scholarly journals Integration of Thermoactive Metro Stations in a Smart Energy System: Feedbacks from the Grand Paris Project

2018 ◽  
Vol 3 (4) ◽  
pp. 56 ◽  
Author(s):  
Yvon Delerablée ◽  
Dina Rammal ◽  
Hussein Mroueh ◽  
Sébastien Burlon ◽  
Julien Habert ◽  
...  
Keyword(s):  
Energy Demand ◽  
Mechanical Design ◽  
Energy System ◽  
Thermal Design ◽  
Transport Efficiency ◽  
The Public ◽  
Geothermal Potential ◽  
Potential Estimate ◽  
Urban Energy ◽  
Public Entity

During the next 15 years, around 200 km of tunnels and 68 new metro stations will be built around Paris to increase the capacity of the existing metro and the transport efficiency. The Société du Grand Paris—the public entity in charge of the design and the execution of this new network—is also highly concerned by the development and the use of renewable energy within this project, especially the integration of thermoactive metro stations in a smart energy system. This paper discusses some issues related to this strategy within the “Grand Paris Project”. The first part presents how smart technology could help to the integration of thermoactive metro stations into the urban energy system, while the second part addresses the following issues: assessment of the geothermal potential, estimate of the energy demand, ground investigations, thermal design, and finally system monitoring. The mechanical design is not considered in this paper. The paper shows the pertinence of the smart energy system for the integration of the thermoactive metro stations energy and the procedure for its implementation.

scholarly journals Indicators for the optimization of sustainable urban energy systems based on energy system modeling

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Christian Klemm ◽  
Frauke Wiese
Keyword(s):  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Energy Demand ◽  
Energy Systems ◽  
Energy System ◽  
Energy Sustainability ◽  
Gas Emissions ◽  
Urban Energy ◽  
Absolute Energy ◽  
Final Energy Demand

Abstract Background Urban energy systems are responsible for 75% of the world’s energy consumption and for 70% of the worldwide greenhouse gas emissions. Energy system models are used to optimize, benchmark and compare such energy systems with the help of energy sustainability indicators. We discuss several indicators for their basic suitability and their response to changing boundary conditions, system structures and reference values. The most suitable parameters are applied to four different supply scenarios of a real-world urban energy system. Results There is a number of energy sustainability indicators, but not all of them are suitable for the use in urban energy system optimization models. Shortcomings originate from the omission of upstream energy supply chains (secondary energy efficiency), from limited capabilities to compare small energy systems (energy productivity), from excessive accounting expense (regeneration rate), from unsuitable accounting methods (primary energy efficiency), from a questionable impact of some indicators on the overall system sustainability (self-sufficiency), from the lack of detailed information content (share of renewables), and more. On the other hand, indicators of absolute greenhouse gas emissions, energy costs, and final energy demand are well suitable for the use in optimization models. However, each of these indicators only represents partial aspects of energy sustainability; the use of only one indicator in the optimization process increases the risk that other important aspects will deteriorate significantly, eventually leading to suboptimal or even unrealistic scenarios in practice. Therefore, multi-criteria approaches should be used to enable a more holistic optimization and planning of sustainable urban energy systems. Conclusion We recommend multi-criteria optimization approaches using the indicators of absolute greenhouse gas emissions, absolute energy costs, and absolute energy demand. For benchmarking and comparison purposes, specific indicators should be used and therefore related to the final energy demand, respectively, the number of inhabitants. Our example scenarios demonstrate modeling strategies to optimize sustainability of urban energy systems.

Modeling and Future Scenario Setting of Urban Energy Demand Based on District Energy System

2006 ◽  
Vol 41.3 (0) ◽  
pp. 833-838
Author(s):  
Yoshiyuki Shimoda ◽  
Yohei Yamaguchi ◽  
Takashi Asai ◽  
Minoru Mizuno
Keyword(s):  
Energy Demand ◽  
Energy System ◽  
Future Scenario ◽  
District Energy ◽  
Urban Energy

Urban Building Energy Planning With Space Distribution and Time Dynamic Simulation

2009 ◽  
Vol 131 (3) ◽  
Author(s):  
Lin Fu ◽  
Zhonghai Zheng ◽  
Hongfa Di ◽  
Yi Jiang
Keyword(s):  
Energy Demand ◽  
Air Conditioning ◽  
Energy System ◽  
Building Energy ◽  
Space Distribution ◽  
Energy Planning ◽  
Energy Sources ◽  
Simulation Tool ◽  
Time Dynamic ◽  
Urban Energy

