考虑环境约束的不确定性城市能源系统优化模型
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摘要
随着城市社会经济的快速发展和人民生活水平的提高,能源消费量持续增长,能源供需矛盾日益紧张。而以煤炭为主的能源结构导致大量环境污染物和温室气体的排放,城市环境污染问题日益严重。我国城市能源管理面临着经济发展与环境保护的双重压力,且存在着较大的不确定性。因此,综合考虑能源、环境和经济,建立不确定性城市能源系统优化模型,将为我国的城市能源管理及决策提供科学的和实用的技术手段,促进社会经济、能源与环境的协调可持续发展。
在城市能源系统分析的基础上,研究我国城市目前存在的主要能源问题,以及与能源利用相关的环境问题。针对这些主要问题,考虑我国城市能源结构和能流特征,以及能源系统优化模型的变量和参数存在的诸多不确定性,以区间规划为基本框架,综合机会约束规划、模糊规划和混合整数规划等方法来处理能源与环境系统的不确定性和复杂性,陆续开发了不确定性的城市能源系统综合优化模型,不确定性机会约束混合整数城市能源系统优化模型,不确定性模糊机会约束混合整数城市能源系统优化模型。
为验证不确定性城市能源系统优化模型的可靠性和实用性,将其应用到北京市能源系统的实例研究中。这三种不确定性能源模型的结果均表明,北京市城市能源结构将从以原煤为主的污染型能源结构逐步转变为以天然气、电力等优质能源为主的清洁型能源结构。电力生产仍以燃煤发电为主,但燃气热电联产技术得到大力发展,成为发电量与燃煤发电不相上下的第二大电源,水电、风电等可再生能源发电技术在总装机容量中的比例将提高到5～8%。北京市热力生产主要发展了燃气供热技术,热泵和地热技术等新兴供热技术在规划期内也有容量增加。
在城市能源模型中,电力生产是非常重要的组成部分。应用区间规划和机会约束规划方法建立不确定的电厂优化配煤模型,这些模型可以在煤质参数发生一定程度的波动时,仍能保证配煤质量满足电力生产要求。初步探讨了配煤特性与机组负荷之间的关联,建立电厂负荷优化分配与配煤优化模型,在满足机组实时负荷变化下的生产要求的同时,避免不必要的燃料浪费和减少污染物的排放。
Rapid socio-economic development and improvement in people's living standards result in increased energy consumption. Contradiction between energy supply and demand is becoming increasingly acute. Furthermore, the coal-dominance energy structure has caused that large quantities of pollutants and greenhouse gases (GHGs) were emitted and environmental pollution became more seriously. So, China's municipal energy management is confronted with dual pressures from economic development and environmental protection. Therefore, with considering energy, environment and economy, a series of inexact energy system optimization models were developed, which would provide scientific and practical techniques for China's municipal energy management and decision-making. They would promote coordinated and sustainable development of the energy, environment and economy.
On the basis of energy system analysis, some major energy problems and related environmental problems in China's urban energy system at present were discussed. In response to these concerns, considering the energy structure and energy flow characteristics of our country, chance-constrained programming (CCP), fuzzy linear programming (FLP) and mixed integer linear programming (MILP) was separately or jointly integrated within the basic framework of interval linear programming (ILP) to deal with uncertainties that exist in the variables and parameters of energy system optimization models. In order to reflect uncertainty and complexity of energy and environmental system, a series of energy models under uncertainties were developed, which were the inexact urban energy system optimization model, the inexact chance-constrained mixed-integer programming approach for urban energy system optimization model, and the inexact fuzzy chance-constrained mixed-integer programming approach for urban energy system optimization model.
In order to verify reliability and practicality of these above-mentioned inexact urban energy system optimization models, they were applied to Beijing's energy system as case studies. The results would help shift Beijing from coal-dominance energy structure to cleaner high-quality energy structure that had more shares of clean energy types such as natural gas and electricity. Coal-fired power plants are still the main force of electricity production. In the periods of planning, natural gas-fired heat and power co-generation technology would be developed rapidly, and it would become the second-largest power supply, a little less than coal-fired electricity generating. Hydropower, wind power and other renewable energy power generation technologies would also be developed, around to 5-8 percent of the total capacity. The heat generating would mainly supplied by natural gas. Heat pump, geothermal technology and other new technologies, have some capacities expansion during the planning period.
Electricity system is a very important component of urban energy system optimization model. Interval linear programming and chance-constrained programming was applied to establish some nonlinear programming methods for coal blending in power plants. The results showed that the quality of blended coal would meet production requirements of coal-fired power plants though the price and some quality parameters of coal fluctuated to some extent. The relationship between unit load and coal quality was discussed, on the basis, an optimization model for load distribution and coal blending in power plant was developed. The results of a case study showed that the optimization model for load dispatch and coal blending would satisfy the requirement of electricity-generating with real-time unit load changing, and avoid unnecessary fuel consumption, and reduce the emissions of contaminants.
