Abstract

One of the possible ways to improve balance between building energy consumption and occupant thermal comfort in existing buildings is to use simulation-assisted operation of HVAC systems. Simulation-assisted operation can be formulated as a type of operation that implements knowledge of future disturbance acting on the building and that enables operating the systems in such a way to fulfill given goals, which in nature can often be contradictory. The most important future conditions on building energy consumption are weather parameters and occupant behavior and expectations of thermal environment. In order to achieve this type of operation, optimization methods must be applied. Methodology to create HVAC system operation strategies on a daily basis is presented. Methodology is based on using building energy performance simulation software EnergyPlus, available weather data, global sensitivity analysis, and custom developed software with particle swarm optimization method applied over the moving horizon. Global sensitivity analysis is used in order to reduce number of independent variables for the optimization process. The methodology is applied to office part of real combined-type building located in Niš, Serbia. Use of sensitivity analysis shows that the reduced number of independent variables for the optimization would lead to similar thermal comfort and energy consumption, with significant computer runtime reduction.

Highlights

  • Building energy performance modeling and simulation represent very powerful and useful method in all stages of building lifecycle

  • Creating energy model of the existing building besides describing building geometry, construction materials used, HVAC and other installed systems has to include the description of building usage through defining patterns of occupancy and number of occupants, schedules of artificial lighting systems use, schedules of electrical appliances and equipment use and the most importantly, through proper description of existing control systems installed in the building

  • The PMV variations in case with full number of independent variables (99) for the selected periods is given in figure 8, while the PMV variation for the same period but with application of sensitivity analysis is given in figure 9

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Summary

Introduction

Building energy performance modeling and simulation represent very powerful and useful method in all stages of building lifecycle. Optimal operation strategies are developed in order to minimize building energy consumption while preserving occupant thermal comfort in given boundaries, during occupied period.

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