Distributed fast optimization algorithm for group operation of mechanical equipment

Parallel equipment group of the same or similar category is widely existed in mechanical and electrical systems in public buildings. For optimal operation and energy conservation of buildings, it is of significance to research the optimization of parallel equipment group. The existing researches and applications mainly depend on expert experiences and full condition optimal search techniques. The former is an incomplete decision method, and the latter needs detailed modeling with a large amount of calculation. Based on theoretical analysis, presents a fast and simple decision method to search the optimal startup and adjusting strategy for equipment group. The new method features much lower demand for equipment modeling and can be realized a distributed computing framework. Presents the method and performs a field test in a chilled water pump group of an office building. Both of the test and analysis results show that new algorithm has a good performance in group optimization decision in practical engineering projects.