Modelling and optimization of residential heating system using random neural networks

Abbas Javed*, Hadi Larijani, Ali Ahmadinia, Rohinton Emmanuel

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

In this paper, a novel random neural network (RNN) model based optimization process for radiator-based heating system is proposed to maintain a comfortable indoor environment in a living room of a single storey residential building. The predictive model of the living room is developed by training a feed forward RNN and then optimisation algorithms are used to calculate the optimal flowrate for the radiators. Three optimisation algorithms: Genetic Algorithm (GA), Particle swarm optimization (PSO) algorithm, and Sequential quadratic programming (SQP) optimization algorithm are investigated to calculate the optimal control input. The accuracy of the control scheme is verified by simulations using International Building Physics Toolbox (IBPT). It was found that mean squared error (MSE) for PSO is 38.87% less than GA and the MSE for PSO is 21.19% less than SQP. The RNN model based optimization technique is further compared with model predictive controller (MPC) designed for the radiator based heating system. The comparison results showed that the proposed RNN technique minimize the energy consumption and maintains accurate room thermal comfort according to the predicted mean vote (PMV) based setpoints.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Control Science and Systems Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages90-95
Number of pages6
ISBN (Electronic)9781479963973
ISBN (Print)9781479963966
DOIs
Publication statusPublished - 27 Aug 2015
EventIEEE International Conference on Control Science and Systems Engineering - Yantai, China
Duration: 29 Dec 201430 Dec 2014

Publication series

NameProceedings - 2014 IEEE International Conference on Control Science and Systems Engineering, CCSSE 2014

Conference

ConferenceIEEE International Conference on Control Science and Systems Engineering
Abbreviated titleCCSSE 2014
Country/TerritoryChina
CityYantai
Period29/12/1430/12/14

Keywords

  • genetic algorithm
  • particle swarm optimization
  • random neural networks
  • sequential quadratic programming

ASJC Scopus subject areas

  • Control and Systems Engineering

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