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Optimising the installation costs of renewable energy technologies in buildings: A Linear Programming approach

Privitera, G., Day, A. R., Dhesi, G. and Long, D.
2011
Energy and Buildings, 43(4): 838-843


Privitera, G., Day, A. R., Dhesi, G. and Long, D., (2011), "Optimising the installation costs of renewable energy technologies in buildings: A Linear Programming approach", Energy and Buildings, 43(4): 838-843.
Abstract:
This paper demonstrates how Linear Programming (LP) can be applied to assist in the choice of renewable energy technologies for use in buildings to meet CO2 emissions reduction targets. Since there are many possibilities for combining different renewable technologies, the capital costs associated with the installation of one or more renewables can vary widely. In terms of capital investment the preferred solution will be the one at least cost, and LP provides an effective way to find this minimum through the so-called 'objective function'. This project has used 'lp_solve', a free-source Mixed Integer Linear Programming solver that has been embedded in a Microsoft Excel application called Carbon emissions And Renewables for Building OPtimisation Toolkit (CARB-OPT) developed by RES Ltd in collaboration with London South Bank University (Renewable Environmental Services Ltd. (RES) is the environmental consultancy of Long and Partners Engineering Group. RES is currently involved in a Knowledge Transfer Partnerships (KTP) project in conjunction with the Faculty of Engineering, Science and the Building Environment (ESBE) at London South Bank University). This paper reports the application of this LP optimisation process for an office building case study with four alternative combinations of renewables. The process showed the technology mix that would lead to the smallest investment needed to comply with UK Building Regulations requirements and regional planning targets. In addition, the process offers a robust methodology to test the impact that the key assumptions may have upon the optimum solution.

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