Abstract
To tackle the climate crisis, the European energy strategy relies on consumers taking ownership of the energy transition, accelerating decarbonisation through investments in low-carbon technologies and ensuring system stability and reliability by actively participating in the market. Therefore, tools are needed to better understand an increasingly complex and actor-dense energy system, tracking socio-technical dynamics that occur at its margins and then predicting the effects on larger scales. Yet, existing domestic energy demand models are not flexible enough to incorporate a wide range of socio-technical factors, and to be incorporated into larger energy system simulation environments. Here, a co-simulation design for domestic energy demand modeling is presented and motivated on the basis of four design principles: granularity, scalability, modularity and transparency. Microsimulation of domestic energy demand, through the Python open source library demod, shows that it is possible to achieve high detail and high temporal resolution without compromising scalability. Furthermore, mosaik, an open source co-simulation framework, makes it possible to generate, integrate and orchestrate a multitude of demod-based instances with other independent models, which for the illustrative purposes of this study are represented by a heat pump model. The authors hope that the detailed documentation of the proposed solution will encourage interdisciplinary and collaborative efforts to develop a simulation ecosystem capable of investigating alternative energy transition pathways and evaluating policy interventions through the socio-technical lens.
Highlights
Since the energy crisis of the early 1970s, energy demand models have received great interest because of their relevance in predicting, quantifying and planning electricity generation needs and designing related policy interventions (Swan and Ugursal 2009)
The common thread running through these changes is the new consumer-centric energy system paradigm, “[...] where citizens take ownership of the energy transition, benefit from new technologies to reduce their bills, participate actively in the market, and where vulnerable consumers are protected.” (European Commission 2015)[p.2]
The idea of modeling the consumer as a sink (Hilpert et al 2018) prevails, and the use of empirical or synthetic load profiles to be fed into other models, e.g., to optimize the design of distributed energy systems (Dorer et al 2016) or evaluate the performance of new management strategies (Mammoli et al 2019)
Summary
Since the energy crisis of the early 1970s, energy demand models have received great interest because of their relevance in predicting, quantifying and planning electricity generation needs and designing related policy interventions (Swan and Ugursal 2009). Traditional methods to model energy demand are being challenged by several emerging issues: (i) the profound change in nature, timing, ownership and dispatchability of electricity supply requires higher spatial and temporal resolution of energy demand (Camargo and Stoeglehner 2018), (ii) electrification is branching the interactions of a traditionally vertical system across different scales and sectors (e.g., heating and mobility) (?Brundlinger2018) and (iii) new policy interventions and grid management paradigms (e.g., multi-modal demand response programs and local energy systems) are unveiling the limitations of purely techno-economic modeling approaches (Pfenninger et al 2014). The idea of modeling the consumer as a sink (Hilpert et al 2018) prevails, and the use of empirical or synthetic load profiles to be fed into other models, e.g., to optimize the design of distributed energy systems (Dorer et al 2016) or evaluate the performance of new management strategies (Mammoli et al 2019)
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