**1. Introduction**

The building sector in Europe is considered as the largest consumer of energy, using up to 40% of the final energy consumption [1,2]. As reported in the EU directive 2018/844/EU, almost 50% of the Union's final energy consumption is used for heating and cooling, 80% of which is allocated to buildings. This indicates that the achievement of the Union's targets regarding energy efficiency and resilience to climate change depends on the increase of renovation rates of its building stock, in fact, by giving priority to energy efficiency as well as by considering deployment of renewables [3]. According to its (EU) 2019/786 recommendation on building renovation [4], the Commission invites Member States to establish long-term renovation strategies focused on the national building stock, including both public and private buildings, towards highly energy efficient and decarbonized building stock by 2050, also prescribing measures for the cost-effective transformation of existing buildings into nearly zero-energy buildings (the so-called NZEBs). In this framework, it is acknowledged that the design approaches followed in order to achieve the highest possible energy-saving potential require advanced calculation techniques at the design stage, with the highest possible accuracy of predictions. In the context of evaluating building energy performance, many parameters are required, such as the thermo-physical properties of the envelope, indoor–outdoor physical interactions, energy end uses, building systems' operating schedules, etc. Considering all these influencing factors, building energy upgrading is indeed not an easy task. Especially now with more strict regulations and

**Citation:** Stavrakakis, G.M.; Katsaprakakis, D.A.; Damasiotis, M. Basic Principles, Most Common Computational Tools, and Capabilities for Building Energy and Urban Microclimate Simulations. *Energies* **2021**, *14*, 6707. https:// doi.org/10.3390/en14206707

Academic Editor: Marcin Kami ´nski

Received: 29 August 2021 Accepted: 12 October 2021 Published: 15 October 2021

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policies, building energy renovation plans require precise estimations of energy indicators, as specific thresholds of these indicators should be satisfied, and at the same time least-cost renovation measures should be identified.

On the other hand, a crucial factor that affects the energy performance of building complexes is the external microclimate, i.e., the microclimatic conditions in the vicinity of buildings determines cooling and heating loads, thus the energy demand and the decision of most appropriate energy-efficiency measures. Especially in densely built environments, the external microclimatic conditions should not be disregarded in the design stage as, indeed, the Urban Heat Island (UHI) effect is ever more intense and impacts many aspects of quality of life in cities, e.g., building energy efficiency, thermal comfort, and indoor and outdoor air quality. Over the last 30 years, heat waves in Europe in combination with the Urban Heat Island (UHI) phenomenon have dramatically deteriorated quality of life in densely built-up Cities, by means of mortality rates due to heat strokes, and of hygiene conditions as well as of the energy demand for cooling purposes. UHI is well documented in terms of its intensity. Indicatively, in Europe, the mean value of recorded maximum UHI intensities ranged between 0.3 ◦C and 6.8 ◦C (yielding an average of 2.6 ◦C), with absolute peaks close to 12 ◦C [5,6]. Such conditions of unusually high temperatures for long periods favor high energy consumption in buildings. For example, it has been documented that the increase in urban temperature may lead to an average increase of cooling loads from 20% to 45% in the Mediterranean climate [7]. This means that a holistic confrontation over the improvement of building energy performance should not disregard the impact of UHI on energy consumption. Apart from benefiting building energy performance, UHI mitigation projects ensure more comfortable and healthy open spaces for pedestrians.

To deal with the requirements of the latest EU directives as well as of the design challenges, EU Member States have developed their own national methodologies and computational tools (e.g., based on the CEN Standards), aiming to assess building energy performance in the pre-renovation (or pre-construction) and the post-renovation (or postconstruction) situations in order to determine renovation measures. However, the available national tools are much more biased to single-building energy simulation, while, concerning the effect of local microclimate, it is often omitted from the numerical-simulation toolboxes used for purposes of compliance with building energy regulations. In current policies and regulatory frameworks, only the general bioclimatic-design principles are adopted regarding urban planning, without addressing the quantification of microclimatic indicators; hence, still no computational tools and/or concrete calculation methodologies are recommended to estimate microclimate and environmental indicators in the study phase specifically for design-for-compliance purposes.

On the other hand, considering the issues raised above, it becomes obvious that in order to comply with the latest energy efficiency policies and much stricter regulations, as well as to obtain sustainably built and urban environments, accurate methods and computational tools to estimate the impact of retrofit options based on the aspects of building and urban physics are required. The use of such methods is considered crucial even in the early study phase, especially for major renovation projects, for the following reasons:


for the impact of the UHI effect, i.e., of the local microclimate rather than relying on the wider climate zone, on building energy consumption.


The present paper provides an overview of commercial or freely available computational tools that can be used to assess building energy performance and UHI effect in open spaces. The major categories of physical models are presented, i.e., multi-zonal (also known as nodal models) for building energy performance assessments and field models for UHI assessments. The capabilities of the most popular computational tools of each category are presented together with case studies found in the scientific literature. Furthermore, nodal/field models coupling possibilities to assess UHI effect on building energy consumption are discussed.
