Minimize Carbon Emissions Research Articles

Multi-objective bi-level planning of the integrated energy system considering uncertain user loads and carbon emission during the equipment manufacturing process

Faced with urgent energy crisis and global warming, there is still debate on how to balance the relationship between the economy and environment when planning energy systems. Aiming at this problem, a multi-objective bi-level planning model of the integrated energy system has been developed. In the first stage, the equipment capacity is configured with the objective of minimize carbon emissions from the production phase. In the second stage, the system operation model is a bi-level model, considering the uncertainty loads. In addition, various energy storage strategies for the integrated energy system are simulated, including following the electric load (FEL), following the cold load (FCL), following the heat load (FHL), and price following renewable energy (PFR). In the results of capacity configuration, the photovoltaic installation capacity decreases by 44% with no wind power. Five cases are designed, which contain single and combination strategies. The results show that the system with PFR-FEL can produce carbon emissions and cost 7.3 × 107 kg/year, 4.7 × 107 CNY/year, respectively, while the system with PFR can produce carbon emissions and cost 7.8 × 107 kg/year, 5.2 × 107 CNY/year, respectively. Those results indicate that photovoltaic is more valuable than wind power in Urumqi, and the combination strategy has better performance than single strategy.

Optimal configuration method of electric vehicle’s participating in Load Aggregator’s VPP low-carbon economy

This paper aims to improve the reliability of multi-type load power supply, reduce the disorder of electric vehicle (EV) charging, and ensure the low-carbon economic operation of virtual power plant (VPP). Therefore, the optimal allocation method of low-carbon economy for VPP involving load aggregator (LA) participated by EV is proposed. First, a probabilistic model of electric load demand of a VPP is constructed, and an aggregation model of multiple types of uncertain loads is established based on the probabilistic model. Secondly, the disorder of EV charging is analyzed. Considering the time-of-use price policy, an optimization model with the maximum profit of load aggregator is established. Finally, the supply and demand matching model of VPP is established, and the minimum carbon emission and maximum net income of virtual power plant are optimized. Through simulation analysis, it is verified that this optimal configuration method can effectively improve the economics of EVLA and VPP, and ensure low-carbon operation of VPP.

Role of environmental emissions on work engagement in industrial sectors: An exploratory study of the workforce, resource planning, and environmental performance in sustainable development

The study is conducted for 1991–2021 using annual data for China to examine the non-linearity among environmental emissions and work engagement using the Non-Linear Autoregressive Distributive Lag (NARDL) modeling approach. The study's findings reflect that, in contrast to the widespread assumption, asymmetric relationships exist between CO2 emissions and employee engagement in the short and long run for the industrial and services sectors. Hence, the study reflects that considering the linear association between environmental emissions and work engagement may not be accurate and results in biased outcomes. Based on the study's results, the policymakers and environmentalists are suggested to achieve the sustainability targets by minimizing carbon emissions by utilizing environmentally friendly technologies and efficient energy.

Welding parameters and sequences integrated decision-making considering carbon emission and processing time for multi-characteristic laser welding cell

Welding parameters and sequences significantly impact the carbon emission and processing time for laser welding cells. Considering the multi-characteristic of the laser welding cell, achieving integrated decision-making on welding parameters and sequences for laser welding cells remains the challenge. To tackle the gap, this research carries out the welding parameters and sequences integrated decision-making considering carbon emission and processing time for multi-characteristic laser welding cell. Firstly, the 6 M characteristics (multi-source, multi-device, multi-state, multi-feature, multi-stage, and multi-sequence) of the laser welding cell are proposed for revealing the time-series coupling and dynamics of the carbon emission. Then, an integrated decision-making model of welding parameters and sequences for laser welding cell is proposed for minimizing carbon emission and processing time. To obtain the optimal solution, a two-layer solving algorithm combined with the state compression dynamic programming (SCDP) and multi-objective marine predator algorithm (MOMPA) is developed, and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is employed for decision-making on solution set. Finally, the case study of one laser welding cell for aluminum alloy body-in-white is performed for demonstrating the reliability and effectiveness of the integrated decision-making model and solving method, and the carbon-reduction and time-saving potential of the laser welding cell is analyzed.

