One piece of the puzzle towards 100 Positive Energy Districts (PEDs) across Europe by 2025: An open-source approach to unveil favourable locations of PV-based PEDs from a techno-economic perspective

Bruck, Axel; Ruano, Santiago Diaz; Auer, Hans

doi:10.1016/j.energy.2022.124152

Cited by 14 publications

(12 citation statements)

References 41 publications

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“…However, the process of developing and creating a PED is still an ongoing research topic because of its inherent complexity and uncertainty. For example, diverse climate zones and technology settlements make the optimal location for establishing a PED to be areas in southern Europe that, unlike northern Europe, lack district heating [13]. This section examines the existing literature on PEDs that has in some way sought to analyze the definition of a PED or to identify the key factors or main elements of a PED.…”

Section: Elements Of Peds and Research Methodsmentioning

confidence: 99%

“…As one of the most important activity and funding leaders, the JPI UE identified three functions of a PED in the urban energy system: energy production, energy efficiency, and energy flexibility [31]. It went on to study these functions in more detail from different angles [5,13,37]. Energy produced for PEDs needs to be sourced from local or regional renewable sources, and achieve the goal of zero emissions.…”

Section: Elements Of a Pedmentioning

confidence: 99%

“…Input data and its customization, grid impact, multi-energy interaction, and information on district infrastructure are the key challenges for energy modeling [13]. Because there is no single tool that integrates all of the necessary information, these challenges exist across the whole of the three-stage PED modeling process: pre-simulation, simulation, and post-simulation [7].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

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Perspectives of Machine Learning and Natural Language Processing on Characterizing Positive Energy Districts

Han,

Canli,

Shah

et al. 2024

Buildings

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The concept of a Positive Energy District (PED) has become a vital component of the efforts to accelerate the transition to zero carbon emissions and climate-neutral living environments. Research is shifting its focus from energy-efficient single buildings to districts, where the aim is to achieve a positive energy balance across a given time period. Various innovation projects, programs, and activities have produced abundant insights into how to implement and operate PEDs. However, there is still no agreed way of determining what constitutes a PED for the purpose of identifying and evaluating its various elements. This paper thus sets out to create a process for characterizing PEDs. First, nineteen different elements of a PED were identified. Then, two AI techniques, machine learning (ML) and natural language processing (NLP), were introduced and examined to determine their potential for modeling, extracting, and mapping the elements of a PED. Lastly, state-of-the-art research papers were reviewed to identify any contribution they can make to the determination of the effectiveness of the ML and NLP models. The results suggest that both ML and NLP possess significant potential for modeling most of the identified elements in various areas, such as optimization, control, design, and stakeholder mapping. This potential is realized through the utilization of vast amounts of data, enabling these models to generate accurate and useful insights for PED planning and implementation. Several practical strategies have been identified to enhance the characterization of PEDs. These include a clear definition and quantification of the elements, the utilization of urban-scale energy modeling techniques, and the development of user-friendly interfaces capable of presenting model insights in an accessible manner. Thus, developing a holistic approach that integrates existing and novel techniques for PED characterization is essential to achieve sustainable and resilient urban environments.

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Section: Elements Of Peds and Research Methodsmentioning

confidence: 99%

Section: Elements Of a Pedmentioning

confidence: 99%

Section: Introduction 1backgroundmentioning

confidence: 99%

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Perspectives of Machine Learning and Natural Language Processing on Characterizing Positive Energy Districts

Han,

Canli,

Shah

et al. 2024

Buildings

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“…Bruck et al [88] analyzed already realized PED from the techno-economic perspective. An important part was storage.…”

Section: Applications Of Energy Storage Systems In Urban Areasmentioning

confidence: 99%

Energy Storage in Urban Areas: The Role of Energy Storage Facilities, a Review

Anastasovski,

Andreucci,

Kádár

et al. 2024

Energies

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Positive Energy Districts can be defined as connected urban areas, or energy-efficient and flexible buildings, which emit zero greenhouse gases and manage surpluses of renewable energy production. Energy storage is crucial for providing flexibility and supporting renewable energy integration into the energy system. It can balance centralized and distributed energy generation, while contributing to energy security. Energy storage can respond to supplement demand, provide flexible generation, and complement grid development. Photovoltaics and wind turbines together with solar thermal systems and biomass are widely used to generate electricity and heating, respectively, coupled with energy system storage facilities for electricity (i.e., batteries) or heat storage using latent or sensible heat. Energy storage technologies are crucial in modern grids and able to avoid peak charges by ensuring the reliability and efficiency of energy supply, while supporting a growing transition to nondepletable power sources. This work aims to broaden the scientific and practical understanding of energy storage in urban areas in order to explore the flexibility potential in adopting feasible solutions at district scale where exploiting the space and resource-saving systems. The main objective is to present and critically discuss the available options for energy storage that can be used in urban areas to collect and distribute stored energy. The concerns regarding the installation and use of Energy Storage Systems are analyzed by referring to regulations, and technical and environmental requirements, as part of broader distribution systems, or as separate parts. Electricity, heat energy, and hydrogen are the most favorable types of storage. However, most of them need new regulations, technological improvement, and dissemination of knowledge to all people with the aim of better understanding the benefits provided.

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“…In recent years, the Positive Energy District (PED) concept has emerged in which a district generates more local renewable energy than energy consumed from the outer-district boundaries while maintaining a net-zero carbon emission balance. Furthermore, the solar potential of heritage buildings can be implemented in virtual PEDs, which open the spatial frontiers of districts to allow off-site renewable generation [36][37][38][39], (Figure 1).…”

Section: Scopementioning

confidence: 99%

Potentials and Limits of Photovoltaic Systems Integration in Historic Urban Structures: The Case Study of Monument Reserve in Bratislava, Slovakia

Hubinský¹,

Hajtmanek²,

Šeligová³

et al. 2023

Sustainability

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In the context of the current energy crisis and climate change, the importance of discussions on how to incorporate monument protection into sustainable strategies that mitigate the human impact on the environment and implement renewable sources while preserving cultural values is raised. Through the case study of the Monument Reserve in Bratislava, Slovakia, this article presents the potentials and limits of the integration of photovoltaic systems in historic urban structures that directly affect their feasible participation in smart city and positive energy district concepts by means of energy cooperativeness. This study highlights the most current recommendations and basic principles on how to assess their visual impact and select the most appropriate solutions. Using the datafication process, it analyzes the irradiance of pitched and flat roof polygons of the set area based on their characteristics such as the normal vector azimuth and slope of the rooftops. For this purpose, a 3D morphological model in LOD3 detail and the open-source solar irradiation model r.sun implemented in GRASS GIS / QGIS were used. The data obtained provided an estimate of the output potential to endow the city’s power grid and were compared to the electricity consumption of the particular city district. Furthermore, these data are suitable for designing a customized technical and aesthetic solution for the integration of photovoltaics with respect to cultural sustainability, as well as for decision- and policy makers.

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One piece of the puzzle towards 100 Positive Energy Districts (PEDs) across Europe by 2025: An open-source approach to unveil favourable locations of PV-based PEDs from a techno-economic perspective

Cited by 14 publications

References 41 publications

Perspectives of Machine Learning and Natural Language Processing on Characterizing Positive Energy Districts

Perspectives of Machine Learning and Natural Language Processing on Characterizing Positive Energy Districts

Energy Storage in Urban Areas: The Role of Energy Storage Facilities, a Review

Potentials and Limits of Photovoltaic Systems Integration in Historic Urban Structures: The Case Study of Monument Reserve in Bratislava, Slovakia

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