Energy performance upgrade of stadiums constitutes a complex and demanding task because of both the size and the variety of the involved energy loads. The present article aims to summarize the basic results of the implemented study on the energy performance upgrade of the Pancretan Stadium, Crete, Greece. This target was approached with a cluster of passive and active measures: replacement of old openings, a photovoltaic station, an open loop geothermal system, installation of energy-efficient lighting devices, a solar-biomass combi system and a Building Energy Management System (BEMS) for the control of the main energy consumptions. The dimensioning of all the proposed active systems is optimized through the computational simulation of their annual operation. With the applied technologies, the achieved annual energy saving percentage exceeds 83%. The Renewable Energy Sources annual penetration percentage is calculated at 82% versus the annual energy consumption. The Stadium’s energy performance is upgraded from rank D to rank A+, according to the European Union’s directives. The set-up cost of the under consideration energy performance upgrade systems is approximately calculated at 2,700,000 €, with a payback period of 12 years, calculated versus the achieved monetary savings due to the reduction of the consumed energy resources.
This article presents the computational simulation process and the operation algorithms of the VAV and VRV systems, for indoor space conditioning, with extensive physical cooling and heat recovery. Through the introduction of appropriate operation algorithms, the article aims to highlight the high energy saving potential on indoor space conditioning, by exploiting physical cooling and heat recovery processes. The proposed algorithms are evaluated with a case study for a hydro power plant building located in the area of Lugano, Switzerland, with significant cooling needs for the whole year, due to high internal heat gains from indoor electrical equipment. This fact enables physical cooling during winter, for the cooling load coverage, and heat recovery, for the concurrent heating load coverage in different thermal zones of the building. Analytical operation algorithms are developed for a VAV and a VRV system. Both algorithms are computationally simulated. With the VAV system, 86.1% and 63.7% of the annual cooling and heating demand, respectively are covered by physical cooling and heat recovery. With the VRV system, 58.5% of the annual heating demand is covered by heat recovery. The set-up cost of the VAV system is almost twice higher than the set-up cost of the VRV system.
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