by The integration of variable renewable energy sources into power grids presents a challenge in balancing electricity supply with demand. To address this issue and maintain grid reliability while reducing electricity costs, demand response strategies have become essential. Commercial buildings, which comprise 37% of all electrical load in the United States, offer a significant opportunity to implement impactful demand response programs.
Currently, the potential of commercial buildings as a grid balancing resource remains largely untapped. However, a team of researchers led by Johanna Mathieu, an associate professor of electrical engineering and computer science at the University of Michigan, aims to change this. In a groundbreaking development, the team has presented an open dataset in the Journal of Dynamic Systems, Measurement, and Control, which provides valuable insights into the role that commercial buildings can play in balancing the grid.
In particular, the team focused on Heating, Ventilating, and Air Conditioning (HVAC) systems as an ideal flexible load for demand response improvement. HVAC systems account for nearly half of the power consumption in commercial buildings, making them a prime target for optimizing demand response. Additionally, commercial buildings’ high thermal inertia allows for short-term alterations in HVAC system power consumption without significantly affecting building temperatures.
To effectively achieve grid balancing, closed-loop control systems that incorporate feedback from the HVAC system are crucial. However, most building automation systems, which are used to control and monitor various variables, do not collect power measurements from HVAC system components. Whole-building electric meters, on the other hand, only measure power every 15 minutes, which is too infrequent for effective grid balancing. As a result, a clear understanding of HVAC system dynamics and responses is lacking.
To bridge this gap and enhance the availability of real-world demand response data, the research team developed the Sub-metered HVAC Implemented for Demand Response (SHIFDR) dataset. This comprehensive dataset contains power measurements from HVAC system components collected over five years from 14 University of Michigan campus buildings, encompassing both typical operation and demand response events.
The SHIFDR dataset provides researchers and practitioners with valuable insights into the dynamics and responses of HVAC systems in commercial buildings during demand response events. By analyzing this data, stakeholders can identify strategies to maximize the potential of commercial buildings for grid balancing, renewables integration, reliability, and resilience.
The implications of this development are significant. Leveraging the full potential of commercial buildings in demand response programs can enhance grid stability and reduce the strain on power grids caused by peak electricity demands. Furthermore, demand response programs focusing on commercial buildings can contribute to the successful integration of renewable energy sources into power grids, ultimately promoting a sustainable and resilient energy system.
Mathieu and her team have presented a game-changing opportunity for the energy industry. With the SHIFDR dataset, researchers and practitioners can explore innovative approaches to harness the power of commercial buildings and optimize grid balancing efforts. As the journey towards a cleaner, more sustainable energy future continues, demand response strategies centered around commercial buildings will play a vital role in achieving this vision.
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1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
