City energy modelling - Optimising local low carbon transitions with household budget constraints

Dias, Luís; Simões, Sofia; Gouveia, João Pedro; Seixas, Júlia

doi:10.1016/j.esr.2019.100387

Cited by 28 publications

(18 citation statements)

References 42 publications

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“…They use quantitative tools to physically model the energy system; take energy consumption, emission, or economy as constraints; and obtain the best transition pathway through scenario comparison. Currently, more than 60 energy system modeling tools can be used for urban or wider energy transition planning [27,28], such as LEAP [29], EnergyPLAN [30], TIMES [31], and City Energy Analyst [32]. However, a data gap is the biggest challenge for such methods.…”

Section: Planning Methodsmentioning

confidence: 99%

A Comprehensive Planning Method for Low-Carbon Energy Transition in Rapidly Growing Cities

et al. 2022

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Coping with climate change requires promoting low-carbon energy transition (LCET) in cities. However, the planning method of LCET for rapidly growing cities deserves further study because it involves dynamicity and interactions of multiple factors. This paper aims to put forward a comprehensive methodology to fill that gap. First, a theoretical framework of “energy system–sustainability–governance–operation of rapidly growing cities” is put forward to explain the general mechanism of LCET. Second, a three step method is built for LCET planning, including energy system analysis based on low emissions analysis platform modeling, operation analysis applying multilevel perspective and stakeholder theories, and governance evaluation by policy review. To verify this method, a city in Western China, Chengdu, was selected as the case study. The results show that Chengdu’s energy related CO2 emissions are expected to peak in 2025 under timely and aggressive measures. The main obstacles lie in three aspects: techno–economic insufficiencies, lack of social cognition, and problems of institution and policy. To realize this scenario, Chengdu must incorporate the target and pathway of a carbon peak as soon as possible into its policy system and enhance the coordination among governmental departments.

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Section: Planning Methodsmentioning

confidence: 99%

A Comprehensive Planning Method for Low-Carbon Energy Transition in Rapidly Growing Cities

et al. 2022

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“…Do you want to develop a data storage facility? You can do the same thing with Hive, but you'll need to learn the techniques to make Hive an effective weapon for ELT tool [24][25][26][27]. As shown in Figure 1, the transformation process basically involves putting the datasets in the most appropriate format suitable for analysis.…”

Section: Methodsmentioning

confidence: 99%

Application of big data for distribution and consumption of power

Mukaila¹,

Adeniyi

Ogundokun

et al. 2021

TELKOMNIKA

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The exponentially growing and tremendous collection of data stored in the power sector, combined with the need for data analysis, has produced an urgent need for powerful tools to extract hidden data as to effectively distribute the power for proper consumption for the household. This research work was embarked on to show the business value of big data analytics in Energy and utilities with a focus on how analytics can help solve problems of inefficiency and wastages in electricity generation, production and distribution and how raw energy datasets can be converted into insights that can be used by energy policy makers to make major business decisions. To explicitly show how raw data can be turned into insights, the study deploys the use of the Hadoop on Hortonworks' open-source apache-Hive licensed data warehousing framework run on a windows operating system to turn raw datasets (in excel formats converted to .csv format) gotten from the prepaid meters of 196,000 consumers (households and businesses) in 11 business units of Ikeja Electricity Distribution Company (IKEDC, Nigeria) to analyze the distribution and consumption of power.

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“…Besides the limitation in available area for each PT, the previous scenarios considered the installed PV capacity as an unbounded variable, constrained only by location (city or winery). Although this increases the search space of optimal system configurations, the fact is that the deployment of residential-scale PV is highly dependent on local RES adoption targets or climate change mitigation plans set up by municipalities or other regional actors [23,51]. However, the integration of such plans within the present modeling framework is straightforward.…”

Section: Both Actors As Prosumers Assuming Two Pv Adoption Scenarios For the Citymentioning

confidence: 99%

“…The model the authors present has a coupled structure combining MILP and Model Predictive Control approaches. Other works explore well-established energy modeling tools such as TIMES [21][22][23] and EnergyPLAN [24][25][26] to study and optimize energy systems at the district or city scales, considering multiple energy sources and/or longer-term periods of analysis. Chen et al explored the SystemC-AMS framework to design and simulate a power grid encompassing a residential community of 15 houses, a wind turbine, a PV array, and a battery pack [27].…”

Section: Introductionmentioning

confidence: 99%

Modeling Energy Communities with Collective Photovoltaic Self-Consumption: Synergies between a Small City and a Winery in Portugal

Luz

Silva

2021

Energies

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The recently approved regulation on Energy Communities in Europe is paving the way for new collective forms of energy consumption and production, mainly based on photovoltaics. However, energy modeling approaches that can adequately evaluate the impact of these new regulations on energy community configurations are still lacking, particularly with regards to the grid tariffs imposed on collective systems. Thus, the present work models three different energy community configurations sustained on collective photovoltaics self-consumption for a small city in southern Portugal. This energy community, which integrates the city consumers and a local winery, was modeled using the Python-based Calliope framework. Using real electricity demand data from power transformers and an actual winery, the techno-economic feasibility of each configuration was assessed. Results show that all collective arrangements can promote a higher penetration of photovoltaic capacity (up to 23%) and a modest reduction in the overall cost of electricity (up to 8%). However, there are clear trade-offs between the different pathways: more centralized configurations have 53% lower installation costs but are more sensitive to grid use costs (which can represent up to 74% of the total system costs). Moreover, key actor’s individual self-consumption rate may decrease by 10% in order to benefit the energy community as a whole.

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City energy modelling - Optimising local low carbon transitions with household budget constraints

Cited by 28 publications

References 42 publications

A Comprehensive Planning Method for Low-Carbon Energy Transition in Rapidly Growing Cities

A Comprehensive Planning Method for Low-Carbon Energy Transition in Rapidly Growing Cities

Application of big data for distribution and consumption of power

Modeling Energy Communities with Collective Photovoltaic Self-Consumption: Synergies between a Small City and a Winery in Portugal

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