Two‐stage self‐adaption security and low‐carbon dispatch strategy of energy storage systems in distribution networks with high proportion of photovoltaics

AbstractWith the goal of achieving carbon neutrality, active distribution networks (DNs) with a high proportion of photovoltaics (PVs) are facing challenges in maintaining voltage stability and low‐carbon operation. Energy storage systems (ESSs), which have the ability to store and transfer energy temporarily, can be used as effective measures to enhance the capacity of consuming PVs and reduce carbon emissions in DNs. However, existing low‐carbon dispatch strategies for multiple sources, storages and loads fail to consider voltage violations, while the temporal carbon emission intensity of the upper‐level power grid is also often overlooked, which is an important factor that affects the dispatch strategy. Therefore, a two‐stage self‐adaptive dispatch strategy of ESSs that considers the temporal characteristics of slack nodal carbon emission intensity to minimise carbon emissions while maintaining voltage stability in DNs with high access to PVs is proposed. First, the framework of the proposed two‐stage self‐adaptive dispatch strategy of ESSs is established by taking into account the effects of ESSs on adjusting voltages and reducing carbon emissions, respectively, with the two‐stage switch principle of two operation modes being determined. On this basis, an optimization dispatch model is established to improve voltages and carbon emissions, and the optimal day‐ahead dispatch strategy of ESSs can be obtained by solving the model using genetic algorithm. Case studies of the modified 10 kV IEEE 33‐node DN and IEEE 123‐node DN verify the feasibility and superiority of the proposed two‐stage self‐adaptive security and low‐carbon day‐ahead dispatch strategy for ESSs, showing that the voltage stabilisation and lower carbon emissions of DNs are both improved.

Integration and Optimisation of Palm Oil Sector with Multiple-Industries to Achieve Circular Economy

A typical palm oil sector includes oil palm plantations, palm oil mills, and palm oil refineries. The sector generates a huge amount of biomass by-products, effluent, and refinery wastes. These are usually disposed of at landfills causing inefficient waste management and sustainability issues. As reported in many previoius works, palm-based biomass, palm oil mill effluent (POME) and refinery wastes can be reused or recycled within the palm oil sector. However, there are still large amounts of these which are unprocessed and disposed to landfills. To address this issue, a circular economy approach that integrates the palm oil sector with other industries is needed. This work proposes a mathematical optimisation model to determine the optimal pathway for the circularity of palm-based biomass, POME, and refinery wastes with other sectors. Paper, polymer, and furniture industries are considered to evaluate the potential of a palm-based circular economy. Besides, various biorefineries are also considered, thereby providing multiple pathways for the conversion of palm-based biomass and refinery wastes to value-added products and energy generation. The optimisation is performed under four scenarios – maximise economic potential, minimise net emissions, minimise landfill wastes, and fuzzy multi-objective. The multi-objective results show economic potential of USD 151.36 million, net emissions of −804,946.60 tCO2 and landfill waste reduction by 80.17 %. The results indicate that the polymer industry has better potential to integrate with the palm oil sector. The fuzzy optimisation has allowed to determine trade-off between landfill disposal and resource circularity to maximise the economic value and minimise carbon emissions.

REVEALING TIMBER STRUCTURES POTENTIAL IN DECARBONIZATION OF LOW-RISE RESIDENTIAL BUILDINGS

The article presents the results of theoretical studies on embodied carbon for load-bearing wall structures prevailing in low-rise buildings consturction practice in order to reveal the potential of timber structures in decarbonization of the construction sector. Seven types of wall structures were considered in the study. CO2 emissions were determined using the environmental product declarations for relevant materials considering sequential life-cycle stages (raw material supply, production and transportation of building products, construction process, building waste transportation and disposal) with regard to recycling benefits. A lightweight timber framed wall panel was shown to have minimum carbon emissions at each life-cycle stage leading to lowest total carbon embodied

Co-optimization of passive building and active solar heating system based on the objective of minimum carbon emissions

Co-optimization of passive building and active solar heating system based on the objective of minimum carbon emissions

