Building Design Optimisation
- A Few Key Concepts
Dr Yi Zhang
Founder and Director, Energy Simulation Solutions Ltd
Associate Professor, University College London
The key ingredients of optimisation
1. Optimisation variables (“the search space”)
2. Optimisation criteria (“objectives” and “constraints”)
3. Means to evaluate (many) solutions
4. An effective (and efficient) search strategy
In the context of building design/operation
Optimisation variables
–Dimensions, orientations, constructions, values, parameters, coefficients, …
–Operational schemes, schedules and setpoints
–Alternative designs, systems and equipment selection
–And a lot more…
Optimisation criteria
–Objectives: Energy, Carbon, Cost, Comfort, …
–Constraints: Energy, Carbon, Cost, Comfort, …, and Physics
Difference between Objectives and Constraints
Objective –never stop chasing the best
Constraint –satisfied once the threshold is passed
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Multi-objective optimisation
Environmental impact
Life-cycle cost
Preferred
solutions
Pareto front
Means to Evaluate (Many) Solutions
•Automated process:
(1) create new solutions (2) run simulations (3) collect results
•DesignBuilder vs. jEPlus+EA
DesignBuilder: built-in functions to apply parameters and process results, but slow
to create alternative solutions
jEPlus+EA: unlimited possibilities and highly efficient, but requires a good
understanding of E+ models and has a steeper learning curve
Both: can run simulations locally or online
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Evolutionary Algorithms
New population
Rank solutions
within population
Encode solutions
and generate a
random sample
Select solutions
for reproduction
Create Variants
by crossover
and mutation
Terminate?
Report
Evaluate
individual
solutions
No
Yes
Start
Run simulation and calculate
objective/constraint functions
Ranking depends on a
‘Fitness’ function
Post-processing and Analysing Results
•In DesignBuilder:
–Export results table
•In jEPlus+EA:
–Filter, select, highlight and inspect solutions
–Online data analytic tools
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