This paper presents a novel integration of building energy simulation with The World Avatar(TWA),a dynamic knowledge graph and agent-based framework designed for comprehensive and interoperable digital representation ...This paper presents a novel integration of building energy simulation with The World Avatar(TWA),a dynamic knowledge graph and agent-based framework designed for comprehensive and interoperable digital representation of the world.The study addresses the imperative for accurate and granular building energy data in energy planning scenarios.By leveraging knowledge graph,agents within TWA replace default assumptions in simulation tools with real-time and location-specific input data,such as building geometry,usage,weather,and terrain elevation.This integrated approach automates the simulation process,enabling agents to retrieve input data,execute simulations,and update the knowledge graph with results in a consistent format.To demonstrate this approach,we developed a simulation agent using the City Energy Analyst.Validation against external datasets from Germany and Singapore shows that the agent significantly improves simulation accuracy.The study also highlights the challenges in data acquisition and processing for municipal heat planning,aligning with the requirements of the German Heat Planning Act.Using Pirmasens,a mid-sized city in Germany,as an example,we demonstrate the practical applicability of the agent in municipal heat planning by providing highly granular data on the heating demands and the solar potentials for heat generation.An accompanying economic analysis further evaluates the cost implications and energy storage requirements associated with the installation of solar collectors,and identifies zones in the city with high solar suitability.These insights enable data-driven decision-making,showcasing the potential of this integrated approach to support municipal heat planning.展开更多
This paper presents a knowledge graph-based approach for the dynamic control of a district heating network with integrated emission dispersion modelling. We propose an interoperable and extensible implementation to fo...This paper presents a knowledge graph-based approach for the dynamic control of a district heating network with integrated emission dispersion modelling. We propose an interoperable and extensible implementation to forecast the anticipated heat demand of a municipal heating network, minimise associated total generation cost based on a previously devised methodology, and couple it with dispersion simulations for induced airborne pollutants to provide automatic insights into air quality implications of various heat sourcing strategies. We create cross-domain interoperability in the nexus of energy and air quality via newly developed ontologies and semantic software agents, which can be chained together via The World Avatar dynamic knowledge graph to resemble the behaviour of complex systems. Furthermore, we integrate the City Energy Analyst into this ecosystem to provide building-level insights into energy demand and renewable generation potential to foster strategic analyses and scenario planning. Underlying calculations use building and weather data from the knowledge graph in place of inherent assumptions in the official software release, facilitating a more data-driven approach. All use cases are implemented for a mid-size town in Germany as a proof-of-concept, and a unified visualisation interface is provided, allowing for the examination of 3D buildings alongside their corresponding energy demand and supply time series, as well as emission dispersion data. With this work, we outline the potential of Semantic Web technologies to connect digital twins for holistic energy modelling in smart cities, thereby addressing the increasing complexity of interconnected energy systems.展开更多
基金supported by the National Research Foundation,Prime Minister’s Office,Singapore under its Campus for Research Excellence and Technological Enterprise(CREATE)programmePart of this work was also supported by Towards Turing 2.0 under EPSRC,United Kingdom Grant EP/Y016076/1.
文摘This paper presents a novel integration of building energy simulation with The World Avatar(TWA),a dynamic knowledge graph and agent-based framework designed for comprehensive and interoperable digital representation of the world.The study addresses the imperative for accurate and granular building energy data in energy planning scenarios.By leveraging knowledge graph,agents within TWA replace default assumptions in simulation tools with real-time and location-specific input data,such as building geometry,usage,weather,and terrain elevation.This integrated approach automates the simulation process,enabling agents to retrieve input data,execute simulations,and update the knowledge graph with results in a consistent format.To demonstrate this approach,we developed a simulation agent using the City Energy Analyst.Validation against external datasets from Germany and Singapore shows that the agent significantly improves simulation accuracy.The study also highlights the challenges in data acquisition and processing for municipal heat planning,aligning with the requirements of the German Heat Planning Act.Using Pirmasens,a mid-sized city in Germany,as an example,we demonstrate the practical applicability of the agent in municipal heat planning by providing highly granular data on the heating demands and the solar potentials for heat generation.An accompanying economic analysis further evaluates the cost implications and energy storage requirements associated with the installation of solar collectors,and identifies zones in the city with high solar suitability.These insights enable data-driven decision-making,showcasing the potential of this integrated approach to support municipal heat planning.
文摘This paper presents a knowledge graph-based approach for the dynamic control of a district heating network with integrated emission dispersion modelling. We propose an interoperable and extensible implementation to forecast the anticipated heat demand of a municipal heating network, minimise associated total generation cost based on a previously devised methodology, and couple it with dispersion simulations for induced airborne pollutants to provide automatic insights into air quality implications of various heat sourcing strategies. We create cross-domain interoperability in the nexus of energy and air quality via newly developed ontologies and semantic software agents, which can be chained together via The World Avatar dynamic knowledge graph to resemble the behaviour of complex systems. Furthermore, we integrate the City Energy Analyst into this ecosystem to provide building-level insights into energy demand and renewable generation potential to foster strategic analyses and scenario planning. Underlying calculations use building and weather data from the knowledge graph in place of inherent assumptions in the official software release, facilitating a more data-driven approach. All use cases are implemented for a mid-size town in Germany as a proof-of-concept, and a unified visualisation interface is provided, allowing for the examination of 3D buildings alongside their corresponding energy demand and supply time series, as well as emission dispersion data. With this work, we outline the potential of Semantic Web technologies to connect digital twins for holistic energy modelling in smart cities, thereby addressing the increasing complexity of interconnected energy systems.