중국 자동차 산업의 역물류 네트워크 최적화에 관한 연구

Reverse logistics network design is a strategic level of decision-making, and the recovery process of abandoned vehicles is inseparable from the support of a complete reverse logistics network. Against the backdrop of the green economy and the circular economy, this study designed a waste vehicle reverse logistics network under two constraints: carbon tax policy and carbon transaction market policy, respectively, and established a multi-purpose mixed integer linear plan model to minimize carbon emissions and costs. In addition, using a Chinese automobile manufacturer as an example, the results of the model of maximizing economic effects (i.e., minimizing costs) and maximizing environmental effects by conducting case verification and using lingo 11.0 are as follows. First, the cost of transportation using pure electric vehicles under the same carbon emission policy is lower than using fuel cars. Second, under the two carbon policies, carbon trading policies have a better emission reduction effect and lower network operating costs. Third, we found that transactional carbon constraints help companies reduce costs and reduce carbon emissions, and help shape long-term, even image-oriented, corporate behavior. By analyzing the optimization of China's waste vehicle reverse logistics network, this study promotes the sustainable and sound development of Chinese waste vehicle recovery companies and realizes the double benefits of the economic environment. There is a certain significance in the research and practice of developing reverse logistics activities in academia

A Novel Sustainable Reverse Logistics Network Design for Electric Vehicle Batteries Considering Multi-Kind and Multi-Technology

With the expansion of the new energy vehicle market, electric vehicle batteries (EVBs) have entered a massive retirement wave. The strategic level of facility location and configuration decisions and the tactical level of multi-product flow and multi-technology selection decisions have been integrated into a sustainable reverse logistics network (SRLN). In this paper, we considered multiple kinds of waste electric vehicle batteries (WEVBs) with multiple recycling technology and constructed a multi-level SRLN model for WEVBs with the objectives of minimum economic costs and minimum carbon emissions. To solve this model, fuzzy set theory was applied to the equivalence transformation of constraints, non-interactive and interactive methods were used to solve the multi-objective planning (MOP), and interactive fuzzy programming with priority control was proposed to find the global optimal solution for this model. Finally, numerical experiments demonstrated the feasibility and effectiveness of the proposed model and solution method. The experimental results show that the SRLN model considering carbon emissions can significantly reduce carbon emissions of the network through a slight increase in the initial network construction cost, thus effectively balancing both economic and environmental objectives. In the non-interactive solution, the Lp-metric method has a lower deviation index than the weighted sum method; in the interactive solution, the priority control method proposed in this paper outperforms the TH method in terms of the number of practical solutions and CPU time and shows strong performance in searching and finding optimal solutions. The proposed model and method can provide the theoretical basis and technical support for a WEVB SRLN under the limited information uncertainty environment.

Optimization Model of Substation Building Envelope–Renewable Energy Utilization Based on Life-Cycle Minimum Carbon Emissions

Maximizing the carbon reduction in substations with minimum cost investments can be achieved by taking advantage of the potential of substations in terms of the envelope and renewable energy, which is significant in promoting carbon reduction in substations. Therefore, firstly, the relationship between building cost–energy consumption–carbon emissions is explored, and then the global optimal calculation model of substation envelope–renewable energy is established, with the lowest life-cycle carbon emission of the substation as the optimization goal. Finally, the validity of the model is verified based on a case study of a typical 110 kV outdoor substation. The model calculation results show that, without considering the cost constraint, Harbin has the highest maximum carbon reduction of 180,350 kg, which is 25.15% and 13.74% higher than the maximum carbon reduction in Shanghai and Haikou, respectively. Furthermore, based on the comparison of the cost and benefits of each carbon reduction technology, a prioritization of various carbon reduction technologies is given for each climate zone. The model established in this paper can provide the optimal configuration of substation carbon reduction technologies with different incremental cost constraints, and provide a reference for the low-carbon design of substations.

