Sustainable district energy integrating biomass peaking with geothermal baseload heating: A case study of decarbonizing Cornell's energy system

2020 ◽  
Vol 12 (6) ◽  
pp. 066302
Author(s):  
Nazih Kassem ◽  
James Hockey ◽  
Steve Beyers ◽  
Camilo Lopez ◽  
Jillian L. Goldfarb ◽  
...  
2021 ◽  
Author(s):  
Zahra Ghaemi ◽  
Thomas T. D. Tran ◽  
Amanda D. Smith

In this study, a framework is developed to perform two-stage stochastic programming in a district energy system. This framework optimizes the sizing of energy components to minimize the total cost and operating $CO_2$ emissions. Uncertainties in electricity demand, solar irradiance, wind speed, and electricity emissions are considered. A group of buildings at University of Utah is used as the case study to test the optimization framework. This study is novel by forming an open-source framework, considering electricity emissions with more details compared to previous studies in the literature, and performing the optimization for a campus in the U.S. This study’s results show the trade-off between cost and emissions when different energy configurations are used for three electricity purchasing cases. This framework can help facility managers to evaluate the optimum sizing of their district energy system to minimize the cost and emissions.


Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7257
Author(s):  
Adrian Grimm ◽  
Patrik Schönfeldt ◽  
Herena Torio ◽  
Peter Klement ◽  
Benedikt Hanke ◽  
...  

We present a method to turn the results of model-based optimisations into resilient and comprehensible control strategies. Our approach is to define priority lists for all available technologies in a district energy system. Using linear discriminant analysis and the results of the optimisations, these are then assigned to discrete time steps using a set of possible steering parameters. In contrast to the model-based optimisations, the deduced control strategies do not need predictions or even perfect foresight but solely rely on data about the present. The case study using priority lists presents results in terms of emissions and prices that are only about 5% off the linear optimum. Considering that the priority lists only need information about the present, the results of the control strategies obtained using the proposed method can be considered competitive.


2018 ◽  
Vol 211 ◽  
pp. 269-281 ◽  
Author(s):  
Jin Hou ◽  
Peng Xu ◽  
Xing Lu ◽  
Zhihong Pang ◽  
Yiyi Chu ◽  
...  

Smart Cities ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 1039-1057
Author(s):  
Amro M. Farid ◽  
Asha Viswanath ◽  
Reem Al-Junaibi ◽  
Deema Allan ◽  
Thomas J. T. Van der Van der Wardt

Recently, electric vehicles (EV) have gained much attention as a potential enabling technology to support CO2 emissions reduction targets. Relative to their internal combustion vehicle counterparts, EVs consume less energy per unit distance, and add the benefit of not emitting any carbon dioxide in operation and instead shift their emissions to the existing local fleet of power generation. However, the true success of EVs depends on their successful integration with the supporting infrastructure systems. Building upon the recently published methodology for the same purpose, this paper presents a “systems-of-systems” case study assessing the impacts of EVs on these three systems in the context of Abu Dhabi. For the physical transportation system, a microscopic discrete-time traffic operations simulator is used to predict the kinematic state of the EV fleet over the duration of one day. For the impact on the intelligent transportation system (ITS), the integration of EVs into Abu Dhabi is studied using a multi-domain matrix (MDM) of the Abu Dhabi Department of Transportation ITS. Finally, for the impact on the electric power system, the EV traffic flow patterns from the CMS are used to calculate the timing and magnitude of charging loads. The paper concludes with the need for an intelligent transportation-energy system (ITES) which would coordinate traffic and energy management functionality.


Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 461
Author(s):  
Isabel Azevedo ◽  
Vítor Leal

This paper proposes the use of decomposition analysis to assess the effect of local energy-related actions towards climate change mitigation, and thus improve policy evaluation and planning at the local level. The assessment of the impact of local actions has been a challenge, even from a strictly technical perspective. This happens because the total change observed is the result of multiple factors influencing local energy-related greenhouse gas (GHG) emissions, many of them not even influenced by local authorities. A methodology was developed, based on a recently developed decomposition model, that disaggregates the total observed changes in the local energy system into multiple causes/effects (including local socio-economic evolution, technology evolution, higher-level governance frame and local actions). The proposed methodology, including the quantification of the specific effect associated with local actions, is demonstrated with the case study of the municipality of Malmö (Sweden) in the timeframe between 1990 and 2015.


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