Exploratory assessment of adaptive pathways toward renewable energy systems: a modelling framework facilitating decision making under deep uncertainty

Michas, Serafeim; Μίχας, Σεραφείμ

Διερευνητική αξιολόγηση προσαρμοστικών μονοπατιών για την μετάβαση σε συστήματα ανανεώσιμων πηγών ενέργειας: πλαίσιο μοντελοποίησης για την υποστήριξη αποφάσεων υπό συνθήκες μεγάλης αβεβαιότητας

Doctoral Thesis

Author

Michas, Serafeim

Μίχας, Σεραφείμ

Date

2024

Abstract

The European energy and climate policy is frequently revised in order to be aligned with uncertain factors, such as the influence of human activity on climate change, geopolitical tendencies, and energy market dynamics. Given such uncertainties, member states encounter difficulties in formulating their national contributions via the National Energy and Climate Plans, since, in addition to strengthening clean energy objectives, modifications to European energy and climate policy may entail structural adjustments, such as the minimization of natural gas use as an intermediate fuel during the energy transition. Hence, member states must not only select new technological trajectories, but also make decisions for implemented expenditures that may contradict with the revised European policy. Given the notable uncertainties that the European Union has encountered in recent years, including the economic crisis, the COVID-19 pandemic, and the energy crisis of 2022, energy policy and the energy models supporting it must shift away from optimized projections made under linear assumptions. Instead, modelling simulations and the consequent energy policy formulation, should be characterized by adaptability to non-linear trends. This is the case of exploratory assessment of adaptive pathways toward renewable energy systems. The purpose of this doctoral dissertation is the development of a modeling framework that: • Performs exploratory analysis of policy/strategy options, to identify those that perform well under deep uncertainty, while specifying coping strategies that can be implemented in the case of realization of unlikely uncertainties. • Supports adaptive policy making, by specifying why and when a policy change should be sought, which policies/strategies are prone to specific uncertainties, and therefore making explicit what should be monitored to trigger adaptation during actual implementation. • Supports stepwise implementation of policies. This means that a policy or strategy may be chosen for implementation for a specific period of time by a stakeholder, and the results, as well as the plausible policy/strategy pathways forward, are updated almost instantly. With this feature, a tight participatory modelling process is feasible. Based on the above, the doctoral dissertation answers to the following main research question: “How could energy models support the exploratory assessment of adaptive policies towards the design of electricity systems based on renewables, which are resilient to contextual uncertainties?” More precisely, the dissertation focuses on three major challenges during the shift towards energy systems that are abundant in renewable energy sources (RES). • consumer engagement in the energy transition, • minimum waste of renewable energy, and • shielding the electricity system from external disruptions. The application of the modelling framework to the case study of Greece’s energy transition showcased its usefulness towards adaptive and robust policymaking. Specifically, policies for incentivizing citizens to participate in the energy transition through investments in small-scale photovoltaic systems were evaluated. Subsequently, mixes of RES and storage which minimize curtailment were explored, identifying those that minimize the cost of integrating renewable energy into the electricity mix. Finally, power generation mixes which disengage Greece’s electricity generation from natural gas, while concurrently achieving carbon emission and renewable energy targets in an economically efficient manner were assessed. Overall, the suggested modelling framework improves existing simulation practices, by supporting the development of energy strategies and policies which are robust under uncertainty, facilitating that way policymakers’ short- and long-term energy planning.

Department

Σχολή Ναυτιλίας και Βιομηχανίας. Tμήμα Βιομηχανικής Διοίκησης και Tεχνολογίας

Number of pages

195

Language

English

URI

https://dione.lib.unipi.gr/xmlui/handle/unipi/16391
http://dx.doi.org/10.26267/unipi_dione/3813

Collections

Τμήμα Βιομηχανικής Διοίκησης και Τεχνολογίας

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Except where otherwise noted, this item's license is described as
Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα