Energy System Model Research Articles

An assessment of energy system transformation pathways to achieve net-zero carbon dioxide emissions in Switzerland

Switzerland has one of the lowest carbon intensities among industrialised countries. However, its transition to net-zero carbon dioxide emissions is complicated by limited domestic mitigation options, which tend to increase costs, raise energy security concerns, and trigger socio-economic barriers in policy implementation. Research on these issues is relevant to the societal and political debates on energy transition worldwide. Here we apply a well-established techno-economic energy systems model and highlight the challenges of the Swiss energy transition under different technical, socio-economic, and geopolitical contexts. We suggest feasible technical solutions based on low-carbon technologies, efficiency, and flexibility. We find that import independency and net-zero emissions by 2050 require an additional cumulative discounted investment, compared to a business-as-usual scenario, of 300 billion CHF2019 in energy efficiency, negative emissions and renewable technologies. The average per capita costs of net-zero emissions are 320–1390 CHF2019/yr. from 2020 to 2050, depending on exploited domestic mitigation options, integration into international energy markets, and energy security ambition.

Techno-economic optimization of the industrial excess heat recovery for an industrial park with high spatial and temporal resolution

With increasing heating and cooling demands, decarbonisation of the heating and cooling sectors is key to achieving a carbon–neutral energy system. Using industrial excess heat in heating systems helps offset emissions by reducing the use of fossil fuels. While several studies have analysed the temperature of heat availability, the cost of extending or constructing the heating network and techno-economic feasibility, it is important to consider all aspects together to achieve a comprehensive design of industrial excess heat recovery. This study proposes a method to link an energy system optimisation tool with a spatial analysis tool and an exergy analysis tool to achieve a comprehensive design. An iterative soft link is implemented between the energy system model and the spatial analysis tool for high spatial and temporal resolution. The developed method is applied to a case study of an industrial park in Greece. Scenarios are developed to assess the robustness of the developed method and the system profitability of excess heat recovery. The scenarios indicated that the profitability of excess heat depends heavily on the price of natural gas with the share of excess heat increasing from 10% to 45% with a 20% increase in natural gas prices in cases where heat pumps are needed for temperature boosting. In cases where heat pumps are not needed, excess heat indicates higher system profitability with a share of around 40% and reduces the emissions by around 50 times. The method provides robust results in considered scenarios with convergence within four iterations.

Prospects for the 2040 Norwegian electricity system: Expert views in a probabilistic modeling approach

This study examines expert opinions on power demand and supply developments for 2040 in Norway based on a combined survey and modeling approach. The survey responses show that production and consumption will likely increase, with most respondents assuming a positive energy balance in 2040 Norway. Capacity expansion uncertainty between expert opinions is particularly high for offshore wind on the production side and electricity demand from hydrogen electrolysis on the consumption side. The survey results are combined with a Monte Carlo modeling approach to estimate solution spaces for electricity prices, value factors, and market values for power generating technologies in the energy system model Balmorel. The model results show that electricity prices are strongly influenced by the energy balance, with a negative exponential relationship between the electricity price and an increase in the energy balance. The value factors for hydropower with reservoirs are consistently the highest across the model runs, while solar PV and hydro run-of-river have the lowest value factors. An increasingly positive energy balance increases hydropower with reservoirs' value factor and decreases the value factor for all other technologies. This indicates an additional competitive advantage for hydropower with reservoirs if production development outpaces demand and vice versa.

