Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainti...Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainties of new energies and various types of loads in the IES.Accordingly,a robust optimal dispatching method for the IES based on a robust economic model predictive control(REMPC)strategy considering source-load power interval prediction is proposed.First,an operation model of the IES is established,and an interval prediction model based on the bidirectional long short-term memory network optimized by beetle antenna search and bootstrap is formulated and applied to predict the photovoltaic power and the cooling,heating,and electrical loads.Then,an optimal dispatching scheme based on REMPC is devised for the IES.The source-load interval prediction results are used to improve the robustness of the REPMC and reduce the influence of source-load uncertainties on dispatching.An actual IES case is selected to conduct simulations;the results show that compared with other prediction techniques,the proposed method has higher prediction interval coverage probability and prediction interval normalized averaged width.Moreover,the operational cost of the IES is decreased by the REMPC strategy.With the devised dispatching scheme,the ability of the IES to handle the dispatching risk caused by prediction errors is enhanced.Improved dispatching robustness and operational economy are also achieved.展开更多
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
为提高区域综合能源系统(Regional Integrated Energy System,RIES)优化运行的低碳经济性和控制精度,提出计及碳交易机制的多时间尺度优化调度策略。现有研究较少将阶梯式碳交易机制与使用新能源发电额外补贴的碳交易配额相结合,进一步...为提高区域综合能源系统(Regional Integrated Energy System,RIES)优化运行的低碳经济性和控制精度,提出计及碳交易机制的多时间尺度优化调度策略。现有研究较少将阶梯式碳交易机制与使用新能源发电额外补贴的碳交易配额相结合,进一步提高系统运行的低碳经济性。因此,在日前优化调度中,提出计及可再生能源发电的奖惩阶梯式碳交易机制,并采用差分进化混合粒子群算法对多维非线性模型进行求解。参考日前优化调度指令,根据模型预测控制思想实现日内滚动优化,以提高不确定性条件下区域综合能源系统优化调度的精确性。最后,通过算例分析验证了所提优化策略与算法的有效性和适用性。展开更多
基金supported by the National Key Research and Development Project of China(2018YFE0122200).
文摘Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainties of new energies and various types of loads in the IES.Accordingly,a robust optimal dispatching method for the IES based on a robust economic model predictive control(REMPC)strategy considering source-load power interval prediction is proposed.First,an operation model of the IES is established,and an interval prediction model based on the bidirectional long short-term memory network optimized by beetle antenna search and bootstrap is formulated and applied to predict the photovoltaic power and the cooling,heating,and electrical loads.Then,an optimal dispatching scheme based on REMPC is devised for the IES.The source-load interval prediction results are used to improve the robustness of the REPMC and reduce the influence of source-load uncertainties on dispatching.An actual IES case is selected to conduct simulations;the results show that compared with other prediction techniques,the proposed method has higher prediction interval coverage probability and prediction interval normalized averaged width.Moreover,the operational cost of the IES is decreased by the REMPC strategy.With the devised dispatching scheme,the ability of the IES to handle the dispatching risk caused by prediction errors is enhanced.Improved dispatching robustness and operational economy are also achieved.
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。
文摘为提高区域综合能源系统(Regional Integrated Energy System,RIES)优化运行的低碳经济性和控制精度,提出计及碳交易机制的多时间尺度优化调度策略。现有研究较少将阶梯式碳交易机制与使用新能源发电额外补贴的碳交易配额相结合,进一步提高系统运行的低碳经济性。因此,在日前优化调度中,提出计及可再生能源发电的奖惩阶梯式碳交易机制,并采用差分进化混合粒子群算法对多维非线性模型进行求解。参考日前优化调度指令,根据模型预测控制思想实现日内滚动优化,以提高不确定性条件下区域综合能源系统优化调度的精确性。最后,通过算例分析验证了所提优化策略与算法的有效性和适用性。
