After nearly 18 months in review, our Biomass and Bioenergy paper is now out:
Recent years have shown a marked interest in the construction of eco-towns, showcase developments intended to demonstrate the best in ecologically-sensitive and energy-efficient construction. This paper examines one such development in the UK and considers the role of biomass energy systems. We present an integrated resource modelling framework that identifies an optimized low-cost energy supply system including the choice of conversion technologies, fuel sources, and distribution networks. Our analysis shows that strategies based on imported wood chips, rather than locally converted forestry residues, burned in a mix of ICE and ORC combined heat and power facilities offer the most promise. While there are uncertainties surrounding the precise environmental impacts of these solutions, it is clear that such biomass systems can help eco-towns to meet their target of an 80% reduction in greenhouse gas emissions.
Read more on Evaluating biomass energy strategies for a UK eco-town…
A fascinating new book on urban economics, infrastructure, and the links between them.
I’ve been working through Gelman et al.’s otherwise excellent Bayesian Data Analysis
and it’s going reasonably well. My statistics is a little bit rusty so it’s taken time to work through all of the exercises and really understand what’s going on. But I say “otherwise excellent” because yesterday I spent ages trying to figure out a problem, only to discover that the data published in the book don’t correspond to the text discussion.
Read more on Grrr……
Posted in R | Tagged Rstats, statistics
I’ve knocked together a quick function for generating efficient Monte Carlo samples. It takes a bit of the legwork out of running Monte Carlo simulations.
I’ve recently shifted from SVN to Git for version control and it’s working great. In fact, I’ve just finished my first project which lets you easily build slides and notes for lectures.
When I first started using R, one of the things that attracted me was its claim to be an object-oriented programming (OOP) language. Coming from a Java background, I was used to designing software with OOP concepts like encapsulation and inheritance but, when I turned my hand to R, I quickly realized that “object-oriented” meant something subtlely different.
Read more on Getters and setters in R…
Posted in R | Tagged programming, Rstats