It is important to deal with energy saving in buildings of one city level, and plan the energy system from one building to one city level. We strongly suggest conducting urban building energy planning (UBEP) in the urban planning field in China. There are two main characteristics of an urban building energy system. First, the terminal building energy demand is dynamically timely. Second, the energy demand, energy sources supply, energy equipments, and networks of heating, cooling, gas, and electricity, are distributed in an urban space. It is meaningful to conduct an innovative urban energy planning with space distribution and time dynamic simulation. Therefore, an UBEP simulation tool, developed by our research group, is introduced. Finally, a case of energy planning in Beijing City in 2010 for heating and air conditioning system is dynamically simulated and analyzed. To meet the same building energy demand in Beijing, such as heating, air conditioning, gas, and electricity, different energy equipments, such as boiler, combined heating and power, combined cooling, heating, and power system, and heat pump based on different energy sources, such as coal, gas, and electricity, should be planned alternatively. Also, an optimum urban energy system with high energy efficiency and low environmental emission can be achieved. This simulation tool contains most models of heating and cooling energy systems in China. We can validate the models with statistical data from previous or present simulation, and the simulation results in future planning can serve as guidance for the construction of municipal energy infrastructure. We can conclude that simulation in time dimension shows the characteristics of dynamic load in each nodes of the energy flow. The objective is to present the comparison of different scenarios and optimize the planning schemes.

Modeling and Future Scenario Setting of Urban Energy Demand Based on District Energy System

2006 ◽  
Vol 41 (0) ◽  
pp. 187-187
Author(s):  
Yoshiyuki Shimoda ◽  
Yohei Yamaguchi ◽  
Takashi Asai ◽  
Minoru Mizuno
Keyword(s):  
Energy Demand ◽  
Energy System ◽  
Future Scenario ◽  
District Energy ◽  
Urban Energy

An Integrated Energy Strategy for the Optimization of Retrofit Actions in Urban Planning

2014 ◽  
Vol 935 ◽  
pp. 312-315
Author(s):  
Ilaria Falcone ◽  
Michele Grimaldi
Keyword(s):  
Energy Consumption ◽  
Urban Planning ◽  
Energy Demand ◽  
Energy Savings ◽  
Research Work ◽  
Decision Support Tool ◽  
Energy System ◽  
Support Tool ◽  
Energy System Model ◽  
Urban Energy

This research work aims at providing a methodology to analyze quantitatively energy sustainability of existing urban fabric and creating an urban energy system model as a decision support tool for the urban planning processes. Spatially resolved energy demand allows the identification of critical areas of energy consumption (CECA), in particular, a local-type spatial analysis has been adopted, GIS based, using a Kernel density estimation (KDE) and maps algebra. Within the CECA a simulation of energy consumption on an annual base for a representative building was carried out, in order to explore and estimate limits and vulnerabilities and to propose a hierarchy of energy-savings measures, addressing different scales of criticality in urban energy systems, from the city to district and block level.

Urban Building Energy Planning With Space Distribution and Time Dynamic Simulation

2008 ◽  
Author(s):  
Lin Fu ◽  
Zhonghai Zheng ◽  
Hongfa Di ◽  
Yi Jiang
Keyword(s):  
Dynamic Simulation ◽  
Energy Demand ◽  
Air Conditioning ◽  
Energy System ◽  
Building Energy ◽  
Space Distribution ◽  
Energy Planning ◽  
Energy Sources ◽  
Time Dynamic ◽  
Urban Energy

It’s important to deal with building energy-saving in one city level and plan the energy system from one building to one city level. It’s suggested strongly to conduct urban building energy planning in urban planning system in China. There are two main characteristics of urban building energy system. That is, firstly, the terminal building energy demand is dynamic timely, such as the heating, cooling, gas and electricity load of 8760 hours a year with peak and valley load. Secondly, the energy demand, energy sources supply, energy equipments and networks of heating, cooling, gas and electricity are distributed in urban space. It’s meaningful to conduct an innovative urban energy planning with space distribution and time dynamic simulation. In this paper, the energy planning method with space and time characteristics is presented and analyzed briefly. In the meanwhile, to meet the same energy demand in buildings, such as heating, air conditioning, gas and electricity, different energy equipments such as boiler, CHP, CCHP and heat pump based on different energy sources such as coal, gas and electricity can be planned and should be alternative among those energy sources and equipments. Thus, a well alternative urban energy system with high energy efficiency and low environmental emission should be simulated. Therefore, an urban building energy planning (UBEP) simulation tool developed by our research group is introduced. And finally, a case of energy planning in Beijing City in 2010 for heating and air conditioning system is simulated dynamically and analyzed.

scholarly journals Linking Dynamic Building Simulation with Long-Term Energy System Planning to Improve Buildings Urban Energy Planning Strategies

Smart Cities ◽  
2020 ◽  
Vol 3 (4) ◽  
pp. 1242-1265
Author(s):  
Lidia Stermieri ◽  
Chiara Delmastro ◽  
Cristina Becchio ◽  
Stefano Paolo Corgnati
Keyword(s):  
Energy Consumption ◽  
Energy Demand ◽  
Clean Energy ◽  
Energy System ◽  
Building Energy ◽  
Building Simulation ◽  
Energy Planning ◽  
Low Grade ◽  
Urban Energy ◽  
The Impact

