Energy-efficient building retrofits: An assessment of regulatory proposals under uncertainty

Abstract

Improving energy efficiency in European Union buildings will require retrofitting much of the existing stock due to limited new construction opportunities. Given uncertainty in energy prices and technology costs stemming from deregulation, a stochastic optimisation framework is desirable for long-term decision support. We synthesise treatment of uncertainty and risk management to obtain insights about the impact of retrofits on energy consumption, costs, CO 2 emissions, and risk at real buildings in Austria and Spain. The optimal strategy for the Spanish site is to invest in photovoltaic and solar thermal technologies. This lowers expected costs by 8.5% and reduces expected primary energy consumption and CO 2 emissions by 20% relative to using existing equipment. By limiting exposure to volatile energy prices, the strategy also yields a nearly 10% reduction in risk. We obtain similar results also for the Austrian site. Via this framework, tradeoffs among competing objectives and the effectiveness of proposed regulation may be assessed. Specifically, we find that more stringent restrictions on energy efficiency are economically viable if regulation also facilitates enhanced operational decision support for buildings. Indeed, primary energy consumption can be lowered only through more on-site generation such as combined heat and power, which is more complex for building managers to deploy.

Machine Learning Techniques Focusing on the Energy Performance of Buildings: A Dimensions and Methods Analysis

“…In the study of a total of 33 literature papers, we analyzed 13 journal papers, including from Applied Energy (9), Energy & Buildings (7) 1 shows the summary of the journals with their information, that most journals are Q1-quartile ranked (9), representing 90%, (2) are Q2-quartile-ranked, and the remaining (1) is not yet classified by the quartile-ranked [22], although the quartile rank can change over time.…”

“…Considering that buildings account for 40% of the primary energy consumption (EC) in the European Union [1], reducing the EC of buildings has become a necessity. The European Union, considering the increasing urbanization and climate change trends, defined the objective to reduce EC by 32.5% until 2030, from the baseline year of 2007, as a key priority in the EU's strategy and Green deal [2] to increase EE and decrease the energy performance (EP) of existing buildings [2][3][4].…”

“…Buildings are responsible for the second largest portion of the final EC in the European Union [1,6,7], with households on 26.3% and public buildings on 28.8%, just after the transport sector (with 30.9%). Their refurbishment and energy-efficient retrofitting is a priority for many countries to reduce EC and decrease the EP of existing buildings as part of the EU Green deal [2,8].…”

Optimal Selection of Distributed Energy Resources Under Uncertainty and Risk Aversion

“…By contrast, since energy loads in commercial buildings can be forecast accurately [24], we assume that both electricity and heat loads are known in advance. Likewise, technology costs are assumed to be fixed in real terms as our focus is on managing the risk from uncertain prices (see [25] for incorporation of technology cost risk). Thus, the consumer makes its investment and futures contracting decisions without knowing spot price realisations, but it can purchase additional electricity and gas later, when their spot prices are known.…”

“…The results have not been validated at a real site because it is generally not possible to advise a consumer to switch its energy procurement strategy and to observe the subsequent changes in costs. However, [25] did validate the performance of stochastic programming tools for technology adoption and operation by real buildings. In particular, the observed energy consumption and cost patterns of a Spanish test site are faithfully replicated by the model when it is run by an independent energy auditor for only the current year with investment decisions disabled.…”