• Energy Research

The Vehicle Routing Problem (VRP) in its manifold variants is widely discussed in scientific literature. We investigate related optimization models and solution methods to determine the state of research for vehicle routing attributes and their combinations. Most of these approaches are idealized and focus on single problem-tailored routing applications. Addressing this research gap, we present a customizable VRP for optimized road transportation embedded into a Decision Support System (DSS). It integrates various model attributes and handles a multitude of real-world routing problems. In the context of urban logistics, practitioners of different industries and researchers are assisted in efficient route planning that allows for minimizing driving distances and reducing vehicle emissions. Based on the design science research methodology, we evaluate the DSS with computational benchmarks and real-world simulations. Results indicate that our developed DSS can compete with problem-tailored algorithms. With our solution-oriented DSS as final artifact, we contribute to an enhanced economic and environmental sustainability in urban logistic applications.

Although Germany has the largest capacity of installed residential photovoltaic (PV) systems in Europe, comprehensive evidence on transparent pricing information remains missing. This study disentangles why PV quote prices are subject to significant dispersion and analyzes which factors influence particularly low- and high-priced systems in Germany. We create a comprehensive cross-sectional dataset of 19 561 PV system quotes from 2011 to 2022 and use regression analyses to investigate the effects of system characteristics, installation scope, and location-related parameters on quoted prices. Our results reveal highly volatile annual price dispersion consistent over 11 years and large price differences despite similar system characteristics. Applying hedonic regression techniques, we reveal spatially fine-resolved price heterogeneity with up to 20 % difference in the German PV market. System characteristics such as battery usage, installation scope, and system capacity have the most significant effect sizes and are instead control variables. More insightful, the installer density shows price-lowering effects, whereas more PV installations per region, higher solar radiation, and higher labor wages cause price-increasing effects. Quantile regression results reveal that installer density promotes the price reduction of high-priced systems more. Scaffolding, AC installation, and elevation are significant price-increasing factors but with small effect sizes. Finally, DC optimizers affect the levels of high-priced systems more than low-priced ones.

AbstractWith rising electricity demand through digitization and innovation, the urgency of climate change mitigation, and the recent geopolitical crisis, stakeholders in developing countries face the complex task to build reliable, affordable, and low-emission energy systems. Information inaccessibility, data unavailability, and scarce local expertise are major challenges for planning and transitioning to decentralized solutions. Motivated by the calls for more solution-oriented research regarding sustainability, we design, develop, and evaluate the web-based decision support system NESSI4Dweb+ that is tailored to the needs and capabilities of various stakeholders in developing countries. NESSI4Dweb+ is open access and considers location-specific circumstances to facilitate multi-energy planning. Its applicability is demonstrated with a case study of a representative rural village in southern Madagascar and evaluated through seven interviews with experts and stakeholders. We show that NESSI4Dweb+ can support the achievement of the United Nations Sustainable Development Goals and enable the very prerequisite of digitization: reliable electrification.

The urgency of climate change mitigation, rising energy prices and geopolitical crises make a quick and efficient energy transition in the building sector imperative. Building owners, housing associations, and local governments need support in the complex task to build sustainable energy systems. Motivated by the calls for more solution-oriented, practice-focused research regarding climate change and guided by design science research principles, we address this need and design, develop, and evaluate the web-based decision support system NESSI. NESSI is an open-access energy system simulator with an intuitive user flow to facilitate multi-energy planning for buildings and neighborhoods. It calculates the technical, environmental, and economic effects of 14 energy-producing, consuming, and storing components of the electric and thermal infrastructure, considers time-dependent effects, and accounts for geographic as well as sectoral circumstances. Its applicability is demonstrated with the case of a single-family home in Hannover, Germany, and evaluated through twelve expert interviews.

The provision of ancillary services (AS) is subject to changes associated with the energy transition. Due to new requirements, the power supply quality, reliability, and safety must be achieved by simultaneously complying with technological, economic, and environmental constraints. To mitigate these challenges, we derive factors responsible for a successful venture of all stakeholders, referred to as critical success factors (CSFs). In a Design Science Research (DSR)-based approach, twelve specific CSFs are deduced from expert interviews with transmission-, plant-, and distribution system operators. These CSFs are evaluated in a focus group discussion with academic experts afterward. We summarize practical results and findings from failed and successful projects concerning energy trading strategies, asset portfolios, grid expansion, and communication technologies. We contribute to AS knowledge and derive recommendations for further research and practice.

The researchers working in the project ZLE developed an “Open Science Declaration” committing their research activities to the standards of Open Science. Research within the ZLE will be built upon the idea of sharing scientific methods, data, and publications to improve research quality and make results accessible to the scientific and non-scientific communities. Members of the ZLE support the principles of Open Science as expressed by the Budapest Open Access Initiative, the Berlin Declaration, the Horizon 2020 Program, and the German Strategy for Open Access. Funded by the Ministry of Science and Culture of Lower Saxony, one of the major goals of the ZLE is to make energy research activities and its resources available for public use while preserving the intellectual property of all involved parties. This will strengthen the research in Lower Saxony by promotion and expansion of cooperation between science and industry on strategic sectors. Moreover, greater transparency in the use of public funds and in the development of research activities is enabled.

Abstract Offshore wind energy is a seminal technology to achieve the goals set for renewable energy deployment. However, today's offshore wind energy projects are mostly not yet sufficiently competitive. The optimization of offshore wind turbine substructures with regard to costs and reliability is a promising approach to increase competitiveness. Today, interdisciplinary analyses considering sophisticated engineering models and their complex economic effects are not widespread. Existing approaches are deterministic. This research gap is addressed by combining an aero-elastic wind turbine model with an economic viability model for probabilistic investment analyses. The impact of different monopile designs on the stochastic cost-efficiency of an offshore wind farm is investigated. Monopiles are varied with regard to diameters and wall thicknesses creating designs with increased lifetimes but higher capital expenditures (durable designs) and vice versa (cheaper designs). For each substructure, the aero-elastic wind turbine model yields distributions for the fatigue lifetime and electricity yield and different capital expenditures, which are applied to the economic viability model. For other components, e.g. blades, constant lifetimes and costs are assumed. The results indicate that the gain of increased stochastic lifetimes exceeds the benefit of reduced initial costs, if the overall lifetime is not governed by other turbine components' lifetimes.