scholarly journals Equilibrium Strategy-Based Optimization Method for Carbon Emission Quota Allocation in Conventional Power Plants

2018 ◽  
Vol 10 (9) ◽  
pp. 3195
Author(s):  
Qian Huang ◽  
Qing Feng ◽  
Yuan Tian ◽  
Li Lu
Keyword(s):  
Carbon Emissions ◽  
Power Plants ◽  
Optimal Allocation ◽  
Optimization Method ◽  
Equilibrium Strategy ◽  
Proposed Model ◽  
Emission Quota ◽  
Interactive Algorithm ◽  
Quota Allocation ◽  
Objective Model

Carbon emissions have become significant obstacles to sustainable development. To control carbon emissions, rational carbon emissions quota allocation provides an effective way. As conventional power plants (CPP) are the major contributors to global carbon emissions, this study proposes an equilibrium strategy-based bi-level multi-objective model for carbon emissions quota allocation which fully considers the conflict between the authority and the CPPs, and the conflict between economic development and environmental protection. In addition, uncertainty theory is employed to represent the imprecise parameters in reality. The proposed model is then applied to Shenzhen to show the practicality and efficiency of the proposed model. An interactive algorithm is developed to calculate. Based on results, the proposed method can achieve carbon emissions reductions, cooperative authority-CPPs relationship and economic-environmental coordination. It also indicates that the authority would allocate greater quotas to lower carbon emissions power plants. These results demonstrate the proposed method could help seek optimal allocation policies.

Stackelberg game based co-firing biomass with coal under carbon cap-and-trade regulation

2021 ◽  
pp. 0958305X2110415
Author(s):  
Zongtang Xie ◽  
Hongxia Liu
Keyword(s):  
Emission Reduction ◽  
Power Plants ◽  
Carbon Emission ◽  
Stackelberg Game ◽  
Cap And Trade ◽  
Carbon Emission Reduction ◽  
Trade Regulation ◽  
Social Welfare Maximization ◽  
Emission Quota ◽  
Interactive Algorithm

Coal-fired power industry is under enormous pressure to accomplish carbon emission reduction targets. This paper proposes a bi-level multi-objective model for co-firing biomass with coal under carbon cap-and-trade regulation which considers a leader-follower Stackelberg game between the authority and the coal-fired power plants. The upper level regards social welfare maximization and allocation satisfaction maximization as its multiple objectives, while the lower level attempts to maximize the profits of each coal-fired power plant. The inherent uncertainty prompts the motivation for employing fuzzy set theory to characterize the uncertain parameters and determine their exact values. A case study from Shandong Province, China is provided to demonstrate the practicality and efficiency of the optimization model. [Formula: see text]-constraint method and interactive algorithm are used to solve the model, and furthermore the solutions associated with different free carbon emission quota levels and minimal allocation satisfactions have been generated to examine the influences. Based on the analysis and discussion, the methodology can meet the carbon emission reduction goals and transit to a lower-carbon power generation. It also assists the decision makers to develop desired quota allocation strategy in accordance with their attitudes and actual conditions.

scholarly journals Carbon Tax and Trading Price on Power Plant with Carbon Capture and Storage under Incentive Regulation Theory

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Huan Zhang ◽  
Xinxin Xu ◽  
Jianli Jiang ◽  
Meimei Zhang
Keyword(s):  
Power Plant ◽  
Carbon Emissions ◽  
Carbon Capture ◽  
Power Plants ◽  
Carbon Emission ◽  
Carbon Capture And Storage ◽  
Regulation Mechanism ◽  
Emission Quota ◽  
The Government ◽  
Low Efficiency

This paper investigates how the government can develop subsidies or tax policies to incent power plants to effectively carry out carbon capture to reduce carbon emissions. According to the government’s incentive model for carbon capture power plants, the regulation mechanism is developed when government controls carbon emission. When regional or national carbon emission quota is tense, significant effect can be obtained when regulators make regulations to take off low efficiency power plants. In addition, it is verified that the regulators should not blindly pursue a reduction in carbon emissions regardless of the cost. Therefore, regulators need to pay more attention to control the costs of carbon capture equipment and technology. Finally, by parametric and numerical analyses, the conditions of the power plant to maximize corporate surplus are further studied.

scholarly journals Proposed Model of Sustainable Resource Management for Smart Grid Utilization

