A general model for the optimization of energy supply systems of buildings

Abstract In this paper, a general model for the optimization of the energy supply systems of buildings is proposed. The model is based on a general superstructure that allows to include all the existing and future technologies, covering heating, domestic hot water, cooling and electricity. The model is linked to a Mixed Integer Linear Programming (MILP) problem that allows the selection of equipment and its operation, enabling the minimization of the annual cost for a set of constraints imposed by the designer, such as a Non-Renewable Primary Energy (NRPE) consumption limit. The model has been applied to a case study consisting of a domestic building located in Bilbao (Northern Spain). 13 different technologies were taken under consideration together with the specific conditions of the Spanish context. Three different objectives were determined: (i) the optimal cost; (ii) the Zero Energy Building (ZEB); and (iii) the ZEB′, an alternative ZEB where the whole electricity consumption is considered for the calculation of the NRPE. The 3 cases were compared and analyzed and, finally, a parametric evaluation was carried out, setting the aspects that limit the feasibility of low energy buildings: economic feasibility and physical constraints such as roof availability for renewables.

[1]  Weijun Gao,et al.  Optimal option of distributed generation technologies for various commercial buildings , 2009 .

[2]  Eike Musall,et al.  Implications of weighting factors on technology preference in net zero energy buildings , 2014 .

[3]  Hongbo Ren,et al.  A MILP model for integrated plan and evaluation of distributed energy systems , 2010 .

[4]  You-Yin Jing,et al.  Optimization of capacity and operation for CCHP system by genetic algorithm , 2010 .

[5]  Tarek Y. ElMekkawy,et al.  Optimal design of hybrid renewable energy systems in buildings with low to high renewable energy ratio , 2015 .

[6]  Edoardo Amaldi,et al.  A detailed MILP optimization model for combined cooling, heat and power system operation planning , 2014 .

[7]  Cristina Becchio,et al.  The cost-optimal methodology for the energy retrofit of an ex-industrial building located in Northern Italy , 2016 .

[8]  A. Boies,et al.  Distributed energy resource system optimisation using mixed integer linear programming , 2013 .

[9]  Laurence A. Wolsey,et al.  Integer and Combinatorial Optimization , 1988 .

[10]  M. Hamdy,et al.  A multi-stage optimization method for cost-optimal and nearly-zero-energy building solutions in line with the EPBD-recast 2010 , 2013 .

[11]  Lazaros G. Papageorgiou,et al.  A mathematical programming approach for optimal design of distributed energy systems at the neighbourhood level , 2012 .

[12]  W. Beckman,et al.  Estimation of degree-days and ambient temperature bin data from monthly-average temperatures , 1983 .

[13]  Gerald B. Sheblé,et al.  Unit commitment literature synopsis , 1994 .

[14]  Salvatore Carlucci,et al.  Assessing gaps and needs for integrating building performance optimization tools in net zero energy buildings design , 2013 .

[15]  Jianlei Niu,et al.  Optimal building envelope design based on simulated performance: History, current status and new potentials , 2016 .

[16]  Ross Baldick,et al.  The generalized unit commitment problem , 1995 .

[17]  Gerard Doorman,et al.  Cost-optimal energy system design in Zero Energy Buildings with resulting grid impact: A case study of a German multi-family house , 2016 .

[18]  Mads Pagh Nielsen,et al.  A cost optimization model for 100% renewable residential energy supply systems , 2012 .

[19]  Gerardo Maria Mauro,et al.  Multi-stage and multi-objective optimization for energy retrofitting a developed hospital reference building: A new approach to assess cost-optimality , 2016 .

[20]  Enrico Fabrizio,et al.  Energy systems in cost-optimized design of nearly zero-energy buildings , 2016 .

[21]  N.P. Padhy,et al.  Unit commitment-a bibliographical survey , 2004, IEEE Transactions on Power Systems.

[22]  Gevork B. Gharehpetian,et al.  Optimization of distributed generation capacities in buildings under uncertainty in load demand , 2013 .

[23]  Peter B. Luh,et al.  Design optimization of a distributed energy system through cost and exergy assessments , 2017 .

[24]  W. Beckman,et al.  Solar Engineering of Thermal Processes , 1985 .

[25]  M. Jünger,et al.  50 Years of Integer Programming 1958-2008 - From the Early Years to the State-of-the-Art , 2010 .