Project:Climate Analysis for Building Design

I’m starting the “Climate Analysis for Building Design” using R language(Python is also a good choice) . R is a free software environment for statistical computing and graphics. The goal of the project is to analyse the climate data under various criteria to guide the choosing of different strategy for building design in different climatic environment. There should be a GUI for the settings so an integration of R and C++ is necessary. Rcpp provides a powerful API on top of R, permitting direct interchange of rich R objects (including S3, S4 or Reference Class objects) between R and C++. The RInside package provides C++ classes that make it easier to embed R in C++ code — on either Linux, OS X or Windows. A web application is also under considering.

The R Project for Statistical Computing.

Rcpp: Seamless R and C++ Integration.

RInside: Easier embedding of R in C++ applications.

rApache.

RStudio – Shiny.

net present value (NPV), return on investment (ROI), internal rate of return (IRR)

http://en.wikipedia.org/wiki/Net_present_value

http://en.wikipedia.org/wiki/Return_on_investment

http://en.wikipedia.org/wiki/Internal_rate_of_return

The main difference between providing a simple payback figure (typically just the capital cost divided by the annual energy cost savings) and providing NPV, ROI or IRR is that the consultant includes cash flows in the analysis. A simple payback calculation generally underestimates the true economic value of the energy efficiency investment, as it ignores other important benefits (rebates, depreciation expenses, maintenance savings, etc.). LCCA enables decision-makers to fully understand the economic justification for an integrated sustainable design.