Modelling to generate near-Pareto-optimal alternatives (MGPA) for the municipal energy transition

Energy system models are frequently used to support energy planning. Especially at the local level, however, decision-making is difficult because of conflicting interests of diverse stakeholders. This study proposes a new method to overcome such policy dilemmas and demonstrates it for municipal heat and power planning. Modelling to generate near-Pareto-optimal alternatives (MGPA) is a novel combination of the augmented epsilon-constraint method (AUGMECON) and modelling to generate alternatives (MGA). This approach tackles explicit, easy-to-formulate objectives first before exploring a spectrum of alternatives within a region of interest in a second step. MGPA is implemented in a highly adaptable energy system optimisation framework (Backbone) and applied to two municipalities with heterogeneous demands and renewable potentials. By first generating a Pareto front between cost and CO 2 emissions, marginal CO 2 abatement costs and their corresponding decarbonisation potentials are identified. Subsequently, near-Pareto-optimal alternatives are generated and technological trade-offs as well as must-haves and must-avoids are discussed. Depending on the local renewable energy potential available, decarbonisation costs at the municipal level can differ by a factor of five. The diversification resulting from the use of MGPA reveals a broad range of viable solutions, for example without large-scale renewable infrastructure or with up to 95% local power autonomy, but switching to heat pumps remains a must-have in both municipalities. We recommend that energy system modellers adopt a combination of such different multi-objective optimisation methods to improve decision support for the energy transition. • Decision-makers must balance own and stakeholders’ stated and hidden interests. • We propose a novel method combining explicit and implicit multi-objective approaches. • New method demonstrated for energy system models and the municipal energy transition. • Explicit Pareto fronts limit choices by falsely suggesting must-haves and must-avoids. • Implicit modelling to generate alternatives makes a priori assumptions on preferences.

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Publication Details

Journal
Applied Energy
Published
2024-08-22
DOI
https://doi.org/10.1016/j.apenergy.2024.124126
Citations
15
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
3.13

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article

Modelling to generate near-Pareto-optimal alternatives (MGPA) for the municipal energy transition

Valentin Bertsch, Russell McKenna, Febin Kachirayil, Jonas Finke
15 citations
Applied Energy
Integrated Energy Systems Optimization
3.13
article

Modelling to generate near-Pareto-optimal alternatives (MGPA) for the municipal energy transition

Valentin Bertsch, Russell McKenna, Febin Kachirayil, Jonas Finke
article en
15 citations

Abstract

Energy system models are frequently used to support energy planning. Especially at the local level, however, decision-making is difficult because of conflicting interests of diverse stakeholders. This study proposes a new method to overcome such policy dilemmas and demonstrates it for municipal heat and power planning. Modelling to generate near-Pareto-optimal alternatives (MGPA) is a novel combination of the augmented epsilon-constraint method (AUGMECON) and modelling to generate alternatives (MGA). This approach tackles explicit, easy-to-formulate objectives first before exploring a spectrum of alternatives within a region of interest in a second step. MGPA is implemented in a highly adaptable energy system optimisation framework (Backbone) and applied to two municipalities with heterogeneous demands and renewable potentials. By first generating a Pareto front between cost and CO 2 emissions, marginal CO 2 abatement costs and their corresponding decarbonisation potentials are identified. Subsequently, near-Pareto-optimal alternatives are generated and technological trade-offs as well as must-haves and must-avoids are discussed. Depending on the local renewable energy potential available, decarbonisation costs at the municipal level can differ by a factor of five. The diversification resulting from the use of MGPA reveals a broad range of viable solutions, for example without large-scale renewable infrastructure or with up to 95% local power autonomy, but switching to heat pumps remains a must-have in both municipalities. We recommend that energy system modellers adopt a combination of such different multi-objective optimisation methods to improve decision support for the energy transition. • Decision-makers must balance own and stakeholders’ stated and hidden interests. • We propose a novel method combining explicit and implicit multi-objective approaches. • New method demonstrated for energy system models and the municipal energy transition. • Explicit Pareto fronts limit choices by falsely suggesting must-haves and must-avoids. • Implicit modelling to generate alternatives makes a priori assumptions on preferences.

Applied EnergyVol. 376
University Hospitals of the Ruhr-University of Bochum (DE), Paul Scherrer Institute (CH), ETH Zurich (CH), Ruhr University Bochum (DE)
Eidgenössische Technische Hochschule Zürich
Affordable and clean energy
Openalex Percentile: Top 8%
Integrated Energy Systems Optimization
3.13
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