期刊
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 14, 期 3, 页码 846-857出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2017.2702009
关键词
Demand response (DR); distributionally robust optimization; energy consumption scheduling; heating; ventilation and air conditioning (HVAC)
类别
资金
- National Natural Science Foundation of China [51428702]
- Engineering and Physical Science Research Council U.K. [EP/M507192/1]
- Engineering and Physical Sciences Research Council [EP/M507192/1] Funding Source: researchfish
- EPSRC [EP/M507192/1] Funding Source: UKRI
In this paper, the distributionally robust optimization approach (DROA) is proposed to schedule the energy consumption of the heating, ventilation and air conditioning (HVAC) system with consideration of the weather forecast error. The maximum interval of the outdoor temperature is partitioned into subintervals, and the proposed DROA constructs the ambiguity set of the probability distribution of the outdoor temperature based on the probabilistic information of these subintervals of historical weather data. The actual energy consumption will be adjusted according to the forecast error and the scheduled consumption in real time. The energy consumption scheduling of HVAC through the proposed DROA is formulated as a nonlinear problem with distributionally robust chance constraints. These constraints are reformulated to be linear and then the problem is solved via linear programming. Compared with the method that takes into account the weather forecast error based on the mean and the variance of historical data, simulation results demonstrate that the proposed DROA effectively reduces the electricity cost with less computation time, and the electricity cost is reduced compared with the traditional robust method.
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