Dynamic Scheduling of a Photovoltaic–Storage Office Building with Heating, Ventilation, and Air-Conditioning and Electric-Vehicle Flexibility

Abstract

High photovoltaic (PV) penetration can create hourly mismatches among office-building demand, renewable generation, electricity prices, and grid carbon intensity. This study develops a reproducible, deterministic, time-coupled day-ahead mixed-integer linear programming model for a predetermined PV–battery energy storage system (BESS), simplified heating, ventilation, and air-conditioning (HVAC) load response, and electric-vehicle (EV) charging/vehicle-to-building operation. Separate charging and discharging variables, binary operating states, a cyclic 50% BESS terminal state of charge, and PV- and grid-origin battery accounts eliminate simultaneous operation, initial-energy depletion, and grid-to-BESS-to-grid arbitrage. Five scenarios and five one-factor-at-a-time sensitivity families are independently re-optimized for a Suzhou office-building case. For the selected summer day, Scenario 2 costs 1974.04 CNY. Scenario 3 costs 1974.73 CNY before DR revenue, earns 323.85 CNY, and has a net cost of 1650.88 CNY. Its grid import and grid-side emissions are 1.27% and 1.28% below Scenario 2, respectively, whereas its pre-incentive cost is 0.04% higher. The corrected DR formulation leaves the reported optima unchanged within 2.6 × 10−9. The maximum hourly balance residual across all runs is 1.3 × 10−9 kW.