Intelligent optimal scheduling strategy of IES with considering the multiple flexible loads

As the energy system continues to evolve and advance, a relatively single energy system gradually turns to the comprehensive energy system. With the advancement of technology related to electric vehicle networks progresses, the flexible load in the power system has been significantly improved, and there will be more and more schedulable resources in the power system. On this basis, the paper mainly studies the integrated energy system including the power station of electric driven vehicles and a variety of flexible loads. First, an intelligent energy system model is built, including wind power, ES, cogeneration units, gas boilers, etc. Secondly, according to the flexible load response of electricity, heat and gas, the dynamic response of flexible loads such as electricity, heat and natural gas is incorporated into the optimal scheduling of the integrated energy system, and a model has been created for optimizing the integrated energy system with the goal of minimizing the system operational expenses. Finally, YALMIP is utilized to formulate the problem during modeling, while CPLEX is employed as the solver to find a solution. Through the example calculation, the system operation cost is reduced by 13.04%, the wind power consumption rate is increased by 8.65%, and the peak valley difference is reduced by 24.58%. This approach has been demonstrated to lower the overall operational expenses of the system, as well as assist in smoothing out peak and off-peak electricity demand, and increase the utilization of wind power.

What is the future of nuclear power in Ukraine? The role of war, techno-economic drivers, and safety considerations

The TIMES-Ukraine energy system model is used to explore the future of nuclear power plants (NPPs) under an ambitious climate policy scenario, achieving net zero greenhouse gas emissions in 2050. Varying techno-economic (construction costs and capacity factors for NPPs, capital costs for solar and wind), policy (ban on construction or extension of NPPs), and macroeconomic (alternative economic recovery trajectories) factors are considered. The difference in the techno-economic assumptions for nuclear power generation has a very moderate impact on the total system costs (TSC) of the energy transition, as their variation (positive or negative change) does not exceed 0.1%–0.2% relative to the default case. Policy decisions on restricting nuclear power generation could have a more substantial impact, as TSC increase by 4–5 billion USD (0.6%–0.9%) over the 2020–2050 period under the most restrictive case. In terms of the economic viability of various NPPs, we find small modular reactors to be more competitive than large NPPs due to the higher availability factor. Overall, in terms of developing new NPP capacities, policymakers can consider alternative futures for this technology without major implications for the energy transition costs, as retired NPPs can be substituted by alternative generation technologies in a cost-competitive manner.

The mutual benefits of comparing energy system models and integrated assessment models

Background: The transition to a carbon neutral society such as that envisaged in the European Union Green Deal requires careful and comprehensive planning. Integrated assessment models (IAMs) and energy system models (ESMs) are both commonly used for policy advice and in the process of policy design. In Europe, a vast landscape of these models has emerged and both kinds of models have been part of numerous model comparison and model linking exercises. However, IAMs and ESMs have rarely been compared or linked with one another. Methods: This study conducts an explorative comparison and identifies possible flows of information between 11 of the integrated assessment and energy system models in the European Climate and Energy Modelling Forum. The study identifies and compares regional aggregations and commonly reported variables We define harmonised regions and a subset of shared result variables that enable the comparison of results across the models. Results: The results highlight similarities and differences on final electricity demand, electricity supply and hydrogen across three levels of aggregation. However, the differences between the regional aggregation of the models limit detailed analysis. Conclusions: This first-of-its-kind comparison and analysis of modelling results across model type boundaries provides modellers and policymakers with a better understanding of how to interpret both IAM and ESM results. It also highlights the need for community standards for region definitions and information about reported variables to facilitate future comparisons of this kind.

How would sustainable transformations in the electricity sector of megacities impact employment levels? A case study of Beijing

The impacts of a transition towards a low-carbon economy on the structure of labor demand are gaining widespread attention among sustainability practitioners and policymakers around the world. This is particularly relevant for megacities with large energy demands and populations, such as Beijing, the capital of China. In this study, we assess the employment impacts of Beijing's energy transition trajectory through a soft-linking approach combining MESSAGEix-Beijing, an energy system model, with Input-Output analysis. We estimate that by 2050, the total employment effect of the electricity sector in Beijing is higher under the baseline (154 thousand people) and indigenous (IND) scenarios (375 thousand people) in comparison to the imported electricity-dependent (EIMP) scenario (28 thousand people). If the input-output interaction between industries is considered, more indirect employment will be created, which will be 1.7–1.9 times more than direct employment. The most significant gains would materialize in the electricity sectors together with the Leasing and Business Service; Finance; and Transport and Telecommunications Services sectors. The indirect and induced employment benefits from the sectoral interrelation and household consumption point to the need for complementary policies in balancing trade-offs between low-carbon transitions and employment levels in the economy.

