Site demonstration and performance evaluation of MPC for a large chiller plant with TES for renewable energy integration and grid decarbonization. (1st September 2022)

• Record Type: Journal Article
• Authors: Kim, Donghun; Wang, Zhe; Brugger, James; Blum, David; Wetter, Michael; Hong, Tianzhen; Piette, Mary Ann
• Is Part Of: Applied energy. Volume 321(2022)
• Publication Date: 2022-09-01
• Subjects: MPC demonstration -- Building optimal control -- Model predictive control -- District energy system -- Carbon reduction -- Renewable energy; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2022.119343
• Languages: English
• ISSNs: 0306-2619

Abstract

Abstract: Thermal energy storage (TES) for a cooling plant is a crucial resource for load flexibility. Traditionally, simple, heuristic control approaches, such as the storage priority control which charges TES during the nighttime and discharges during the daytime, have been widely used in practice, and shown reasonable performance in the past benefiting both the grid and the end-users such as buildings and district energy systems. However, the increasing penetration of renewables changes the situation, exposing the grid to a growing duck curve, which encourages the consumption of more energy in the daytime, and volatile renewable generation which requires dynamic planning. The growing pressure of diminishing greenhouse gas emissions also increases the complexity of cooling TES plant operations as different control strategies may apply to optimize operations for energy cost or carbon emissions. This paper presents a model predictive control (MPC), site demonstration and evaluation results of optimal operation of a chiller plant, TES and behind-meter photovoltaics for a campus-level district cooling system. The MPC was formulated as a mixed-integer linear program for better numerical and control properties. Compared with baseline rule-based controls, the MPC results show reductions of the excess PV power by around 25%, of the greenhouse gas emission by 10%, and of peak electricity demand by 10%. Highlights: Experimentally demonstrated an MPC for a campus-scale cooling plant system. Present MPC's real performance for renewable integration and decarbonization. First MPC demonstration in response to a real time grid carbon signal. Achieved reductions of the excess PV power by 25%, and of the CO2 emission by 10% Share lessons-learned during the demonstration to facilitate MPC deployment.