Automated Multi-Zone Linear Parametric Black Box Modeling Approach for Building HVAC Systems

2015 ◽  
Author(s):  
Rohit H. Chintala ◽  
Bryan P. Rasmussen
Keyword(s):  
Large Scale ◽  
Model Development ◽  
Hvac Systems ◽  
Black Box ◽  
Modeling Method ◽  
Distributed Model ◽  
Control Algorithms ◽  
Model Parameters ◽  
Distributed Model Predictive Control ◽  
Automated Method

Optimal control algorithms such as distributed model predictive control (DMPC) offer tremendous potential in reducing energy consumption of building operations. Heating, ventilation and air-conditioning (HVAC) systems which form a major part of the building operations contain a large number of interconnected subsystems. One of the challenges associated with implementing DMPC is the development of reliable models of individual subsystems for prediction, especially for large scale systems. In this paper an automated method is proposed to develop linear parametric black box models for individual building HVAC subsystems. The modeling method proposed identifies the significant inputs, and the upstream and downstream neighbors of each subsystem before performing regression analysis to determine the model parameters. Automation of the model development makes the implementation of the model-based control algorithms much more feasible. The modeling method is then verified through an EnergyPLus model, and using data of a real office building.

scholarly journals Voltage Coordination via Communication in Large-Scale Multi-Area Power Systems. Part II: Simulation Results

2012 ◽  
Vol 433-440 ◽  
pp. 7183-7189
Author(s):  
Mohammad Moradzadeh ◽  
René Boel
Keyword(s):  
Power Systems ◽  
Power System ◽  
Electricity Market ◽  
Large Scale ◽  
Test System ◽  
Distributed Model ◽  
Future Evolution ◽  
Distributed Model Predictive Control ◽  
Control Actions ◽  
Simulation Results

This two-part paper deals with the coordination of the control actions in a network of many interacting components, where each component is controlled by independent control agents. As a case study we consider voltage control in large electric power systems where ever-increasing pressures from the liberalization and globalization of the electricity market has led to partitioning the power system into multiple areas each operated by an independent Transmission System Operator (TSO). Coordination of local control actions taken by those TSOs is a very challenging problem as poorly coordinated operation of TSOs may endanger the power system security by increasing the risk of blackouts. This second part of the paper presents simulation results on a 12-bus 3-area test system, using the distributed model predictive control paradigm in order to design a coordinating model-based feedback controller. Coordination requires that each agent has some information on what the future evolution of its power flows to and from its neighbors will be. It will be shown that how the communication between agents can avoid voltage collapse in circumstances where classical uncoordinated controllers fail.

scholarly journals Distributed Model Predictive Control over Multiple Groups of Vehicles in Highway Intelligent Space for Large Scale System

2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
Tang Xiaofeng ◽  
Gao Feng ◽  
Xu Guoyan ◽  
Ding Nenggen ◽  
Cai Yao ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Large Scale ◽  
Distributed Model ◽  
Large Scale System ◽  
Control Approach ◽  
Distributed Model Predictive Control ◽  
Intelligent Space ◽  
Multiple Groups ◽  
Information Framework

The paper presents the three time warning distances for solving the large scale system of multiple groups of vehicles safety driving characteristics towards highway tunnel environment based on distributed model prediction control approach. Generally speaking, the system includes two parts. First, multiple vehicles are divided into multiple groups. Meanwhile, the distributed model predictive control approach is proposed to calculate the information framework of each group. Each group of optimization performance considers the local optimization and the neighboring subgroup of optimization characteristics, which could ensure the global optimization performance. Second, the three time warning distances are studied based on the basic principles used for highway intelligent space (HIS) and the information framework concept is proposed according to the multiple groups of vehicles. The math model is built to avoid the chain avoidance of vehicles. The results demonstrate that the proposed highway intelligent space method could effectively ensure driving safety of multiple groups of vehicles under the environment of fog, rain, or snow.

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