【Advances in Applied Energy】气电能源系统脱碳优化规划

学术   科学   2024-10-20 18:30   美国  

原文信息:

Optimal gas-electric energy system decarbonization planning

原文链接:

https://www.sciencedirect.com/science/article/pii/S266679242200004X

Highlights

• Novel multi-period planning framework for decarbonization of integrated gas-electric energy systems.

• Customer appliance stock investment optimization enables low-cost substitution of final energy demands.

• Local gas quality restrictions may limit blending of hydrogen for direct-use in buildings.

• Mixed-integer nonlinear optimization implemented in high performance computing setting on a synthetic test case.

摘要

       随着能源公司实施气候变化缓解政策,系统规划者需要实现可承担的减排战略。电力和天然气系统的协调规划将允许协同投资,以解决跨部门运营限制、净零排放燃料的竞争性使用以及能源运输公司能源需求的变化等问题。在这项研究中,开发了一个新的优化程序,该程序找到了基础设施扩展或减少燃气和电力系统的成本最小化组合,以满足特定行业的排放限制。除了能源供应资源以外,所提出的框架还允许对终端设备库存进行集中规划,以便在发生故障或过早更换时,在燃气和电气设备之间进行切换。所提出的模型用于模拟与24节点电力系统测试网络耦合的基准24管道燃气网络的案例研究场景。结果表明,80%以上的核心天然气需求的电气化是建模能源系统最低成本解决方案的组成部分。尽管采用这种替代方案,燃气系统仍能为电气化困难的客户提供服务,并能在电力需求高峰时向发电机输送净零排放气体。限制燃气设备的电气化将增加对电改气技术的依赖,并在2040年增加15%的年度成本。忽视对掺氢管道的限制,可能会产生一个误导性结果,即依赖于大于50%的氢气混合分数。在所有情况下,作者发现在脱碳转型期间,输送天然气的平均成本增加了近5倍,这突出了未来研究成本分配策略以确保公平能源转型的重要性。

      更多关于" Decarbonization "的研究详见:

https://www.sciencedirect.com/search?qs=Decarbonization&pub=Advances%20in%20Applied%20Energy&cid=777797

Abstract

As energy utilities implement climate change mitigation policies, system planners require strategies for achieving affordable emissions reductions. Coordinated planning of electric power and natural gas systems will allow synergistic investments to address cross-sector operational constraints, competing uses for net-zero emissions fuels, and shifts in energy demands across energy carriers. In this study, we develop a novel optimization program that finds the cost-minimizing mix of infrastructure expansion or reduction across gas and electric systems to satisfy sector-specific emissions constraints. Alongside energy supply resources, our framework allows for central-planning of end-use equipment stocks to allow switching between gas and electric appliances upon failure or premature replacement. The proposed model is used to simulate case study scenarios for a benchmark 24-pipe gas network coupled to a 24-node power system test network. We find that electrification of greater than 80% of core gas demands is a component of the least-cost solution for modeled energy systems. Despite this substitution, the gas system is maintained to service difficult-to-electrify customers and to deliver net-zero emissions gas to electricity generators in times of peak electricity demand. Restricting electrification of gas appliances increases reliance on power-to-gas technologies and increases annual costs by 15% in 2040. Neglecting constraints on pipeline blending of hydrogen can produce a misleading result that relies on hydrogen blend fractions of greater than 50%. In all cases, we find the average costs of delivered gas increase nearly 5-fold across the decarbonization transition, highlighting the importance of future work investigating cost-allocation strategies for ensuring an equitable energy transition.

Keywords

Integrated gas-electric system

Capacity expansion

Decarbonization

Net-zero energy system

System planning

Optimization

Multi-period

Graphics


Fig. 2. Schematic illustration of integrated gas-electric energy system nodes.

Fig. 5. Schematic illustration of the case study scenarios explored in this analysis and the constraints added or removed from Eq. (1).

Fig. 6. Comparative results of time-extended planning optimization of a Mountain Northwest (left) and Coastal Pacific (right) integrated energy system for capacity (top), generation (middle), and gas production (bottom).

Fig. 8. Comparative results of appliance stocks for a Mountain Northwest (left) and Coastal Pacific (right) integrated energy system.

Fig. 12. Comparative results for increasing degrees of hydrogen blend limits ranging from unconstrained hydrogen blending (left), to hydrogen blend fractions constrained on an annual, system-wide basis (center), to blend limits imposed across daily time scales at the nodal level (left).

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