Modeling and operation optimization of hydrogen-based integrated energy system with refined power-to-gas and carbon-capture-storage technologies under carbon trading

As a promising solution to realize the energetic complementarity and energy cascade utilization, integrated energy system with a large-scale integration of renewable energy garners considerable attention recently. However, the renewable energy curtailment and uncertainty become two prominent challenges. To the end, we establish a hydrogen-based integrated energy system (HIES) operation framework comprising a refined power to gas (P2G) and carbon capture system (CCS) under carbon trading. Subsequently, a Wasserstein metric based distributional robust optimization method (WDRO) is developed to address wind power uncertainty. Finally, numerical analysis is performed. Simulations results show that: (1) the proposed approach can realize a low-carbon electric energy supply and consumption mode and satisfies the hydrogen demand through internal equipment of the system; (2) compared with the benchmark, the proposed model reveals outstanding economic, environmental and energy performance by obtaining 31.81% decline in operation cost, a 20.19% mitigation in CO2 emission, 7.89% reduction of wind power curtailment and a higher energy efficiency; (3) the validation of WDRO model is demonstrated by the data-driven and robustness test. Moreover, the model exhibits advantages due to its trade-off between conservativeness and computational complexity. The optimization results provide a good reference for the HIES investment strategy and government carbon pricing decision.

Key Determinants of Solar Share in Solar- and Wind-Driven Grids

Solar PV is already the cheapest option to produce electricity in many world regions. Moreover, the price of utility-scale solar power plants in 2050, while highly uncertain, will decrease further with present-day learning rates and projected solar capacities. In this article, we analyze how possible future costs of solar and other characteristics affect the optimal share of electricity demand supplied by solar in different energy systems. We first use a simplified, open, hourly resolved, copper-plate model for four isolated regions, with only wind and solar generation and storage allowed, to identify the core dynamics while sweeping the cost of solar. Using this model, we show that future cost assumptions of utility solar affect energy systems in regions with comparable solar and wind potential compared to regions with much stronger solar or much stronger wind potential. Then, we use a multicountry, networked, sector-coupled model of the European energy system (PyPSA-Eur-Sec) to analyze not only the effect of solar characteristics in a comprehensive energy system, but also how our model assumptions themselves affect the optimal share of solar. We find that assumptions of system properties, such as transmission or sector-coupling can greatly affect the optimal solar penetration at the country level.

An energy systems model of large commercial liquid hydrogen aircraft in a low-carbon future

Liquid hydrogen (LH2) aircraft have the potential to achieve carbon neutrality. However, if the hydrogen is produced using electricity grids that utilise fossil fuel, they have a non-zero carbon dioxide (CO2) emission associated with their well-to-wing pathway. To assess the potential of LH2 in aviation decarbonisation, an energy systems comparison of large commercial LH2, liquified natural gas (LNG), conventional Jet-A and LH2 dual-fuel aircraft is presented. The performance of each aircraft is compared towards 2050, over which three system changes occur: (1) LH2 aircraft technology develops; (2) both world average and region-specific grid electricity, which is used to produce the hydrogen, decarbonises; and (3) the International Air Transportation Association (IATA) emissions targets, which are used to restrict the passenger-range performance of each aircraft, tighten. In 2050, the emissions of all aircraft are thus constrained to 0.063 kg-CO2/p-km, relative to 0.110 kg-CO2/p-km for the unconstrained Jet A fuelled Boeing 787-8. It is estimated that, in this year, an LH2 aircraft powered by fuel cells and sourcing world average electricity can travel 6000 km, 20% further than the conventional Jet A aircraft that is also constrained to meet the IATA targets, but not as far as the LNG aircraft. At its maximum range, the LH2 aircraft carries 84% of the Jet A passenger demand. Analysis using region-specific hydrogen indicates that LH2 aircraft can travel further than LNG aircraft in North America only, accounting for 17% of the global demand. 1.59 times the current aviation energy consumption is required if all conventional aircraft are replaced with LH2 designs. Under stricter emissions constraints than those outlined by the IATA, LH2 outperforms LNG in Europe and the Americas, accounting for 41% of the global demand. Also in these regions, the range, energy consumption and passenger capacity of LH2 aircraft can be improved upon by combining the advantages of LH2 with LNG in dual-fuel aircraft concepts. The use of LH2 is therefore advantageous within several prominent niches of a future, decarbonising aviation system.