在城市能源系统分析的基础上,研究我国城市目前存在的主要能源问题,以及与能源利用相关的环境问题。针对这些主要问题,考虑我国城市能源结构和能流特征,以及能源系统优化模型的变量和参数存在的诸多不确定性,以区间规划为基本框架,综合机会约束规划、模糊规划和混合整数规划等方法来处理能源与环境系统的不确定性和复杂性,陆续开发了不确定性的城市能源系统综合优化模型,不确定性机会约束混合整数城市能源系统优化模型,不确定性模糊机会约束混合整数城市能源系统优化模型。
为验证不确定性城市能源系统优化模型的可靠性和实用性,将其应用到北京市能源系统的实例研究中。这三种不确定性能源模型的结果均表明,北京市城市能源结构将从以原煤为主的污染型能源结构逐步转变为以天然气、电力等优质能源为主的清洁型能源结构。电力生产仍以燃煤发电为主,但燃气热电联产技术得到大力发展,成为发电量与燃煤发电不相上下的第二大电源,水电、风电等可再生能源发电技术在总装机容量中的比例将提高到5～8%。北京市热力生产主要发展了燃气供热技术,热泵和地热技术等新兴供热技术在规划期内也有容量增加。
在城市能源模型中,电力生产是非常重要的组成部分。应用区间规划和机会约束规划方法建立不确定的电厂优化配煤模型,这些模型可以在煤质参数发生一定程度的波动时,仍能保证配煤质量满足电力生产要求。初步探讨了配煤特性与机组负荷之间的关联,建立电厂负荷优化分配与配煤优化模型,在满足机组实时负荷变化下的生产要求的同时,避免不必要的燃料浪费和减少污染物的排放。
Rapid socio-economic development and improvement in people's living standards result in increased energy consumption. Contradiction between energy supply and demand is becoming increasingly acute. Furthermore, the coal-dominance energy structure has caused that large quantities of pollutants and greenhouse gases (GHGs) were emitted and environmental pollution became more seriously. So, China's municipal energy management is confronted with dual pressures from economic development and environmental protection. Therefore, with considering energy, environment and economy, a series of inexact energy system optimization models were developed, which would provide scientific and practical techniques for China's municipal energy management and decision-making. They would promote coordinated and sustainable development of the energy, environment and economy.
On the basis of energy system analysis, some major energy problems and related environmental problems in China's urban energy system at present were discussed. In response to these concerns, considering the energy structure and energy flow characteristics of our country, chance-constrained programming (CCP), fuzzy linear programming (FLP) and mixed integer linear programming (MILP) was separately or jointly integrated within the basic framework of interval linear programming (ILP) to deal with uncertainties that exist in the variables and parameters of energy system optimization models. In order to reflect uncertainty and complexity of energy and environmental system, a series of energy models under uncertainties were developed, which were the inexact urban energy system optimization model, the inexact chance-constrained mixed-integer programming approach for urban energy system optimization model, and the inexact fuzzy chance-constrained mixed-integer programming approach for urban energy system optimization model.
In order to verify reliability and practicality of these above-mentioned inexact urban energy system optimization models, they were applied to Beijing's energy system as case studies. The results would help shift Beijing from coal-dominance energy structure to cleaner high-quality energy structure that had more shares of clean energy types such as natural gas and electricity. Coal-fired power plants are still the main force of electricity production. In the periods of planning, natural gas-fired heat and power co-generation technology would be developed rapidly, and it would become the second-largest power supply, a little less than coal-fired electricity generating. Hydropower, wind power and other renewable energy power generation technologies would also be developed, around to 5-8 percent of the total capacity. The heat generating would mainly supplied by natural gas. Heat pump, geothermal technology and other new technologies, have some capacities expansion during the planning period.
Electricity system is a very important component of urban energy system optimization model. Interval linear programming and chance-constrained programming was applied to establish some nonlinear programming methods for coal blending in power plants. The results showed that the quality of blended coal would meet production requirements of coal-fired power plants though the price and some quality parameters of coal fluctuated to some extent. The relationship between unit load and coal quality was discussed, on the basis, an optimization model for load distribution and coal blending in power plant was developed. The results of a case study showed that the optimization model for load dispatch and coal blending would satisfy the requirement of electricity-generating with real-time unit load changing, and avoid unnecessary fuel consumption, and reduce the emissions of contaminants.
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