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This study presents an innovative framework for leveraging the potential of AI in energy systems through a multidimensional approach. Despite the increasing importance of sustainable energy systems in addressing global climate change, comprehensive frameworks for effectively integrating artificial intelligence (AI) and machine learning (ML) techniques into these systems are lacking. The challenge is to develop an innovative, multidimensional approach that evaluates the feasibility of integrating AI and ML into the energy landscape, to identify the most promising AI and ML techniques for energy systems, and to provide actionable insights for performance enhancements while remaining accessible to a varied audience across disciplines. This study also covers the domains where AI can augment contemporary and future energy systems. It also offers a novel framework without echoing established literature by employing a flexible and multicriteria methodology to rank energy systems based on their AI integration prospects. The research also delineates AI integration processes and technique categorizations for energy systems. The findings provide insight into attainable performance enhancements through AI integration and underscore the most promising AI and ML techniques for energy systems via a pioneering framework. This interdisciplinary research connects AI applications in energy and addresses a varied audience through an accessible methodology.

Cities are adopting energy planning strategies and emission reduction targets in line with national decarbonization targets. Modeling and scenario assessments are used to support energy planning. City energy systems are complex systems including interactions and interdependencies, as well as the specifics of the local city context. To investigate the representation of city-specific system complexities in existing case studies, a systematic literature review methodology is applied, and model applications are analyzed using a comparative analysis framework. Additionally, research objective themes used to define the specific aims are explored. Key modeling characteristics include scale aspects, method description, system definition, scenario formulation, and case-specific model inputs. The findings of this study suggest that city case studies have a diverse representation of modeling approaches. However, the analysis of model characteristics shows a limited representation of modeling features, such as stakeholder participation and local air pollution impacts that are unique to the urban context. In terms of research objective themes behind the model application, four research themes are identified. Studies aimed at identifying pathways to future low-carbon energy systems and evaluating policy impacts on the city energy systems are the most stated research objective themes for modeling city energy systems.

Despite the time‐dependent behavior of carbon stored in plastic materials, literature assessing carbon flows into and from plastic typically applies a static approach. To better understand the climate impacts of such storage, this study explores how carbon stored in plastics can contribute over time to the national climate inventory with various emphasis on recycling. This is accomplished by implementing material stock change estimations for carbon in plastic materials that follow first‐order decay and include impacts from recycling rates in the Integrated MARKAL‐EFOM System model generator for Sweden (TIMES‐Sweden). Thereafter, three approaches to how carbon released from the plastic material stock is accounted for in the national climate inventory were applied to determine how each approach affects resulting emission and net‐zero pathways in different recycling rate scenarios. An accounting approach that follows the first‐order decay pattern of material stocks was found to be important for capturing the impacts of recycling and for neither over‐ nor underestimating the emission impact from carbon stored in plastics. Accounting for carbon stored in plastics may provide important incentives for producing renewable plastics and reducing dependence on carbon removal technologies. Because of its synergies with recycling, the carbon storage potential of plastic products is well worth recognizing and promoting in a policy setting that aims for circularity. For Sweden, this reduces the need for bioenergy carbon capture and storage and makes more biomass‐based carbon and electricity available for use elsewhere in the energy system. Using renewable resources to produce plastic creates the temporary storage of carbon that potentially could contribute with negative emissions to national climate inventories. This study presents a method and approach that accounts for this temporary storage, which is implemented into energy system models, to better understand how this temporary storage can contribute to our climate targets. The result of this study implies that accounting for the negative emissions effect of renewable carbon stored in plastic reduces the need for other carbon removal measures.

The European Union and the Austrian government have set ambitious plans to expand renewable energy sources and lower carbon dioxide emissions. However, the expansion of volatile renewable energy sources may affect today’s energy system. To investigate future challenges in Austria’s energy system, a suitable simulation methodology, temporal and spatially resolved generation and consumption data and energy grid depiction, is necessary. In this paper, we introduce a flexible multi-energy simulation framework with optimization capabilities that can be applied to a broad range of use cases. Furthermore, it is shown how a spatially and temporally resolved multi-energy system model can be set up on a national scale. To consider actual infrastructure properties, a detailed energy grid depiction is considered. Three scenarios assess the potential future energy system of Austria, focusing on the power grid, based on the government’s renewable energy sources expansion targets in the year 2030. Results show that the overwhelming majority of line overloads accrue in Austria’s power distribution grid. Furthermore, the mode of operation of flexible consumer and generation also affects the number of line overloads as well.

This study develops an integrated modeling approach to analyze the effects of different scenarios compared to a baseline (2019) scenario on energy demand and supply in Zambia. Aiming at minimizing costs, the model combines available resources and technologies, adhering to techno-economic and environmental limits. On the demand side, the study uses time series analysis to forecast future electricity demand in Zambia. The supply-side energy model identifies the optimal combination of resources and technologies needed to satisfy exogenously specified electricity demand levels at the least cost. The baseline scenario results revealed that the power outages in Zambia, especially at peak times, have been attributed to reliance on imported fuel for power generation, the slow-paced integration of renewable resources, and not fully utilizing resource potential for the supply side. To overcome the power outages and meet the electricity demand in 2035, a comprehensive scenario analysis was conducted, including the main scenarios of 30% integration of renewable energy, no coal power generation, and low emission targets (10%, 20%, 30%, 40%, and 50% reduction from the baseline). The expected CO2 reductions from the renewable energy scenario, no coal scenario, and 50% low emission target are estimated at 5222 kilotons in 2035, respectively.

