’ low-carbon awareness benefits the manufacturer rather than the retailer. The governments can take measures to raise the carbon price to reduce the environmental impact.