Designing climate policy mixes: Analytical and energy system modeling approaches

A matter of debate in climate policy is whether lawmakers should rely on carbon pricing or regulations, such as low-carbon standards, to reach emission reduction goals. Past research showed that pricing is more cost-effective. However, previous work studied the two policies when implemented separately, in effect comparing two policy extremes. In contrast, we explore the full spectrum of climate policy mixes that include both types of policies but vary in how much they rely on each. We do this both analytically by extending previous theory and numerically with two energy system models. In line with past work, increasing reliance on pricing increases the cost-effectiveness of the policy mix. However, we show that this benefit exhibits diminishing marginal returns. Thus the gain in cost-effectiveness from complementing stringent standards with modest pricing is relatively large. Our results show that relying on pricing for 20% of emission reductions (and on a standard for 80%) reduces costs by 32%–57% compared to a standard-only approach. Importantly, trading off more of the standard for pricing delivers smaller and smaller gains in cost-effectiveness. For example, a policy mix that relies on each policy for 50% of emission reductions decreases costs by 60%–81%, which is already 71%–88% as cost-effective as the theoretically most cost-effective pricing-only policy.

Spatial representation of renewable technologies in generation expansion planning models

The increasing share of intermittent Renewable Energy Sources (iRES) in the energy mix leads to a growing need for their accurate representation in energy system models. In this paper, we analyze how the results of generation planning models are impacted by the spatial representation used to model intermittent renewable technologies. It is shown that the spatial resolution, and to a lesser extent the spatial aggregation method used in a planning model, have a significant influence on the obtained system cost. The effect is quantified in a case study of European geographical scale, by varying the spatial resolution from highly resolved (hundreds of sites) to highly aggregated (1 site). A resolution-dependency of the system cost is observed under multiple renewable generation targets, and different renewable capacity restrictions. In doing so, we highlight the importance of implementing an appropriate capacity limit, especially when a high spatial resolution is used. Additionally, basic spatial aggregation methods -to process high resolution input data- are compared.

Temporally detailed modeling and analysis of global net zero energy systems focusing on variable renewable energy

This study newly develops a recursive-dynamic global energy model with an hourly temporal resolution for electricity and hydrogen balances, aiming to assess the role of variable renewable energy (VRE) in a carbon-neutral world. This model, formulated as a large-scale linear programming model (with 500 million each of variables and constraints), calculates the energy supply for 100 regions by 2050. The detailed temporal resolution enables the model to incorporate the variable output of VRE and system integration options, such as batteries, water electrolysis, curtailment, and the flexible charging of battery electric vehicles. Optimization results suggest that combing various technical options suitable for local energy situations is critical to reducing global CO2 emissions cost-effectively. Not only VRE but also CCS-equipped gas-fired and biomass-fired power plants largely contribute to decarbonizing power supply. The share of VRE in global power generation in 2050 is estimated to be 57% in a cost-effective case. The results also imply economic challenges for an energy system based on 100% renewable energy. For example, the average mitigation cost in 2050 is 69USD/tCO2 in the cost-effective case, while it increases to 139USD/tCO2 in the 100% renewable case. The robustness of this argument is tested by sensitivity analyses.