The building sector is currently responsible of 40% of global final energy consumption, influencing the broader energy system in terms of new electricity and heat capacity additions, as well as distribution infrastructure reinforcement. Current building energy efficiency potential is largely untapped, especially at the local level where retrofit interventions are typically enforced, neglecting their potential synergies with the entire energy system. To improve the understanding of these potential interactions, this paper proposes a methodology that links dynamic building simulation and energy planning tools at the urban scale. At first, a detailed bottom-up analysis was conducted to estimate the current and post-retrofit energy demand of the building stock. The stock analysis is further linked to a broader energy system simulation model to understand the impact of building renovation on the whole urban energy system in terms of cost, greenhouse gas emission, and primary energy consumption up to 2050. The methodology is suited to analyze the relationship between building energy demand reduction potential and clean energy sources’ deployment to shift buildings away from fossil fuels, the key priority for decarbonizing buildings. The methodology was applied to the case study city of Torino, Italy, highlighting the critical role of coupling proper building retrofit intervention with district-level heat generation strategies, such as modern district heating able to exploit low-grade heat. Being able to simulate both demand and supply future alternatives, the methodology provides a robust reference for municipalities and energy suppliers aiming at promoting efficient energy policies and targeted investments.

scholarly journals Automatic energy demand and system simulation at district level

2021 ◽  
Author(s):  
Verena Weiler ◽  
Ursula Eicker
Keyword(s):  
Energy Demand ◽  
Focal Point ◽  
Energy System ◽  
The Public ◽  
Heat Demand ◽  
Demand Reduction ◽  
Local Decision ◽  
Automatic Simulation ◽  
Supply Systems ◽  
Local Decision Makers

AbstractThe importance of climate protection and sustainability is steadily increasing all over the world. However, there is a large potential for reducing emissions in the heating demand reduction and renewable heat supply of buildings that needs to be addressed. Therefore, a method was developed within the scope of this work that allows local decision-makers such as energy supply companies, project developers and the public sector to calculate, evaluate and compare different scenarios to make buildings and city districts more sustainable based on few and widely available input data. It includes both the determination of the heat demand and measures for its reduction as well as the selection and simulation of centralised and decentralised supply systems. A combination of different methods from the fields of geoinformatics, heuristic decision-making and object-oriented modelling is used. The latter forms a focal point in the work with the development of a data model for energy system components to enable automatic simulation. The applicability as well as the transferability of the method is shown in several case studies. Based on the simulations results, which can be related to CO2 emissions as well as costs, recommendations for the implementation of measures can be given and implemented.The paper is a summary of the dissertation with the title “Automatische Simulation von Wärmebedarf und -versorgung auf Quartiersebene” by the first author at Karlsruhe Institute for Technology.

Urban Energy System Planning and Chinese Low-Carbon Eco-City Case Study

2012 ◽  
Vol 433-440 ◽  
pp. 1338-1345 ◽  
Author(s):  
Hao Liang ◽  
Wei Ding Long ◽  
J. Keirstead ◽  
N. Samsatli ◽  
Nilay Shah
Keyword(s):  
Energy Flow ◽  
Energy Demand ◽  
Flow Distribution ◽  
Energy System ◽  
Low Carbon ◽  
System Planning ◽  
Demand Prediction ◽  
Urban Energy ◽  
Energy System Planning

An integrated urban energy system planning model named SynCity which could make overall considerations of architecture site selection and layout, energy demand prediction, energy technologies optimal selection and energy flow distribution is shown in this paper and demonstrates it in the case of Shanghai Lingang New City. By case study simulation it offers a promising low-carbon emission solution which is the combination of gas engine heat pump and building cooling, heating and power. The energy flow between different cells of the city is obtained at the same time.

scholarly journals Local Energy Planning Potentialities in Reducing São Paulo’s Inequalities

2021 ◽  
Vol 24 ◽  
Author(s):  
Flávia Mendes de Almeida Collaço ◽  
Célio Bermann
Keyword(s):  
Renewable Energy ◽  
Simulation Model ◽  
Energy Demand ◽  
Ghg Emissions ◽  
Energy System ◽  
Energy Planning ◽  
Local Energy ◽  
Urban Energy ◽  
The City ◽  
Energy Strategies

Abstract This study analyzes the local energy planning (LEP), a set of urban energy strategies and potential scope, for São Paulo from 2014 to 2030. A simulation model is used to quantify the impacts of implementing LEP strategies on the city’s energy system based on three indicators: energy demand, percentage usage of renewable sources, and greenhouse gas (GHG) emissions. The performance of LEP strategies was analyzed for two scenarios: the first reproduces the city policies in force, and the second expands the population’s access to city energy services. Considering the implementation of LEP in the first scenario, the city exhibits a 65% usage of renewable energy and a 43% reduction in GHG emissions in 2030. Furthermore, implementation of the same strategies in the second scenario, also for 2030, results in a 67% usage of renewable energy with a 24% reduction in emissions compared to 2014.

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