Site demonstration and performance evaluation of MPC for a large chiller plant with TES for renewable energy integration and grid decarbonization

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