Study On Distribution Optimization Of The Total Energy Consumption Based On Total Amount Control Of Pollutants

Energy is the most important material foundation to the national economic development. The national energy consumption of China shows an obvious uptrend as the rapid development of economy. The pollutant emission from energy consumption brings tremendous pressure on environmental sustainability and is a serious constraint of environmental sustainability. Recently, policies and planning have set clear goals to the control of national energy consumption, such as The Total Energy Consumption for The Reasonable Control of Work put forward by The State Council. In 2015, the total energy consumption of China will be controlled in 4.1 billion tons. The implementation of new environmental laws will put forward higher requirements on environmental protection. How to control the national energy consumption and allocate the total energy consumption to different provinces, types of energy and industries in a proper way is the focus of present national total control of energy consumption. Moreover, some of the influence factors have uncertainties in the process of energy consumption, which the present uncertainty studies are incapable to handle. Therefore, innovative uncertainty optimization methods are necessary to propose, in order to characterize and transform the comprehensive uncertainties during energy consumption allocation.Under the policy background of national energy consumption control and total amount control of pollutant, this study proposed an allocation model of national energy consumption under total amount control of pollutant. The allocation model took the minimization of energy consumption cost as the optimal objective, and set a series of constraint, such as national energy consumption, total amount control of pollutant, intense of energy consumption, and so on, according to current policies, for instance, "Energy Efficiency and Emission Reduction in The "Twelfth Five-year" Plan", "Energy Planning in the "Twelfth Five-year" Plan", "Energy Development Strategy Plan of Action", "National Plan on Climate Change", and so forth. To presented uncertainties in forms of fuzzy-bound interval, random and interval parameters in the allocation model, fuzzy-bound left-hand-side chance-constrained programming(FB-LCCP) was firstly established and applied in the national energy consumption issue, an obtained optimal scheme for different provinces an types of energies in The "Twelfth Five-year" Plan and The "Thirteenth Five-year" Plan. The optimization for The "Twelfth Five-year" Plan gained from FB-LCCP model shows an advantageous effect. The national energy consumption is [40,41] billion tons, which is strict than national planning requirements. The intense of energy consumption shows a decline of [2.52,6.22]% to the energy planning objectives. On the aspect of air pollution control, the emission of SO2 and NOx show a decline of [0.19,0.60]% and [0.19,0.70]% to reduction targets respectively (8% and 10%). The optimization for The "Thirteenth Five-year" Plan gained from FB-LCCP model can satisfy amount control of national energy consumption (48 billion tons) and district planning (the energy consumption of Beijing, Tianjin, Hebei and Shangdong) concurrently. The intense of energy consumption display a decline of [17.58,18.76]%, while SO2 and NOc reserve a potential of [8.04,8.77]% and [10.16,10.66]% for emission reduction of The "Thirteenth Five-year" Plan.The randomness of air pollution control target has been taken into consideration, since the relevant policies and programs of The "Thirteenth Five-year" Planis not yet published, which leads to the establishment of two-stage fuzzy-bound left-hand-side chance-constrained programming (TS-FB-LCCP), integrating two-stage stochastic programming into FB-LCCP. TS-FB-LCCP has the capacity for presenting the randomness of air pollution control target and can obtain homologousrevised plan and optimal scheme under high, mid and low levels of air pollution control. The emission of SO2 and NOx for The "Thirteenth Five-year" Plan gained from TS-FB-LCCP model show a decrease of [3.70,3.91]% and [2.32,2.76]% to the optimal scheme gained by FB-LCCP. The optimal scheme of The "Thirteenth Five-year" Plan gamed from TS-FB-LCCP model can provide more optional for decision makers, even the planning objective is more rigorous in The "Twelfth Five-year" Plan.Multi-stage fuzzy-bound left-hand-side chance-constrained programming (MS-FB-LCCP) was established based on TS-FB-LCCP by integrating Multi-stage stochastic programming. The MS-FB-LCCP achieved the extension of time scale to obtain the optimal scheme of 2020,2025 and 2030, and the air pollution control level had been extended under 39 joint probabilities. Moreover, industries were took into consideration, and more specific optimal scheme had been gained. The optimal scheme in the first-stage could satisfy the target of energy consumption control and reserve [12.37,14.28]% and [12.22,14.18]% reduction space for The "Twelfth Five-year" Plan. Meanwhile, the optimal scheme in the two-stage and the third-stage were provided under 9 and 27 different levels of air pollution control. The optimization model realized the combined control of national energy consumption and air pollution under different planning periods, and provided flexible options and decision basis for the programming of national energy consumption control.In conclusion, this paper proposed FB-LCCP, TS-FB-LCCP, and MS-FB-LCCP in the first place, and applied in national energy consumption allocation issue. FB-LCCP can characterize uncertainties presented as fuzzy-bound interval parameters, left-hand-side random parameters and interval parameters, and obtained optimization for "12th Five-Year Plan" and "13th Five-Year Plan". And then, TS-FB-LCCP was established after integrated with TSP, in order to deal with randomness of total emission target of air pollution in "13th Five-Year Plan". The optimization gained by TS-FB-LCCP showed advantages under different control levels of the air pollution. Further, MS-FB-LCCP was put forward, and acquired optimization scheme for mid-long term plans (the year 2020,2025 and 2030) after time scale extension by integrating MSP into FB-LCCP. The above three optimization models were separately the integrations of the prior one, and had their own characters and advantages. FB-LCCP is suitable for the situation that the control target of air pollution is explicit, and the energy consumption cost is relatively low. TS-FB-LCCP can be applied in the situation that the control target is random in short term planning. MS-FB-LCCP is adaptive in the situation that the control target is random inlong term planning under different control level of air pollution. Hence, the energy consumption cost of MS-FB-LCCP is relatively high. The optimization scheme obtained by the three optimization model can meet the requirements of environment and energy program, and provide scientific basis for the formulation of environment energy development program. The optimization models proposed in this paper have considerable reference value and application prospect for both theory expansion and practical application.