Optimal Dispatch Controller For Fuel Cell Integrated Building

Conference Year

July 2018

Authors

Yashen Lin, National Renewable Energy Laboratory, United States of AmericaFollow
Dustin McLarty, School of Mechanical and Materials Engineering, Washington State UniversityFollow
Annabelle Pratt, National Renewable Energy Laboratory, United States of AmericaFollow
Brian Ball, National Renewable Energy Laboratory, United States of AmericaFollow
Gregor Henze, National Renewable Energy Laboratory, United States of America; Department of Civil, Environmental, and Architectural Engineering, University of Colorado BoulderFollow
Genevieve Saur, National Renewable Energy Laboratory, United States of AmericaFollow

Keywords

building control, fuel cell, model predictive control, ancillary service, energy storage

Abstract

Buildings contribute to around 40% of the total energy consumption in the US. Improvements to building operation offer substantial economic benefits and emissions reductions. Opportunities arise as more renewable energy sources are integrated into the power grid, where the inherent flexibility that buildings can provide become valuable assets for grid services. Stationary fuel cells providing combined heat and power (CHP) add more flexibility to building operation, where both significant electrical and thermal loads need to be met. As the technology matures, improved fuel cell responsiveness allows for advanced dynamic applications to maximize their utility within the building system. The integration of fuel cells and battery energy storage systems (BESS) to buildings presents several challenges and opportunities for optimal management of resources. In this work, we develop an optimal dispatch controller for real-time management of a fuel cell-integrated building system. The objective is to minimize building operating costs and maximizing profits from participating in the power grid ancillary service markets, while maintaining occupant comfort. To achieve this objective, we develop a specifically tailored model predictive control (MPC) algorithm to schedule the operation of a fuel cell, a BESS, and building equipment in response to the time-of-use electricity tariff. The controller determines the optimal schedules over a 24-hour horizon according to weather and building load forecast. This optimal schedule is implemented for a 1-hour period. Measurements from the fuel cell-integrated building are collected and used to update the optimization for the next 24-hour period. This recursive update ensures that the algorithm is robust to forecast errors and model mismatch. The effectiveness of the proposed algorithm is demonstrated with a co-simulation where the building is represented as a high-fidelity model in the EnergyPlus building simulation program and the optimal control is implemented in Matlab. The proposed optimal dispatch controller provides a tool to manage the real-time operation of a fuel cell-integrated building. It also helps building operators and the fuel cell industry assess the potential benefits of integrating stationary fuel cells with buildings.