2021 ◽  
Vol 12 (2) ◽  
pp. 70
Author(s):  
Haider Ali Tauqeer ◽  
Faisal Saeed ◽  
Muhammad Hassan Yousuf ◽  
Haroon Ahmed ◽  
Asad Idrees ◽  
...  
Keyword(s):  
Resource Management ◽  
Smart Grid ◽  
Carbon Emissions ◽  
Energy Demand ◽  
Power Plants ◽  
Sustainable Energy ◽  
Energy Resource ◽  
Operating Conditions ◽  
Energy Resources ◽  
Proposed Model

Automation and modernization of the grid with the availability of micro-grids including non-conventional sources of energy are the main constituent of smart grid technology. Most energy demand is fulfilled by fossil fuel-based power plants. Inadequacy of fuel resources, higher operating costs, and ever-increasing carbon emissions are the primary constraints of fossil fuels-operated power plants. Sustainable energy resource utilization in meeting energy demand is thought to be a preferred solution for reducing carbon emissions and is also a sustainable economic solution. This research effort discusses an accurate mathematical modeling and simulation implementation of a sustainable energy resource model powered by solar, grid, and proton exchange membrane fuel cell (PEMFC) stack and focuses on the energy management of the model. In the proposed model, despite energy resources being sustainable, consumer side sustainability is achieved by using electrical charging vehicles (ECVs) to be integrated with sustainable resources. The proposed energy resource management (ERM) strategy is evaluated by simulating different operating conditions with and without distributed energy resources exhibiting the effectiveness of the proposed model. PEMFC is incorporated in the model to control fluctuations that have been synchronized with other energy resources for the distribution feeder line. In this proposed model, PEMFC is synchronized with grid and solar energy sources for both DC and AC load with ERM of all sources, making the system effective and reliable for consumer-based load and ECVs utilization.

scholarly journals New Carbon Emissions Allowance Allocation Method Based on Equilibrium Strategy for Carbon Emission Mitigation in the Coal-Fired Power Industry

2018 ◽  
Vol 10 (8) ◽  
pp. 2923
Author(s):  
Qing Feng ◽  
Qian Huang ◽  
Qingyan Zheng ◽  
Li Lu
Keyword(s):  
Power Generation ◽  
Carbon Emissions ◽  
Power Plants ◽  
Sensitivity Analyses ◽  
Equilibrium Strategy ◽  
Emission Mitigation ◽  
Solution Approach ◽  
Risk Levels ◽  
Allowance Allocation ◽  
Carbon Emission Mitigation

The carbon emissions from coal-fired power have become an increasing concern to governments around the world. In this paper, a carbon emissions allowances allocation based on the equilibrium strategy is proposed to mitigate coal-fired power generation carbon emissions, in which the authority is the lead decision maker and the coal-fired power plants are the follower decision makers, and an interactive solution approach is designed to achieve equilibrium. A real-world case study is then given to demonstrate the practicality and efficiency of this methodology. Sensitivity analyses under different constraint violation risk levels are also conducted to give authorities some insights into equilibrium strategies for different stakeholders and to identify the necessary tradeoffs between economic development and carbon emissions mitigation. It was found that the proposed method was able to mitigate coal-fired power generation carbon emissions significantly and encourage coal-fired power plants to improve their emissions performance.

scholarly journals Economical Speed for Optimizing the Travel Time and Energy Consumption in Train Scheduling using a Fuzzy Multi-Objective Model

2021 ◽  
Author(s):  
Ahmad Reza Jafarian-Moghaddam
Keyword(s):  
Energy Consumption ◽  
Travel Time ◽  
Pollutant Emissions ◽  
Scheduling Problems ◽  
Train Scheduling ◽  
Multi Objective ◽  
Consumption Ratio ◽  
Proposed Model ◽  
Objective Model ◽  
Time And Energy

AbstractSpeed is one of the most influential variables in both energy consumption and train scheduling problems. Increasing speed guarantees punctuality, thereby improving railroad capacity and railway stakeholders’ satisfaction and revenues. However, a rise in speed leads to more energy consumption, costs, and thus, more pollutant emissions. Therefore, determining an economic speed, which requires a trade-off between the user’s expectations and the capabilities of the railway system in providing tractive forces to overcome the running resistance due to rail route and moving conditions, is a critical challenge in railway studies. This paper proposes a new fuzzy multi-objective model, which, by integrating micro and macro levels and determining the economical speed for trains in block sections, can optimize train travel time and energy consumption. Implementing the proposed model in a real case with different scenarios for train scheduling reveals that this model can enhance the total travel time by 19% without changing the energy consumption ratio. The proposed model has little need for input from experts’ opinions to determine the rates and parameters.

scholarly journals Lane Allocation Optimization in Container Seaport Gate System Considering Carbon Emissions

