Multi criteria dynamic design optimization of a small scale distributed energy system

The aim of this paper is to analyze the mutual interdependencies and trade-offs between heat storage and district heating network considering economic and ecological aspects. Therefore, a MILP (mixed integer linear programming) problem of a distributed energy system is formulated with a weighted multi-criteria objective function including profit and operational CO2 emissions. The considered components include CHP (combined heat and power) units of three different types, a thermal storage facility, a boiler, and district heating pipelines. In a single optimization step placement, quantity and capacity of all components as well as their operation is determined. The computed designs as well as the operation of the energy system are compared under varying weightings and different technology scenarios. We also conduct a sensitivity analysis of the investment costs associated with heat storage and of the piping costs for the district heating network. The results favor the construction of heat storage devices over a district heating network. This applies to both environmental impact and cost of energy supply and can be well explained by the decoupling of heat demand and electricity production, which is shown in a correlation analysis.

[1]  Anders N. Andersen,et al.  Exploration of economical sizing of gas engine and thermal store for combined heat and power plants in the UK , 2008 .

[2]  Taher Niknam,et al.  Multi-objective energy management of CHP (combined heat and power)-based micro-grid , 2013 .

[3]  Mauro Reini,et al.  Multicriteria optimization of a distributed energy supply system for an industrial area , 2013 .

[4]  Morten Boje Blarke,et al.  The effectiveness of storage and relocation options in renewable energy systems , 2008 .

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

[6]  G. Andersson,et al.  Optimal Coupling of Energy Infrastructures , 2007, 2007 IEEE Lausanne Power Tech.

[7]  Christoph Koch,et al.  The contribution of heat storage to the profitable operation of combined heat and power plants in liberalized electricity markets , 2012 .

[8]  Evangelos Triantaphyllou,et al.  Multi-criteria Decision Making Methods: A Comparative Study , 2000 .

[9]  F. Glover IMPROVED LINEAR INTEGER PROGRAMMING FORMULATIONS OF NONLINEAR INTEGER PROBLEMS , 1975 .

[10]  Brian Vad Mathiesen,et al.  A review of computer tools for analysing the integration of renewable energy into various energy systems , 2010 .

[11]  Woojin Cho,et al.  A simple sizing method for combined heat and power units , 2014 .

[12]  Manuel Wickert,et al.  Long-term scenarios and strategies for the deployment of renewable energies in Germany in view of European and global developments , 2012 .

[13]  Mark Jennings,et al.  A review of urban energy system models: Approaches, challenges and opportunities , 2012 .

[14]  Nilay Shah,et al.  The impact of CHP (combined heat and power) planning restrictions on the efficiency of urban energy systems , 2012 .

[15]  Wei Wu,et al.  Multi-objective optimization for combined heat and power economic dispatch with power transmission loss and emission reduction , 2013 .

[16]  André Bardow,et al.  Automated superstructure-based synthesis and optimization of distributed energy supply systems , 2013 .

[17]  Andrea Zelmer Designing coupled energy carrier networks by mixed-integer programming methods , 2010 .

[18]  Peter Lund,et al.  Urban energy systems with smart multi-carrier energy networks and renewable energy generation , 2012 .