PyPSA-Earth. A new global open energy system optimization model demonstrated in Africa

Macro-energy system modelling is used by decision-makers to steer the global energy transition towards an affordable, sustainable and reliable future. Closed-source models are the current standard for most policy and industry decisions. However, open models have proven to be competitive alternatives that promote science, robust technical analysis, collaboration and transparent policy decision-making. Yet, two issues slow the adoption: open models are often designed with particular geographic scope in mind, thus hindering synergies from collaborating, or are based on low spatially resolved data, limiting their use. Here we introduce PyPSA-Earth, an open-source global energy system model with data in high spatial and temporal resolution. It enables large-scale collaboration by providing a tool that can model the world’s energy system or any subset of it. The model is suitable for operational as well as combined generation, storage and transmission expansion studies. In this study, the novel power system capabilities of PyPSA-Earth are highlighted and demonstrated. The model provides two main features: (1) customizable data extraction and preparation with global coverage and (2) a PyPSA energy modelling framework integration. The data includes electricity demand, generation and medium to high-voltage networks from open sources, yet additional data can be further integrated. A broad range of clustering and grid meshing strategies help adapt the model to computational and practical needs. Data validation for the entire African continent is performed and the optimization features are tested with a 2060 net-zero planning study for Nigeria. The demonstration shows that the presented developments can build a highly detailed power system model for energy planning studies to support policy and technical decision-making. We anticipate that PyPSA-Earth can represent an open reference model for system planning, and we welcome joining forces to address the challenges of the energy transition together.

Techno-economic analysis for using hybrid wind and solar energies in Australia

Hybrid energy production from available resources such as wind and solar are identified as an environmentally friendly alternative for power production. Australia, as a developed country, possesses the potential to use renewable energies. Motivated by the lack of comprehensive research dedicated to the economic analysis of hybrid systems in Australia, the objective of the present work is to propose an optimal integrated renewable energy system model in order to fulfill the electrical energy demands in five major Australian cities, namely, Perth, Adelaide, Melbourne, Sydney, and Brisbane. To compare the studied cities, ten types of buildings (hospital, hotel, office, mall, clinic, retail, apartment, supermarket, school, and warehouse) have been analyzed in different climatic zones of Australia. The results have revealed that different viable scenarios for the investigated case studies are obtained. Furthermore, the optimal configuration, along with the cost and carbon emission that is obtained in the study, can be applied as a guideline for designing power systems (with a minimized cost) for the considered communities and other cities with similar characteristics (population and climatic conditions).

FAME-Core: An open Framework for distributed Agent-based Modelling of Energy systems

FAME-Core: An open Framework for distributed Agent-based Modelling of Energy systems

AEM-electrolyzer based hydrogen integrated renewable energy system optimisation model for distributed communities

The development of sustainable and renewable energy technologies has received significant attention to realize Net-Zero CO2 equivalent emission goals and meet the growing energy demand. Hydrogen is a promising energy carrier that can facilitate the large-scale deployment of renewable energy sources and assist in the replacement of fossil fuels and to reduce the impact of global warming. The objective of this research is to present an advanced hydrogen-integrated renewable energy system model to meet the energy demand of a distributed community and produce green hydrogen from excess/curtailed renewable energy. The study employs an anion exchange membrane water electrolyzer (AEM) for producing hydrogen. An optimization model of the renewable energy system and a mathematical model of the electrolyzer are developed to achieve this objective. The model uses an energy maximisation approach and optimally combines wind system, biogas plant, and solar PV system to meet the residential and commercial load demands. To increase the system stability, the model is interconnected with the local grid station for energy exchange. Moreover, an uncertainty analysis is also performed to analyse the system response under random variation in load demand. The study results show that a significant amount of clean energy (15,025 MWh/year) is produced by the system at the lowest levelized cost of 0.084 €/kWh and a reduction of 6,078 tons of CO2 emission during the first year of operation is obtained. The electrolyzer produces 63 kg/hr of hydrogen, while the cell performance remains stable at 60 °C and the cell voltage reaches 2.019 V at 2.415 A/cm2 current density.

