Abstract

With world's increasing energy demand and growing environmental concerns, efficient utilization of energy is critical for sustainable living. Buildings are the major energy consumers, and a set of buildings are connected by distributed energy resources (DERs) such as chillers and boilers in certain building clusters, e.g., a school campus or residential community. Optimized operation of such building clusters, however, is challenging. Proper device and building models are needed, and it is difficult and impractical to control everything at the cluster level. This paper presents integrated optimization of building clusters with buildings and DERs to reduce energy costs and CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emissions. From the energy and emission point of view, energy networks of buildings, devices, and water/electricity networks are established for energy generation, conversation, storage and utilization, and emissions. The problem is to match different types of energy demand of buildings and supplies from devices with time-varying electricity and gas prices. A mixed-integer model for a small building cluster is established. To coordinate buildings and devices, our idea is to use multipliers as shadow prices in a decomposition and coordination structure. Our surrogate Lagrangian relaxation method is used to solve the problem. With breakthroughs in multiplier updating directions and step-sizing formulas, computational efforts are much reduced. Preliminary optimization and simulation results show that total energy costs and emissions are reduced by optimized operation, e.g., making direct use of energy resource and avoiding unnecessary energy conversion.

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