Robust optimal dispatching model and a benefit allocation strategy for rural novel virtual power plants incorporating biomass waste energy conversion and carbon cycle utilization

To optimize the utilization of rural biomass waste resources (e.g., straw and solid waste), biomass waste energy conversion (BWEC) and carbon cycle utilization (CCU) are integrated into a traditional virtual power plant, i.e., a rural BWEC-CCU-based virtual power plant. Furthermore, a fuzzy robust two-stage dispatching optimal model for the BWEC-CCU-based virtual power plant is established considering the non-determinacy from a wind power plant (WPP) and photovoltaic (PV) power. The scheduling model includes the day-ahead deterministic dispatching model and real-time uncertainty dispatching model. Among them, in the day-ahead dispatching phase, the dispatching plan is formulated with minimum operating cost and carbon emission targets. In the real-time dispatching phase, the optimal dispatching strategy is formulated aiming at minimum deviation adjustment cost by applying the Latin hypercube sampling method. The robust stochastic theory is used to describe the uncertainty. Third, in order to achieve optimal distribution of multi-agent cooperation benefits, a benefit distribution strategy based on Nash negotiation is designed considering the three-dimensional interfering factor of the marginal benefit contribution, carbon emission contribution, and deviation risk. Finally, a rural distribution network in Jiangsu province, China, is selected for case analysis, and the results show that 1) the synergistic optimal effect of BWEC and CCU is obvious, and the operation cost and deviation adjustment cost could decrease by 26.21% and 39.78%, respectively. While the capacity ratio of WPP + PV, BWEC, and CCU is 5:3:2, the dispatching scheme is optimum. 2) This scheduling model can be used to formulate the optimal scheduling scheme. Compared with the robust coefficient Γ = 0, when Γ = 1, the WPP and PV output decreased by 15.72% and 15.12%, and the output of BWEC and CCU increased by 30.7% and 188.19%, respectively. When Γ∈ (0.3, 0.9), the growth of Γ has the most direct impact on the dispatching scheme. 3) The proposed benefit equilibrium allocation strategy can formulate the most reasonable benefit allocation plan. Compared with the traditional benefit allocation strategy, when the proposed method is used, the benefit share of the WPP and PV reduces by 5.2%, and the benefit share of a small hydropower station, BWEC, and CCU increases by 1.7%, 9.7%, and 3.8%, respectively. Overall, the proposed optimal dispatching and benefit allocation strategy could improve the aggregated utilization of rural biomass waste resources and distributed energy resources while balancing the benefit appeal of different agents.

A method for power flow calculation and optimal dispatch of gas–thermal–electricity multi energy system considering unit commitment

The optimal scheduling of integrated energy system considering unit commitment is a mixed integer nonlinear programming (MINLP) problem with 0-1 binary variables, and the efficient solution of MINLP has always been a research hotspot. In this paper, a power flow calculation method of gas thermal power multi energy coupling system is proposed. Considering the output of coal-fired, gas-fired and new energy units, a simplified unit commitment calculation model is established, which can greatly reduce the number of binary variables and constraints. At the same time, an optimal scheduling model with minimum economic cost and minimum carbon emission is established. For the nonlinear and non convex problem of air pressure equations, the incremental piecewise linearization method based on the idea of feasible region segmentation is used to transform it into MILP model, and the effective optimal solution is obtained. Finally, an example is given to verify the effectiveness and accuracy of the proposed algorithm.

Carbon distribution and multi-criteria decision analysis of flexible waste biomass smouldering processing technologies

Waste biomass treatment is a globally urgent matter which highly relates to environmental quality and human health. Here, a flexible suite of smouldering-based waste biomass processing technologies is developed and four processing strategies: (a) full smouldering, (b) partial smouldering, (c) full smouldering with a flame, and (d) partial smouldering with a flame, are proposed. The gaseous, liquid, and solid products of each strategy are quantified under various airflow rates. Then, a multi-criteria analysis in terms of environmental impact, carbon sequestration, waste removal efficiency, and by-product value is performed. The results show that full smouldering achieves the highest removal efficiency but generates significant greenhouse and toxic gases. Partial smouldering effectively generates stable biochar, sequesters over 30% carbon, and therefore reduces the greenhouse gases to the atmosphere. By applying a self-sustained flame, the toxic gases are significantly reduced to clean smouldering emissions. Finally, the process of partial smouldering with a flame is recommended to process the waste biomass that can sequester more carbon as biochar, minimize carbon emissions and mitigate the pollution. And the process of full smouldering with a flame is preferred to maximally reduce the waste volume with minimum environmental impact. This work enriches strategies for carbon sequestration and environmentally friendly waste biomass processing technologies.

