Demand-Side Energy Management Considering Price Oscillations for Residential Building Heating and Ventilation Systems

This paper presents an energy management method to optimally control the energy supply and the temperature settings of distributed heating and ventilation systems for residential buildings. The control model attempts to schedule the supply and demand simultaneously with the purpose of minimizing the...

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Bibliographic Details
Published in:IEEE transactions on industrial informatics Vol. 15; no. 8; pp. 4742 - 4752
Main Authors: Ma, Kai, Yu, Yangqing, Yang, Bin, Yang, Jie
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.08.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Adaptation models
Algorithms
Buildings
Computer simulation
Demand response (DR)
Electricity pricing
Energy management
Gradient algorithm
Heating
Heating and ventilation
Heating systems
HVAC
Optimization
Oscillations
Oscillators
Price oscillations
Residential buildings
Residential energy
Schedules
Supply & demand
Ventilation
ISSN:1551-3203, 1941-0050, 1941-0050
Online Access:Get full text
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Summary:This paper presents an energy management method to optimally control the energy supply and the temperature settings of distributed heating and ventilation systems for residential buildings. The control model attempts to schedule the supply and demand simultaneously with the purpose of minimizing the total costs. Moreover, the Predicted Percentage of Dissatisfied (PPD) model is introduced into the consumers' cost functions and the quadratic fitting method is applied to simplify the PPD model. An energy management algorithm is developed to seek the optimal temperature settings, the energy supply, and the price. Furthermore, due to the ubiquity of price oscillations in electricity markets, we analyze and examine the effects of price oscillations on the performance of the proposed algorithm. Finally, the theoretical analysis and simulation results both demonstrate that the proposed energy management algorithm with price oscillations can converge to a region around the optimal solution.
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ISSN:1551-3203
1941-0050
1941-0050
DOI:10.1109/TII.2019.2901306