A sequential Monte Carlo model of the combined GB gas and electricity network
A sequential Monte Carlo model of the combined GB gas and electricity network
复制标题
DOI：
10.1016/j.enpol.2013.08.011
复制
发表时间：
2013-11
期刊：
影响因子：
9
通讯作者：
M. Chaudry;Jianzhong Wu;N. Jenkins
中科院分区：
文献类型：
--
作者：
M. Chaudry;Jianzhong Wu;N. Jenkins
为确定能源基础设施的可靠性，开发了GB天然气和电力联合网络的蒙特卡罗模型。该模型将天然气和电力网络集成到单个顺序蒙特卡罗模拟中。该模型最大限度地降低了天然气和电力网络的综合成本，包括天然气供应，天然气储存运营和发电。蒙特卡洛模型计算的可靠性指标，如损失的负载概率和预期的能量未送达的组合气和电网络。该工具的目的是促进综合能源系统的可靠性分析。该工具的应用程序通过案例研究，量化了对GB天然气和电力网络的可靠性的影响，给出了不确定性，如风的变化，天然气供应的可用性和停电的能源基础设施资产。分析是在一个典型的仲冬周进行的，假设在2020年的GB天然气和电力网络，满足欧洲可再生能源的目标。评估了GB气体存储容量增加一倍对能源系统可靠性的影响。结果突出了更大的天然气储存设施的价值，提高了GB能源系统的可靠性，考虑到各种能源的不确定性。
A Monte Carlo model of the combined GB gas and electricity network was developed to determine the reliability of the energy infrastructure. The model integrates the gas and electricity network into a single sequential Monte Carlo simulation. The model minimises the combined costs of the gas and electricity network, these include gas supplies, gas storage operation and electricity generation. The Monte Carlo model calculates reliability indices such as loss of load probability and expected energy unserved for the combined gas and electricity network. The intention of this tool is to facilitate reliability analysis of integrated energy systems. Applications of this tool are demonstrated through a case study that quantifies the impact on the reliability of the GB gas and electricity network given uncertainties such as wind variability, gas supply availability and outages to energy infrastructure assets. Analysis is performed over a typical midwinter week on a hypothesised GB gas and electricity network in 2020 that meets European renewable energy targets. The efficacy of doubling GB gas storage capacity on the reliability of the energy system is assessed. The results highlight the value of greater gas storage facilities in enhancing the reliability of the GB energy system given various energy uncertainties.