Inexact Optimization Methodology For Municipal Energy System Management Under Environmental Constraints

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.