Integrated optimization of inventory, replenishment, and vehicle routing for a sustainable supply chain utilizing a novel hybrid algorithm with carbon emission regulation

An integrated approach of making supply chain decisions has been proven to be more cost-effective compared to the strategy of taking supply chain decisions sequentially. It has influenced researchers to break the norm and focus on integrated supply chain decision-making. Considering this an integrated sustainable supply chain network for a single vendor and multiple buyers is formulated along with trade credit policy. The vendor offers a trade credit policy to its buyers. Emissions generated from production, vehicle routing, and storage are taken into account. To minimize carbon emissions, a cap & trade policy is applied. The buyers are served by a fleet of vehicles available at the vendor location. Considering the aforementioned scenario, a mathematical formulation is developed so as to minimize the overall total cost subject to a set of constraints. The integrated decisions regarding production, inventory management, vehicle routing, and carbon emissions are taken. Besides this, a unique metaheuristic technique is also suggested to solve the proposed problem. The solutions obtained through the process of well-known genetic algorithm are further improved during the ruin and recreate phase of the hybridized algorithm named as GA-RR. An in-depth empirical examination of GA-RR algorithm is also done through a quantitative analysis of exploration and exploitation. To better illustrate the proposed mathematical problem, two numerical examples are also demonstrated. It is followed by an extensive sensitivity analysis of the various input parameters so as to highlight important results. It can be concluded that GA-RR outperforms other existing metaheuristic techniques for the proposed mathematical problem.

Micro-Grid Hybrid Renewable Energy Sources Optimal Sizing for Cost and Carbon Emission Reduction using Grey Wolf Algorithm

The rapid depletion of fossil fuel resources and the growing evidence of global warming have made the utilization of renewable energy sources more attractive, especially with the increase in global energy demand. Most of the renewable energy sources are dependent on climate conditions. Therefore, Hybrid Renewable Energy Sources (HRES) can be highly efficient systems. In this paper, the Grey Wolf Algorithm (GWO) is proposed to find the optimal operation of PV/Wind HRES for a typical industrial load system with the objective of minimizing carbon emissions and life cycle cost (LCC). The algorithm is utilized to study two scenarios (PV/Wind and PV/Wind/Diesel generator) in comparison with conventional energy systems. The analysis of the results shows that both scenarios are more appealing than the conventional system. The first scenario can be considered the most attractive scenario for LCC and carbon emissions reduction. 60% and 90 % reductions are achieved, respectively. The second scenario can be considered the most attractive scenario for dump energy reduction. A 33% reduction is achieved compared to the first scenario.

Carbon efficiency in China: Should we be concerned about the shadow economy and urbanization?

Reducing carbon emissions is critical to achieving a carbon‐neutral world according to the Glasgow Climate Pact, but production, and thus carbon emissions, must continue to meet the needs of the world's growing population. Minimizing carbon emissions per production, that is, increasing carbon efficiency is one way to support the Sustainable Development Goals. Therefore, studying the determinants of carbon efficiency for China, the largest global polluter, is important for zero carbon goals. To this end, this study examines the effects of the shadow economy, globalization, trade openness and urbanization on carbon efficiency using novel dynamic autoregressive‐distributed lag simulations for China during 1990–2018. The empirical results illustrate that (i) the environmental Kuznets curve (EKC) hypothesis is not valid; (ii) Shadow economy, trade openness and urbanization reduce carbon efficiency and (iii) Globalization enhances carbon efficiency. Based on these results, it is suggested that the Chinese government should combat the shadow economy to increase carbon efficiency, regulate unplanned and polluting urbanization in a green manner, reduce carbon intensity in foreign trade, and benefit from environmental technologies provided by globalization.