Energy security analysis is a strong tool for policy makers. It allows them to formulate policies that would enhance energy systems by targeting necessary actions. In this study, the impacts of transitioning from a fossil fuels to a renewables dominated energy system on energy security is analysed for Jordan. A Best Policy Scenario was developed for the Jordanian energy system to trace the transition to a 100% renewable energy system. Energy security was analysed for the future system by a qualitative approach utilising colour codes. The results reveal that the primary energy demand increases from 64 TWh in 2015 to 130 TWh in 2050, dominated by electricity and followed by heat and bioenergy. This indicates that a high level of direct and indirect electrification is the key to transition towards a fully sustainable energy system. Renewable electricity generation is projected to increase from 0.1 TWh in 2015 to 110.7 TWh in 2050, with a solar photovoltaic share of 92%. The levelised cost of energy develops from 78 €/MWh in 2015 to 61 €/MWh in 2050. In 2050, this system will have zero greenhouse gas emissions, it will provide plenty of job opportunities and revenue generation. This proposed transition will enhance the energy security level of the Jordanian energy system in five of the six dimensions studied. The five dimensions that will be improved are availability, cost, environment, health, and employment, whereas the dimension on diversity will stay neutral. It can be concluded that Jordan can achieve a 100% renewable energy system by 2050 and such a transition will enhance the energy security level.

A 100% renewable energy (RE) scenario featuring high participation in vehicle-to-grid (V2G) services was developed for the Åland islands for 2030 using the EnergyPLAN modelling tool. Hourly data was analysed to determine the roles of various energy storage solutions, notably V2G connections that extended into electric boat batteries. Two weeks of interest (max/min RE) generation were studied in detail to determine the roles of energy storage solutions. Participation in V2G connections facilitated high shares of variable RE on a daily and weekly basis. In a Sustainable Mobility scenario, high participation in V2G (2750 MWhe) resulted in less gas storage (1200 MWhth), electrolyser capacity (6.1 MWe), methanation capacity (3.9 MWhgas), and offshore wind power capacity (55 MWe) than other scenarios that featured lower V2G participation. Consequently, total annualised costs were lower (225 M€/a). The influence of V2G connections on seasonal storage is an interesting result for a relatively cold, northern geographic area. A key point is that stored electricity need not only be considered as storage for future use by the grid, but V2G batteries can provide a buffer between generation of intermittent RE and its end-use. Direct consumption of intermittent RE further reduces the need for storage and generation capacities.

The Paris Climate Accord calls for urgent CO2 reductions. Here we investigate low and zero carbon pathways based on clean electricity and sector coupling. Effects from different spatialities are considered through city and national cases (Helsinki and Finland). The methodology employs techno-economic energy system optimization, including resilience aspects. In the Finnish case, wind, nuclear, and biomass coupled to power-to-heat and other flexibility measures could provide a cost-effective carbon-neutral pathway (annual costs −18%), but nuclear and wind are, to some extent, exclusionary. A (near) carbon-neutral energy system seems possible even without nuclear (−94% CO2). Zero-carbon energy production benefits from a stronger link to the broader electricity market albeit flexibility measures. On the city level, wind would not easily replace local combined heat and power (CHP), but may increase electricity export. In the Helsinki case, a business-as-usual approach could halve emissions and annual costs, while in a comprehensive zero-emission approach, the operating costs (OPEX) could decrease by 87%. Generally, electrification of heat production could be effective to reduce CO2. Low or zero carbon solutions have a positive impact on resilience, but in the heating sector this is more problematic, e.g., power outage and adequacy of supply during peak demand will require more attention when planning future carbon-free energy systems.

Energy system modelling is an essential practice to assist a set of heterogeneous stakeholders in the process of defining an effective and efficient energy transition. From the analysis of a set of open-source energy system models, it emerged that most models employ an approach directed at finding the optimal solution for a given set of constraints. On the contrary, a simulation model is a representation of a system used to reproduce and understand its behaviour under given conditions without seeking an optimal solution. In this paper, a new open-source energy system model is presented. Multi Energy Systems Simulator (MESS) is a modular, multi-energy carrier, multi-node model that allows the investigation of non optimal solutions by simulating an energy system. The model was built for urban level analyses. However, each node can represent larger regions allowing wider spatial scales to be represented as well. In this work, the tool’s features are presented through a comparison between MESS and Calliope, a state of the art optimization model, to analyse and highlight the differences between the two approaches, the potentialities of a simulation tool and possible areas for further development. The two models produced coherent results, showing differences that were tracked down to the different approaches. Based on the comparison conducted, general conclusions were drawn on the potential of simulating energy systems in terms of a more realistic description of smaller energy systems, lower computational times and increased opportunity for participatory processes in planning urban energy systems.

With its abundance of renewable energy potentials, not only for hydropower and bioenergy, but also for wind and solar, Brazil provides good prospects for a carbon neutral energy system. The role of an enhanced coupling of the power, heat and transport sectors in such systems is not yet fully understood. This paper analyses the least-cost composition and operation of a fully renewable power supply system as part of a carbon neutral energy supply in Brazil. It relies on the application of the high-resolution energy system model REMix. Our analysis reveals that the expansion of wind and solar power is more cost-efficient than the construction of additional hydroelectric plants. This is favoured because the existing hydroelectric plants offer large capacity of dispatchable power to compensate for fluctuations, and thus no additional storage is necessary. Furthermore, the REMix analysis indicates that varying shares of solar and wind power technologies as well as the spatial distribution of power generation have only a small influence on supply costs. This implies that the transformation strategy in Brazil can be primarily based on other criteria such as regional development, public acceptance, environmental impact or industrial policy without major impacts on system costs.