Micro-sources design of an intelligent building integrated with micro-grid☆

Abstract Intelligent buildings are the trend of future buildings, as well as, micro-grids are important scenarios of smart grid under going. An intelligent building integrated with micro-grid can fit the much comfort and low energy consumption targets better. However, the output power of micro-sources in the micro-grid for intelligent building application is stochastic, uncertain and uncontrollable. Thus, micro-sources design of an intelligent building integrated with micro-grid is a significant issue. Therefore, a mathematical model is proposed to optimize the capacities of micro-resources, which can harvest green energy from renewable energy resources (RERs) as much as possible. In the presented model, energy cost coefficient (ECC) is set as the minimization objective function, F, which is defined as the ratio between energy cost of intelligent building and the output energy of RESs. It is should be noted that ECC is different from conventional optimum objective to minimize the cost of whole project, C. As a result, a multi-objective model associated with F and C is also discussed to satisfy different requirements and targets of numerous users. A numerical example is utilized to validate the feasibility of the proposed approach. Simultaneously, the Pareto fronts of the multi-objective model are obtained using Linear INteractive and General Optimizer (LINGO).

[1]  S. M. Halpin,et al.  Determination of Allowable Penetration Levels of Distributed Generation Resources Based on Harmonic Limit Consideration , 2002, IEEE Power Engineering Review.

[2]  Lingfeng Wang,et al.  Multi-agent intelligent controller design for smart and sustainable buildings , 2010, 2010 IEEE International Systems Conference.

[3]  Lingfeng Wang,et al.  Multi-Objective Particle Swarm Optimization for decision-making in building automation , 2011, 2011 IEEE Power and Energy Society General Meeting.

[4]  Thomas Weng,et al.  Understanding the role of buildings in a smart microgrid , 2011, 2011 Design, Automation & Test in Europe.

[5]  Gurjeet Dhesi,et al.  Optimising the installation costs of renewable energy technologies in buildings: A Linear Programmin , 2011 .

[6]  Tomonobu Senjyu,et al.  Optimal Operation by Controllable Loads Based on Smart Grid Topology Considering Insolation Forecasted Error , 2011, IEEE Transactions on Smart Grid.

[7]  Bin Ai,et al.  Computer-aided design of PV/wind hybrid system , 2003 .

[8]  Kalyanmoy Deb,et al.  Multi-objective optimization using evolutionary algorithms , 2001, Wiley-Interscience series in systems and optimization.

[9]  S. Gomaa,et al.  Design and analysis of photovoltaic and wind energy hybrid systems in Alexandria, Egypt , 1995 .

[10]  Ibrahim Dincer,et al.  Thermodynamic analyses of an integrated PEMFC–TEARS-geothermal system for sustainable buildings , 2012 .

[11]  Qing-Shan Jia,et al.  Energy-Efficient Buildings Facilitated by Microgrid , 2010, IEEE Transactions on Smart Grid.

[12]  Eike Musall,et al.  Zero Energy Building A review of definitions and calculation methodologies , 2011 .

[13]  Ryuichiro Goto,et al.  Hybrid utilization of renewable energy and fuel cells for residential energy systems , 2011 .

[14]  Lan Xiao,et al.  A heat pipe photovoltaic/thermal (PV/T) hybrid system and its performance evaluation , 2011 .

[15]  Lingfeng Wang,et al.  A heuristic economic optimizer with emission constraints for building energy management , 2011, 2011 North American Power Symposium.

[16]  Athula D. Rajapakse,et al.  Microgrids research: A review of experimental microgrids and test systems , 2011 .

[17]  C. Singh,et al.  Multicriteria Design of Hybrid Power Generation Systems Based on a Modified Particle Swarm Optimization Algorithm , 2009, IEEE Transactions on Energy Conversion.

[18]  Robert H. Lasseter Microgrids and Distributed Generation , 2007 .

[19]  Saifur Rahman,et al.  Green power: What is it and where can we find it? , 2003 .

[20]  Ian Dobson,et al.  Evidence for self-organized criticality in a time series of electric power system blackouts , 2004, IEEE Transactions on Circuits and Systems I: Regular Papers.

[21]  Nirmal-Kumar C. Nair,et al.  Battery energy storage systems: Assessment for small-scale renewable energy integration , 2010 .

[22]  Lingfeng Wang,et al.  Customer-centered control system for intelligent and green building with heuristic optimization , 2011, 2011 IEEE/PES Power Systems Conference and Exposition.

[23]  Giri Venkataramanan,et al.  Generation unit sizing and cost analysis for stand-alone wind, photovoltaic, and hybrid wind/PV systems , 1998 .

[24]  Qingqian Chen,et al.  Review on blackout process in China Southern area main power grid in 2008 snow disaster , 2009, 2009 IEEE Power & Energy Society General Meeting.

[25]  S. Walker Building mounted wind turbines and their suitability for the urban scale—A review of methods of estimating urban wind resource , 2011 .

[26]  Ying Huang,et al.  Building-integrated photovoltaics (BIPV) in architectural design in China , 2011 .

[27]  Saifur Rahman,et al.  A decision support technique for the design of hybrid solar-wind power systems , 1998 .