Abstract
This report presents the methodology for determining least cost energy efficient upgrade solutions in new residential housing using brute force sequential search (BFSS) method for integration into the reference house to reduce energy consumption while minimizing the net present value (NPV) of life cycle costs. The results showed that, based on the life cycle cost analysis of 30 years, the optimal upgrades resulted in the average of 19.25% (case 1), 31% (case 2a), and 21% (case 2b) reduction in annual energy consumption. Economic conditions affect the sequencing of the upgrades. In this respect the preferred upgrades to be performed in order are; domestic hot water heating, above grade wall insulation, cooling systems, ceiling insulation, floor insulation, heat recovery ventilator, basement slab insulation and below grade wall insulation. When the gas commodity pricing becomes high, the more energy efficient upgrades for domestic hot water (DHW) get selected at a cost premium.
Highlights
Increased environmental awareness and limited energy resources are the driving force behind the escalating importance of the urgent need to reduce energy consumption in the residential sector in Canada
The objective of this report was to present the methodology for determining least cost upgrades in new residential housing using the brute force sequential search (BFSS) method, and to integrate these energy efficient upgrades into a reference Canadian Centre for Housing Technology (CCHT) house that will reduce energy consumption while minimizing the Net Present Value (NPV) of life cycle costs
The results showed that, based on the life cycle cost analysis of 30 years, all of the identified combinations of least cost upgrades including building envelope, domestic hot water, heating, cooling, furnace, and ventilation systems, the resulting were: 1) Up to 32% reduction in annual energy consumption and 29% in greenhouse gas for Toronto, Ontario
Summary
In this chapter the combination of the least cost upgrades were determined using the brute force sequential search (BFSS) method for climate conditions in Ottawa, Thunder Bay, and Windsor, Ontario. The reference city in this study is Toronto, Ontario. The weather condition in Ottawa and Thunder Bay is much colder than Toronto. The estimated heating degree days (HDD) (below 18°) for both cities are (Dembo, 2011): 1) Ottawa: 4602 2) Thunder Bay: 5677 Windsor has a warmer climate than Toronto with heating degree days (HDD) of 3525 (Dembo, 2011).
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