MODULAR CONSTRUCTION: A SUSTAINABLE SOLUTION FOR CARBON EMISSION REDUCTION IN THE CONSTRUCTION INDUSTRY

This research focuses on modular construction as a sustainable solution for reducing carbon emissions in the construction industry. The study examines the environmental benefits of modular construction and its potential to mitigate the carbon footprint associated with traditional construction methods. Through a comprehensive literature review and analysis of case studies, the research explores the use of modular construction techniques, including off-site fabrication and assembly, eco-friendly materials, energy-efficient systems, and renewable energy technologies, to minimize carbon emissions throughout the building lifecycle. The findings highlight the advantages of modular construction in terms of reduced construction time, improved resource efficiency, and lower energy consumption, resulting in significant carbon emission reductions. The research contributes to the existing body of knowledge by emphasizing the importance of adopting sustainable practices in the construction industry and provides valuable insights into the role of modular construction as a sustainable solution for carbon emission reduction.

The carbon cost of agricultural production in the global land rush

Increases in the number of large-scale land transactions (LSLTs), commonly known as ‘land grabbing’ or ‘global land rush,’ have occurred throughout the lower- and middle-income world over the past two decades. Despite substantial and continuing concerns about the negative socio-environmental impacts of LSLTs, trade-off analysis on boosting crop yield and minimizing climate-related effects remains limited. Our study makes use of a global dataset on LSLTs for agricultural production to estimate potential carbon emissions based on different scenarios of land cover change and fertilizer use, as well as potential value of agricultural production on transacted land. We show that, if fully implemented on ∼ 38 M ha of transacted land, 2.51 GtC will be emitted during land conversion, with another 24.2 MtC/year emitted from fertilizer use, assuming farming technology of investors’ origin is adopted on transacted land. Comparison of different combinations of forest protection policies and agricultural intensification levels reveals that enforcing strict deforestation regulation while promoting fertilizer use rate improves the carbon efficiency of agricultural production. Additionally, positive spillovers of investors’ farming technology on existing arable lands of host countries can potentially double their crop yield. Our analyses thus suggest that fostering agricultural intensification and technology spillovers under strict regulation on land allocation to investors to protect forests would allow for boosting agricultural yield while minimizing carbon emissions.

Multi-objective route optimization of urban cold chain distribution using electric and diesel powered vehicles

Increasingly serious urban road congestion and environmental pollution have led some cities to impose restrictions such as limiting certain types of vehicles and the areas in which they can operate and introducing subsidies and other incentives for electric refrigerated vehicles. As a result, both internal combustion engine (ICE) refrigerated vehicles and electric refrigerated vehicles will be used together in urban cold chain distribution for a long time into the future. Most current studies are concerned with mixed vehicle type allocation or mixed vehicle routing problems. Although there are some studies that combine the two, there has been little research into the effects of low carbon emission and multiple objective optimization on distribution and routing for a mixture of vehicle types. This paper describes the creation of an optimized decision-making cold chain distribution model that includes different types of distribution vehicles and different route optimization criteria that represent the three enterprise objectives of minimal cost, minimum carbon emissions and minimum distance. The decision criteria are influenced by conflicting benefits offered by ICE and electric refrigerated vehicles as well as government subsidies for electric refrigerated vehicles and carbon emission trading by logistics enterprises. A chaotic particle swarm optimization algorithm was used to analyze a cold chain distribution system in Wuhan, Hubei Province, China. The results show that: (1) The choice of enterprise distribution models and the vehicles and routes determined are closely related to enterprise goals. To minimize total cost, ICE refrigerated trucks with less load capacity and electric refrigerated trucks with greater load capacity are preferred. To minimize carbon emissions, ICE refrigerated trucks and electric refrigerated trucks with less load capacity are preferred. To minimize total distance, ICE refrigerated trucks and electric refrigerated trucks with greater load capacity are preferred. (2) As the value of government subsidies increases, the total load capacity of electric refrigerated vehicles also increases, the distribution routes change, and total carbon emissions and total distribution costs decrease. (3) When carbon emission trading prices increase, the number of electric refrigerated vehicles gradually increases, the distribution path changes, the total distribution costs increase, and total carbon emissions decrease. Some suggestions are made for government to determine subsidies for electric refrigerated vehicles and carbon emission trading policies that will guide the choice of distribution vehicles and affect the criteria used for route optimization by cold chain logistics enterprises.