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Energy-system scenarios are widely used to relate the developments of the energy supply and the resulting carbon-emission pathways to political measures. To enable scenario analyses that adequately capture the variability of renewable-energy resources, a specialised type of power-sector model (PSM) has been developed since the beginning of this century, which uses input data with hourly resolution at the national or subnational levels. These models focus on techno-economic-system optimisation, which needs to be complemented with expert socioeconomic knowledge in order to prevent solutions that may be socially inacceptable or that oppose political goals. A way to integrate such knowledge into energy-system analysis is to use information from framework scenarios with a suitable geographical and technological focus. We propose a novel methodology to link framework scenarios to a PSM by applying complexity-management methods that enable a flexible choice of base scenarios that are tailored to suit different research questions. We explain the methodology, and we illustrate it in a case study that analyses the influence of the socioeconomic development on the European power-system transition until 2050 by linking the power-sector model, REMix (renewable-energy mix), to regional framework scenarios. The suggested approach proves suitable for this purpose, and it enables a clearer link between the impact of political measures and the power-system development. [ABSTRACT FROM AUTHOR]

It is key in the development of wave energy systems to aim at designing economically competitive solutions that enable maximal annual energy production. Previous studies identify the Wave Energy Converter (WEC) structure, i.e. the hull, to have one of the largest cost reduction potentials. Due to this potential, geometry optimisation of WECs has been previously considered, however, most of these studies have been limited by the simplicity of the employed geometrical shapes and the lack of accurate cost models. It is, therefore, important to include an adaptable geometry definition capable of generating diverse WEC shapes, and to account for other factors that can have an effect on costs. These considerations result in a more challenging optimisation problem, and a more complex objective function. The goal of this study is to address the challenge of finding a suitable and efficient optimisation method for WEC geometry design. In this paper, different geometry definitions, such as using simple shapes or B-spline surfaces, and different meta-heuristic optimisation algorithms, such as genetic algorithms or particle swarm optimisation are applied to this problem to find the most suitable choices. Results show an improvement in final objective function values of up to 224% when using an adaptable geometry definition and up to 11% when employing the most suitable optimisation algorithm compared to previous results. In conclusion, the choice of the different elements of the optimisation formulation have a large impact on the quality of the optimisation results and should be based on preliminary studies as presented here. • A comprehensive optimisation method is required for wave energy converter design. • The main elements for wave energy converter geometry optimisation were studied. • Meta-heuristic algorithms are suitable for WEC geometry optimisation. • Genetic and particle swarm optimisation algorithms suit different study cases. • Geometry definitions based on bicubic B-splines achieve better optimisation results. [ABSTRACT FROM AUTHOR]

Current wave energy development initiatives assume that available designs have the potential for success through continuous learning and innovation-based cost reduction. However, this may not be the case, and potential winning technologies may have been overlooked. The scenario creation tool presented in this paper provides a structured method for the earliest stages of design in technology development. The core function of the scenario creation tool is to generate and rank scenarios of potential Wave Energy Converter (WEC) attributes and inform the user on the areas of the parameter space that are most likely to yield commercial success. This techno-economic tool uses a structured innovation approach to identify commercially attractive and technically achievable scenarios, with a scoring system based on their power performance and costs. This is done by leveraging performance and cost data from state-of-the-art wave energy converters and identifying theoretical limits to define thresholds. As a result, a list of scored solutions is obtained depending on resource level, wave energy converter hull shape, size, material, degree of freedom for power extraction, and efficiency. This scenario creation tool can be used to support private and public investors to inform strategy for future funding calls, and technology developers and researchers in identifying new avenues of innovation. [ABSTRACT FROM AUTHOR]