根据用户侧的冷热电负荷预测、调度周期内用户需求,以及各能源转换、储能设备之间的配合与出力约束等条件,提出基于可再生能源发电的不确定性惩罚和考虑碳排放与绿色证书交易,以整体调度费用最小为目标的日前调度策略。考虑碳排放及可...根据用户侧的冷热电负荷预测、调度周期内用户需求,以及各能源转换、储能设备之间的配合与出力约束等条件,提出基于可再生能源发电的不确定性惩罚和考虑碳排放与绿色证书交易,以整体调度费用最小为目标的日前调度策略。考虑碳排放及可再生能源消纳与电价、碳排放配额和可再生能源配额的配合,减少电网购电和碳排放,降低调度费用。针对综合能源系统日前经济调度模型的混合非线性整数特性,进行线性化处理,建立日前经济调度混合整数线性规划(mixed integer linear programming,MILP)模型。通过对典型日负荷数据设置调度场景,对3种场景的机组配合出力情况及调度成本进行分析,结果验证所提日前优化调度模型在降低商服中心调度成本和碳排放等方面的有效性。展开更多
The scheduling utility plays a fundamental role in addressing the commuting travel behaviours. A new scheduling utility,termed as DMRD-SU, was suggested based on some recent research findings in behavioural economics....The scheduling utility plays a fundamental role in addressing the commuting travel behaviours. A new scheduling utility,termed as DMRD-SU, was suggested based on some recent research findings in behavioural economics. DMRD-SU admitted the existence of positive arrival-caused utility. In addition, besides the travel-time-caused utility and arrival-caused utility, DMRD-SU firstly took the departure utility into account. The necessity of the departure utility in trip scheduling was analyzed comprehensively,and the corresponding individual trip scheduling model was presented. Based on a simple network, an analytical example was executed to characterize DMRD-SU. It can be found from the analytical example that: 1) DMRD-SU can predict the accumulation departure behaviors at NDT, which explains the formation of daily serious short-peak-hours in reality, while MRD-SU cannot; 2)Compared with MRD-SU, DMRD-SU predicts that people tend to depart later and its gross utility also decreases faster. Therefore,the departure utility should be considered to describe the traveler's scheduling behaviors better.展开更多
文摘根据用户侧的冷热电负荷预测、调度周期内用户需求,以及各能源转换、储能设备之间的配合与出力约束等条件,提出基于可再生能源发电的不确定性惩罚和考虑碳排放与绿色证书交易,以整体调度费用最小为目标的日前调度策略。考虑碳排放及可再生能源消纳与电价、碳排放配额和可再生能源配额的配合,减少电网购电和碳排放,降低调度费用。针对综合能源系统日前经济调度模型的混合非线性整数特性,进行线性化处理,建立日前经济调度混合整数线性规划(mixed integer linear programming,MILP)模型。通过对典型日负荷数据设置调度场景,对3种场景的机组配合出力情况及调度成本进行分析,结果验证所提日前优化调度模型在降低商服中心调度成本和碳排放等方面的有效性。
基金Projects(71131001,71271023,71471014)supported by National Natural Science Foundation of ChinaProject(2012CB725403)supported by National Basic Research Program of ChinaProject(2011AA110303)supported by National High Technology Research and Development Program of China
文摘The scheduling utility plays a fundamental role in addressing the commuting travel behaviours. A new scheduling utility,termed as DMRD-SU, was suggested based on some recent research findings in behavioural economics. DMRD-SU admitted the existence of positive arrival-caused utility. In addition, besides the travel-time-caused utility and arrival-caused utility, DMRD-SU firstly took the departure utility into account. The necessity of the departure utility in trip scheduling was analyzed comprehensively,and the corresponding individual trip scheduling model was presented. Based on a simple network, an analytical example was executed to characterize DMRD-SU. It can be found from the analytical example that: 1) DMRD-SU can predict the accumulation departure behaviors at NDT, which explains the formation of daily serious short-peak-hours in reality, while MRD-SU cannot; 2)Compared with MRD-SU, DMRD-SU predicts that people tend to depart later and its gross utility also decreases faster. Therefore,the departure utility should be considered to describe the traveler's scheduling behaviors better.
