Abstract
About 40% of global energy consumption is due to buildings. For this reason, many countries have established strict limits with regard to building energy performance. In fact, the minimization of energy consumption and related polluting emissions is undertaken in the public perspective with the main aim of fighting climate change. On the other hand, it is crucial to achieve financial benefits and proper levels of thermal comfort, which are the principal aims of the private perspective. In this paper, a multi-objective multi-stage approach is proposed to optimize building energy design by addressing the aforementioned public and private aims. The first stage implements a genetic algorithm by coupling MATLAB® and EnergyPlus pursuing the minimization of energy demands for space conditioning and of discomfort hours. In the second stage, a smart exhaustive sampling is conducted under MATLAB® environment with the aim of finding constrained cost-optimal solutions that ensure a drastic reduction of global costs as well as of greenhouse gas (GHG) emissions. Furthermore, the impact of such solutions on heat emissions into the external environment is investigated because these emissions highly affect urban overheating, external human comfort and the livability of our cities. The main novelty of this approach is the possibility to properly conjugate the public perspective (minimization of GHG emissions) and the private one (minimization of global costs). The focus on the reduction of heat emissions, in addition to the assessment of energy demands and GHG emissions, is novel too for investigations concerning building energy efficiency. The approach is applied to optimize the retrofit of a reference building related to the Italian office stock of the 1970s.
Highlights
Introduction and State of the ArtGlobal energy consumption has strong implications on human socio-economic and political spheres
A multi-objective and multi-stage optimization procedure is implemented to find a constrained cost-optimal solution that fulfils these three conditions:. It ensures the Pareto optimization of thermal energy demand (TED) for heating, TED for cooling, discomfort hours (DH) if the retrofit involves the building envelope; it implies a drastic reduction of greenhouse gas (GHG) emissions since a macroeconomic approach is applied for global cost (GC) assessment thereby considering the cost of such emissions [6]; minimizes GC by respecting the first two conditions, which is why it is defined “constrained”
It is important to notice that GC considers the initial investment cost, the GHG emissions costs and the running costs, those latter evaluated for a certain number of years and actualized at the starting time
Summary
Introduction and State of the ArtGlobal energy consumption has strong implications on human socio-economic and political spheres. Improved data about the global energy consumption reveal systemic patterns and trends that can be useful for solving current energy issues In this regard, looking at the worldwide scenario, the energy consumption increased by just 1% in 2016, by following a growth of 0.9% in 2015 and 1%. The recent weak growth in energy demand implied that the global greenhouse gas (GHG) emissions from energy consumption were almost flat during 2016 for the third consecutive year. They increased by only 0.1% in 2016 and during 2014–2016 the average emission growth was the lowest over any three-year period since 1981–1983 [1]. This means that, during recent years, many governments are moving in the direction of sustainable development [2]
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