This paper presents a comprehensive review of all significant research applying computational optimisation to sustainable building design problems. A summary of common heuristic optimisation algorithms is given, covering direct search, evolutionary methods and other bio-inspired algorithms. The main summary table covers 74 works that focus on the application of these methods to different fields of sustainable building design. Key fields are reviewed in detail: envelope design, including constructions and form; configuration and control of building systems; renewable energy generation; and holistic optimisations of several areas simultaneously, with particular focus on residential and retrofit. Improvements to the way optimisation is applied are also covered, including platforms and frameworks, algorithmic comparisons and developments, use of meta-models and incorporation of uncertainty. Trends, including the rise of multi-objective optimisation, are analysed graphically. Likely future developments are discussed.

A review of computational optimisation methods applied to sustainable building design

Combined heat and power economic dispatch by harmony search algorithm

Combined heat and power economic dispatch problem solution using particle swarm optimization with time varying acceleration coefficients

Particle swarm optimization with time varying acceleration coefficients for non-convex economic power dispatch

This paper presents an algorithm, biogeography-based optimization (BBO) to solve both convex and non-convex economic load dispatch (ELD) problems of thermal generators of a power system. The Proposed methodology easily takes care of solving non-convex economic dispatch problems considering different constraints such as transmission losses, ramp rate limits, multi-fuel options and prohibited operating zones. Biogeography deals with the geographical distribution of biological organisms. Mathematical models of biogeography describe how species migrate from one habitat to another, how species arise, and how species become extinct. BBO has features in common with other biology-based optimization methods, like genetic algorithms (GAs) and particle swarm optimization (PSO). Here, first it will be discussed how BBO can be used to solve ELD problems. This algorithm searches the global optimum mainly through two steps: migration and mutation. To show the advantages of the proposed algorithm, it has been applied to four different test systems for solving ELD problems. First, a 6-generator system along with ramp rate limits and prohibited operating zone. Second, considers 40 generators with valve-point loading. Third, considers 20-generator systems with simple quadratic cost function considering transmission loss and operating limit constraints. Last one is addressing both valve-point effects and multiple fuels in a 10-generator system. Comparing with the other existing techniques, the current proposal is found better than, or at least comparable to them considering the quality of the solution obtained. This method is considered to be a promising alternative approach for solving the ELD problems in practical power system.

C.S. Chou

Papers

Combined heat and power economic dispatch by improved ant colony search algorithm