Development of a molten salt thermal conductivity model and database for advanced energy systems

A theoretical model for predicting the temperature-dependent thermal conductivity of pure molten salts, both simple and complex, is presented. The model is based on kinetic theory and incorporates Einstein’s concept of minimum thermal conductivity. The proposed formulation can consider the magnitude of thermal conductivity for separate salts, including complex and polymerizing salts. The model’s thermal conductivity predictions were compared to reliable experimental data in the literature and a previously recommended thermal conductivity model using the Bland–Altman method. The comparison showed accurate thermal conductivity predictions relative to the reliable experimental data, with an average deviation of 10% or less. The model’s predictions were also compared to the experimental data on an individual basis for halide, divalent halide, carbonate, nitrate, nitrite, sulfate, and hydroxide molten salts, demonstrating reliable predictions for the molten salts studied and improved accuracy over the previous model. Lastly, a database of simple and complex molten salts, with the necessary parameters for modeling their thermal conductivity, is recommended.

Developing decarbonisation pathways in changing TIMES for Irish homes

Decarbonising and improving the energy efficiency of dwellings is a priority for climate and energy policy. However, integrated energy systems modelling, commonly used to inform decarbonisation pathways, typically does not capture the heterogeneity of the dwelling stock, particularly internal dwelling temperatures, a key determinant of the cost of switching to low-carbon heating and upgrading building fabric. Addressing this gap, this paper presents a new model of the residential sector within an energy systems optimisation model (ESOM), which is developed using an Energy Performance Certificate (EPC) database and measured energy consumption data, allowing for the heterogeneous depiction of the housing stock.The analysis is carried out for Ireland, which has committed to ambitious legally binding climate targets. The Irish residential sector, which represented 22% of energy-related CO2 emissions in 2020, is characterised by poor thermal efficiency and high reliance on fossil fuels. The TIMES Ireland Model (TIM) is developed within a framework demonstrating cost-optimal pathways for energy supply, transformation, and demand sectors. The model is open-source, and the methodology outlined in this study is replicable for any country with an EPC database.The results presented are indicative of the type of insights that such modelling can provide and demonstrate that to meet climate targets, a rapid reduction in residential fossil fuel heating is necessary. The results show that deeper decarbonisation pathways require more thermal retrofits and electrical heat pumps, increasing the total cost of the energy system. The results explore the effect of internal temperatures, highlighting the importance of using empirical data for accounting for the rebound effect. Exemplifying the value of an integrated system modelling approach, deeper decarbonisation pathways place further costs on the electrical system.

Integration of high levels of electrolytic hydrogen production: Impact on power systems planning

The increasing interest in electrolytic hydrogen production using renewable electricity sources will require to adapt power systems to new electrical loads for hydrogen production and supply chains. Such high loads would impact the long-term planning and operation of power systems, as they need to balance the variability of renewable generation sources with electricity demand. This stresses the importance of characterizing the impact of incorporating hydrogen supply chains into power systems and planning accordingly. This study proposes a methodological framework to assess the integration and development of a national power system with electrolytic hydrogen production and supply chain. The framework is based on the well-known optimization tool for energy systems planning, Open Source Energy Modeling System (OSeMOSYS). For a detailed representation, a module was developed where demand side technologies – such as those associated to hydrogen supply chains – can provide operating reserves. As a case study, the integration of the Chilean power system with a hydrogen supply chain for exporting hydrogen between 2018 and 2050 was modeled. Among other findings, results indicate that an on-grid hydrogen supply chain would be more cost-effective than an off-grid one. However, the new electrical loads originated from such hydrogen supply chain would require additional generation capacity — primarily photovoltaic. Other generation capacities such as concentrated solar power, wind, and storage would experience significant variations in their investment requirements, compared to the off-grid hydrogen supply chain scenario. The study revealed that the coordinated operation of electrolyzers is crucial to the operational flexibility of the new electrical system.