Abstract
Energy-related environmental problems have been hot spot issues in regional energy system sustainable development. Thus, comprehensive planning of energy systems management is important for social and economic development, as well as environmental sustainability. In addition, uncertainties and complexities, as well as their potential interactions pose a great challenge for effective management in energy and environmental system. This study proposes a stochastic factorial energy systems management model to conduct uncertainties and risks in the energy systems, as well as handle their interaction effects among different environmental policies. The developed method can not only tackle uncertainties expressed as probability distributions and even interval values, but also be applied to determine decision alternatives associated with multiple economic penalties if the formulated environmental policy targets are violated. Meanwhile, by introducing the factorial technology, it can analyze a parameter’s impact on the system and their coordination effect. To verify the feasibility and effectiveness of the proposed method, the developed model was applied to a hypothetical case study for energy structure optimization under considering energy supply, SO2 emissions reduction, and environmental quality requirements. Multiple facilities, related environmental pollutants, and energy demand levels were taken into account. Moreover, the key factors of the system and their interaction effect were discovered. The results indicated that the developed method can resolve meritorious uncertainties in decision-making and analysis, generate effective management programming under multi-levels of the proposed energy and environmental systems. The method can be used for supporting the adjustment for allocating fossil fuels and renewable energy resources, analyzing the tradeoff between conflicting economic and environmental objectives and formulating the local policies.
Highlights
Along with the rapid development of economic, the energy demands are increasingly growing
A stochastic factorial energy systems management (SFESM) model will be proposed for optimal energy systems management under considering environmental pollutants emission reduction, energy resources consumption control, and multiple uncertainties
In energy systems management model, the TSP and chance constrained programming (CCP) methods are valid for tackling right-hand-side uncertainties such as energy resources availabilities that are presented as probability distributions
Summary
Along with the rapid development of economic, the energy demands are increasingly growing. The energy management processes and the related factors contain multiple uncertainties, such as distributing energy demand, planning power generation, or dealing emission reduction [1,2,3,4]. The stochastic optimization methods provide a powerful scheme to address the uncertain random information. It fails to distinguish the different degrees of importance and their relationships. A stochastic factorial energy systems management (SFESM) model will be proposed for optimal energy systems management under considering environmental pollutants emission reduction, energy resources consumption control, and multiple uncertainties. The SFESM model will be able to reflect interactions among multiple uncertainties in energy and environmental management systems. The results can be helpful for identifying energy allocation patterns, addressing conflicts between economic objectives and environment, as well as examining the linkage between existing policies and economic penalties
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