An integrated tool for assessing the demand profile flexibility

The purpose of this paper is to describe an integrated tool whose aim is to assess the residential demand profile flexibility through the control of space conditioning loads, mainly air conditioner and heat pump appliances. This assessment has been divided into two principal tasks - an estimation of the controllable load and a selection of the optimum load control strategy according to a target profile and a set of prefixed constraints. The tool also provides the aggregated load behavior, allowing a comparison between different load strategies. This tool can be applied from the customer's and the utility's side. An application example to a real environment is also presented.

[1]  A. Gabaldon,et al.  Class of Models for Load Management Application and Evaluaton Revisited , 1992, IEEE Power Engineering Review.

[2]  Carlos Henggeler Antunes,et al.  A multiple objective decision support model for the selection of remote load control strategies , 2000 .

[3]  J.A. Fuentes,et al.  Approach to multivariable predictive control applications in residential HVAC direct load control , 2000, 2000 Power Engineering Society Summer Meeting (Cat. No.00CH37134).

[4]  Chee-yee Chong,et al.  Statistical Synthesis of Physically Based Load Models with Applications to Cold Load Pickup , 1984, IEEE Transactions on Power Apparatus and Systems.

[5]  E. Agneholm,et al.  Cold load pick-up of residential load , 2000 .

[6]  Anil Pahwa,et al.  Modeling and System Identification of Residential Air Conditioning Load , 1985, IEEE Power Engineering Review.

[7]  J. Douglas Birdwell,et al.  A Physically-Based Low-Order Model for Aggregate Air Conditioner Loads , 1982, 1982 American Control Conference.

[8]  Man-loong Chan,et al.  Simulation-Based Load Synthesis Methodology for Evaluating Load-Management Programs , 1981, IEEE Transactions on Power Apparatus and Systems.

[9]  Fred Schweppe,et al.  Physically Based Modeling of Cold Load Pickup , 1981, IEEE Transactions on Power Apparatus and Systems.

[10]  J.A. Fuentes,et al.  Harmonic model of electronically controlled loads , 2000, 2000 Power Engineering Society Summer Meeting (Cat. No.00CH37134).

[11]  Nanming Chen,et al.  Air conditioner direct load control by multi-pass dynamic programming , 1995 .

[12]  Roland P. Malhamé,et al.  A physically-based computer model of aggregate electric water heating loads , 1994 .

[13]  E. Gomez,et al.  Application of smoothing techniques to solve the cooling and heating residential load aggregation problem , 2004 .

[14]  S. Rahman,et al.  Dispatch of Direct Load Control for Fuel Cost Minimization , 1986, IEEE Transactions on Power Systems.

[15]  Yuan-Yih Hsu,et al.  Dispatch of direct load control using dynamic programming , 1991 .

[16]  S. S. Venkata,et al.  ADSM-an automated distribution system modeling tool for engineering analyses , 1995 .

[17]  E. Gomez,et al.  OBJECT ORIENTED ARCHITECTURE OF A LOAD COMPOSITION IDENTIFICATION SYSTEM AT DISTRIBUTION LEVEL , 2002 .

[18]  T. Calloway,et al.  Physically-Based Model of Demand with Applications to Load Management Assessment and Load Forecasting , 1982, IEEE Transactions on Power Apparatus and Systems.

[19]  R. Adapa,et al.  Scheduling direct load control to minimize system operation cost , 1995 .

[20]  W. Härdle Smoothing Techniques: With Implementation in S , 1991 .

[21]  R. Malhamé,et al.  Electric load model synthesis by diffusion approximation of a high-order hybrid-state stochastic system , 1985 .

[22]  D. Brandt,et al.  A linear programming model for reducing system peak through customer load control programs , 1996 .

[23]  Anibal T. de Almeida,et al.  Advanced monitoring technologies for the evaluation of demand-side management programs , 1993 .

[24]  Hong-Tzer Yang,et al.  Direct load control using fuzzy dynamic programming , 1999 .

[25]  A. Molina,et al.  Implementation and assessment of physically based electrical load models: Application to direct load control residential programmes , 2003 .

[26]  A. I. Cohen,et al.  An optimization method for load management scheduling , 1988 .

[27]  Dariusz Czarkowski,et al.  Experimental test of a load model in the presence of harmonics , 1999 .

[28]  N. Navid-Azarbaijani,et al.  Realizing load reduction functions by aperiodic switching of load groups , 1996 .

[29]  Eric Hirst,et al.  Reliability Benefits of Price-Responsive Demand , 2002, IEEE Power Engineering Review.

[30]  G. W. Hart,et al.  Nonintrusive appliance load monitoring , 1992, Proc. IEEE.

[31]  W. M. Grady,et al.  Analysis of compensation factors influencing the net harmonic current produced by single-phase nonlinear loads , 1998, 8th International Conference on Harmonics and Quality of Power. Proceedings (Cat. No.98EX227).

[32]  Gerald B. Sheblé,et al.  Direct load control-A profit-based load management using linear programming , 1998 .