A5048764465- Building Energy and Comfort Optimization
- Advanced Control Systems Optimization
- Process Optimization and Integration
- Infection Control and Ventilation
- Smart Grid Energy Management
- Fault Detection and Control Systems
- Energy Efficiency and Management
- Noise Effects and Management
- Wind and Air Flow Studies
- Microbial Metabolic Engineering and Bioproduction
- Control Systems and Identification
- Indoor Air Quality and Microbial Exposure
- Environmental Impact and Sustainability
- Iterative Learning Control Systems
- COVID-19 epidemiological studies
- Advanced Multi-Objective Optimization Algorithms
- Adaptive Control of Nonlinear Systems
- Electric Vehicles and Infrastructure
- Image and Video Quality Assessment
- Energy Load and Power Forecasting
- Scheduling and Optimization Algorithms
- Refrigeration and Air Conditioning Technologies
- Spreadsheets and End-User Computing
Johnson Controls (United States)
2020-2023
Johnson Controls (Switzerland)
2020
University of Wisconsin–Madison
2015-2019
With the increasing prevalence of variable-supply electricity production, dynamic market structures, including time-varying prices and/or peak demand charges are becoming more common for consumers. This framework requires consumers to consider both amount (i.e., energy) consumed throughout day as well maximum rate purchase power) over a given period, typically month. Because this complexity, online optimization techniques such economic model predictive control (MPC) natural tool use minimize...
Although recent research has suggested model predictive control as a promising solution for minimizing energy costs of commercial buildings, advanced systems have not been widely deployed in practice. Large-scale implementations, including industrial complexes and university campuses, may contain thousands air handler regions each with tens zones. A single centralized system these applications is desirable. In this paper, we propose distributed to economically optimize temperature regulation...
In this paper, we propose a mixed-integer linear program to economically optimize equipment usage in central heating/cooling plant subject time-of-use and demand charges for utilities. The optimization makes both discrete on/off continuous load decisions while determining utilization of thermal energy storage systems. This formulation allows simultaneous heating cooling subsystems, which interact directly when heatrecovery chillers are present. Nonlinear models approximated as...
It has been established that combinations of increased ventilation, improved filtration, and other HVAC techniques can reduce the likelihood airborne disease transmission in buildings. However, with only qualitative guidance, it is difficult for building managers to make informed decisions. Furthermore, possible actions almost always require additional energy consumption, which generally not well characterized. To address this knowledge gap, we propose simplified physics-based models be used...
Abstract This paper addresses the problem of system identification for heating, ventilation, and air conditioning (HVAC) systems using a relatively small amount data zone under consideration, by leveraging larger datasets similar zones. To this end, hybrid machine learning approach is developed where pre‐trained recurrent neural network (RNN) model, trained on large from representative zone, leveraged to build models other zones smaller data. achieved developing model that integrates RNN...
Because of its ability to handle multivariable systems, model predictive control (MPC) is well-suited large and complicated industrial processes. Such systems are affected by unmodeled disturbances, many have actuators that can take on only a discrete set values. Both these characteristics be addressed directly within nominal MPC theory. In this paper we show, under standard assumptions, suboptimal with mixed continuous/discrete inherently robust. For sufficiently small both robust...
It has been established that combinations of increased ventilation, improved filtration, and other HVAC techniques can reduce the likelihood airborne disease transmission in buildings. However, with only qualitative guidance, it is difficult for building managers to make informed decisions. Furthermore, possible actions almost always require additional energy consumption, which generally not well characterized. To address this knowledge gap, we propose simplified physics-based models be used...