Bidirectional optimal operation of smart building-to-grid systems

This paper proposes a novel bidirectional optimization of buildings integrated to the smart distribution grid, which possess potential benefits to the customers and utilities both. Mathematical models required for the optimal operations of buildings and grids are developed and a new method is proposed to obtain the solution of the bidirectional optimization. In this work, minimization of the cost of energy is chosen as an objective for the building load management, while the distribution utilities aim to increase load penetration by maximizing the load factor. Case studies are carried out based on actual data collected from an office building at Michigan Technological University, and using a standard distribution test feeder. Studies demonstrate that the proposed bidirectional optimization is beneficial to both the customer and the distribution grid as it shows significant saving in the energy costs and improvement on the system load factor.

[1]  Frauke Oldewurtel,et al.  Building modeling as a crucial part for building predictive control , 2013 .

[2]  Alberto L. Sangiovanni-Vincentelli,et al.  Building Efficiency and Sustainability in the Tropics ( SinBerBEST ) Title Model Predictive Control Approach to Online Computation of Demand-Side Flexibility of Commercial Buildings HVAC Systems for Supply Following Permalink , 2014 .

[3]  Mark Alexander,et al.  Evaluations of plug-in electric vehicle distribution system impacts , 2010, IEEE PES General Meeting.

[4]  J. E. Janssen,et al.  Ventilation for acceptable indoor air quality , 1989 .

[5]  Felix F. Wu,et al.  Efficient integer optimization algorithms for optimal coordination of capacitors and regulators , 1990 .

[6]  William Kersting,et al.  Distribution System Modeling and Analysis , 2001, Electric Power Generation, Transmission, and Distribution: The Electric Power Engineering Handbook.

[7]  S. K. Basu,et al.  A new algorithm for the reconfiguration of distribution feeders for loss minimization , 1992 .

[8]  Michael Sebek,et al.  Economical nonlinear model predictive control for building climate control , 2014, 2014 American Control Conference.

[9]  Alberto Sangiovanni-Vincentelli,et al.  Building Efficiency and Sustainability in the Tropics ( SinBerBEST ) Title Online Simultaneous State Estimation and Parameter Adaptation for Building Predictive , 2013 .

[10]  Kankar Bhattacharya,et al.  Optimal Operation of Distribution Feeders in Smart Grids , 2011, IEEE Transactions on Industrial Electronics.

[11]  Peng Xu,et al.  Demand reduction in building energy systems based on economic model predictive control , 2012 .

[12]  Mehdi Maasoumy.  Modeling and Optimal Control Algorithm Design for HVAC Systems in Energy Efficient Buildings , 2014 .

[13]  Manfred Morari,et al.  Use of model predictive control and weather forecasts for energy efficient building climate control , 2012 .

[14]  Alberto L. Sangiovanni-Vincentelli,et al.  Flexibility of Commercial Building HVAC Fan as Ancillary Service for Smart Grid , 2013, ArXiv.

[15]  Alberto L. Sangiovanni-Vincentelli,et al.  Building Efficiency and Sustainability in the Tropics ( SinBerBEST ) Title Selecting Building Predictive Control Based on Model Uncertainty Permalink , 2014 .

[16]  Wang Shengwei,et al.  Interactive building load management for smart grid , 2012, 2012 Power Engineering and Automation Conference.

[17]  Clark W. Gellings,et al.  Demand-side management: Concepts and methods , 1993 .

[18]  R. H. Liang,et al.  Dispatch of Main Transformer ULTC and Capacitors in a Distribution System , 2001, IEEE Power Engineering Review.

[19]  Philip Haves,et al.  Model predictive control for the operation of building cooling systems , 2010, Proceedings of the 2010 American Control Conference.

[20]  Mahdi Shahbakhti,et al.  Building Efficiency and Sustainability in the Tropics ( SinBerBEST ) Title Handling model uncertainty in model predictive control for energy efficient buildings Permalink , 2014 .

[21]  Bo Li,et al.  Economic model predictive control for building energy systems , 2011, ISGT 2011.

[22]  M. Pedrasa,et al.  Scheduling of Demand Side Resources Using Binary Particle Swarm Optimization , 2009, IEEE Transactions on Power Systems.

[23]  I. Roytelman,et al.  Modeling of local controllers in distribution network applications , 2000 .

[24]  Y. Deng,et al.  A Heuristic and Algorithmic Combined Approach for Reactive Power Optimization with Time-Varying Load Demand in Distribution Systems , 2002, IEEE Power Engineering Review.

[25]  Johan Löfberg,et al.  YALMIP : a toolbox for modeling and optimization in MATLAB , 2004 .

[26]  Friederich Kupzog,et al.  A generalized load management gateway coupling smart buildings to the grid , 2011, IEEE Africon '11.

[27]  V. Vittal,et al.  A Framework for Evaluation of Advanced Direct Load Control With Minimum Disruption , 2008, IEEE Transactions on Power Systems.

[28]  Gilbert M. Masters,et al.  Renewable and Efficient Electric Power Systems , 2004 .

[29]  Zechun Hu,et al.  Coordinated charging strategy for PEVs charging stations , 2012, PES 2012.