Heuristic model predictive control implementation to activate energy flexibility in a fully electric school building

被引:18
作者
Morovat, Navid [1 ]
Athienitis, Andreas K. [1 ]
Candanedo, Jose Agustin [2 ]
Nouanegue, Herve Frank [3 ]
机构
[1] Concordia Univ, Ctr Zero Energy Bldg Studies, Montreal, PQ, Canada
[2] Univ Sherbrooke, Dept Civil & Bldg Engn, Sherbrooke, PQ, Canada
[3] Hydroquebec Res Inst, Lab Energy Technol, Shawinigan, PQ, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Energy flexibility; Model predictive control; Building demand response; School buildings; DEMAND FLEXIBILITY; HEATING-SYSTEMS; STORAGE;
D O I
10.1016/j.energy.2024.131126
中图分类号
O414.1 [热力学];
学科分类号
摘要
This paper presents a heuristic model predictive control (MPC) methodology to activate energy flexibility in fully electric school buildings in cold climates to reduce electricity demand during peak demand periods of the electric grid. To streamline the implementation of MPC, the proposed approach employs grey-box archetypes, a clustering of weather conditions to identify typical scenarios and a limited number of possible setpoint profiles. A data-driven grey-box approach is used to create archetype models for different thermal zones in a typical school building; this approach enables rapid development and requires much less calibration data than black-box models. A third-order resistance-capacitance thermal network for zones with convective heating and a fourthorder model for zones with radiant floor heating are developed and calibrated using measured data from an all-electric school building in Que<acute accent>bec, Canada. The weather data are clustered into several categories, representing different weather conditions (6 clusters representing two ambient temperature ranges and three solar radiation ranges). The heuristic MPC strategy uses predefined optimal setpoint profiles for each cluster and weather prediction one day ahead to shift the building load from on-peak to off-peak hours. For each heuristic MPC scenario, the model runs a simulation using forecast weather data to quantify and activate energy flexibility in response to grid requirements. The developed MPC framework was implemented in the school used as the case study. Ten classrooms are investigated, with six using the MPC and four as a reference case with the reactive control system and default zone setpoint profiles. Results indicate that the school building can provide between 47% and 95% energy flexibility (load shifting relative to reference) during on-peak hours and up to 44% electricity cost reduction while satisfying acceptable temperature constraints. By implementing the proposed MPC, energy flexibility of 32 W/m2 of floor area for the zones with a convective heating system and 65 W/m2 of floor area for the zones with radiant heating can be achieved during a demand response event. The proposed strategy can be generalized and replicated in other school buildings.
引用
收藏
页数:18
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