2021 ◽  
Vol 13 (7) ◽  
pp. 3628
Author(s):  
Zhihong Jin ◽  
Xin Lin ◽  
Linlin Zang ◽  
Weiwei Liu ◽  
Xisheng Xiao
Keyword(s):  
Branch And Bound ◽  
Carbon Emissions ◽  
Integer Program ◽  
Arrival Times ◽  
Proposed Model ◽  
Gate System ◽  
Appointment System ◽  
Truck Appointment System ◽  
Gate Congestion ◽  
Allocation Decisions

Long queues of arrival trucks are a common problem in seaports, and thus, carbon emissions generated from trucks in the queue cause environmental pollution. In order to relieve gate congestion and reduce carbon emissions, this paper proposes a lane allocation framework combining the truck appointment system (TAS) for four types of trucks. Based on the distribution of arrival times obtained from the TAS, lane allocation decisions in each appointment period are determined in order to minimize the total cost, including the operation cost and carbon emissions cost. The resultant optimization model is a non-linear fractional integer program. This model was firstly transformed to an equivalent integer program with bilinear constraints. Then, an improved branch-and-bound algorithm was designed, which includes further transforming the program into a linear program using the McCormick approximation method and iteratively generating a tighter outer approximation along the branch-and-bound procedure. Numerical studies confirmed the validity of the proposed model and algorithm, while demonstrating that the lane allocation decisions could significantly reduce carbon emissions and operation costs.

A novel multi-stage ensemble model with fuzzy clustering and optimized classifier composition for corporate bankruptcy prediction

2020 ◽  
pp. 1-17
Author(s):  
Dongqi Yang ◽  
Wenyu Zhang ◽  
Xin Wu ◽  
Jose H. Ablanedo-Rosas ◽  
Lingxiao Yang ◽  
...  
Keyword(s):  
Fuzzy Clustering ◽  
Rapid Development ◽  
Optimization Method ◽  
Selection Method ◽  
Bankruptcy Prediction ◽  
Ensemble Model ◽  
Composition Method ◽  
Classifier Selection ◽  
Multi Stage ◽  
Proposed Model

With the rapid development of commercial credit mechanisms, credit funds have become fundamental in promoting the development of manufacturing corporations. However, large-scale, imbalanced credit application information poses a challenge to accurate bankruptcy predictions. A novel multi-stage ensemble model with fuzzy clustering and optimized classifier composition is proposed herein by combining the fuzzy clustering-based classifier selection method, the random subspace (RS)-based classifier composition method, and the genetic algorithm (GA)-based classifier compositional optimization method to achieve accuracy in predicting bankruptcy among corporates. To overcome the inherent inflexibility of traditional hard clustering methods, a new fuzzy clustering-based classifier selection method is proposed based on the mini-batch k-means algorithm to obtain the best performing base classifiers for generating classifier compositions. The RS-based classifier composition method was applied to enhance the robustness of candidate classifier compositions by randomly selecting several subspaces in the original feature space. The GA-based classifier compositional optimization method was applied to optimize the parameters of the promising classifier composition through the iterative mechanism of the GA. Finally, six datasets collected from the real world were tested with four evaluation indicators to assess the performance of the proposed model. The experimental results showed that the proposed model outperformed the benchmark models with higher predictive accuracy and efficiency.

scholarly journals Optimization of Consignment-Store-Based Supply Chain with Black Hole Algorithm

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Ágota Bányai ◽  
Tamás Bányai ◽  
Béla Illés
Keyword(s):  
Black Hole ◽  
Supply Chain ◽  
Optimization Problems ◽  
Optimization Method ◽  
Chain Model ◽  
Supply Chain Optimization ◽  
Proposed Model ◽  
Supply Chain Model ◽  
Supply Model ◽  
Black Hole Algorithm

The globalization of economy and market led to increased networking in the field of manufacturing and services. These manufacturing and service processes including supply chain became more and more complex. The supply chain includes in many cases consignment stores. The design and operation of these complex supply chain processes can be described as NP-hard optimization problems. These problems can be solved using sophisticated models and methods based on metaheuristic algorithms. This research proposes an integrated supply model based on consignment stores. After a careful literature review, this paper introduces a mathematical model to formulate the problem of consignment-store-based supply chain optimization. The integrated model includes facility location and assignment problems to be solved. Next, an enhanced black hole algorithm dealing with multiobjective supply chain model is presented. The sensitivity analysis of the heuristic black hole optimization method is also described to check the efficiency of new operators to increase the convergence of the algorithm. Numerical results with different datasets demonstrate how the proposed model supports the efficiency, flexibility, and reliability of the consignment-store-based supply chain.

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