Energy System Model Research Articles

Analysis of the role of hydrogen energy in achieving carbon neutrality by 2050: A case study of the Republic of Korea

The importance of achieving carbon neutrality by 2050 to combat climate change is widely recognized, leading to the proposal of various net-zero scenarios using energy system models. In these scenarios, hydrogen energy is often considered as a primary mitigation option alongside renewables. However, uncertainties surrounding hydrogen technologies prevent a comprehensive analysis of its role in achieving carbon neutrality. This study focuses on examining the impact of hydrogen energy demand, supply methods, and technology levels on carbon neutrality in the Republic of Korea using an energy system model. Findings suggest that hydrogen energy could constitute a significant portion of energy supply and demand by 2050. Sensitivity analyses reveal that reducing hydrogen imports could increase domestic power demand, while improving electrolysis efficiency could lead to more efficient carbon neutrality. Additionally, employing carbon capture technologies in hydrogen production rather than power generation is deemed effective. In conclusion, while hydrogen is a main reduction option for carbon neutrality, the effective utilization of hydrogen requires an increased reliance on imported hydrogen, further technology development including improved electrolysis efficiency and increased dissemination of reforming technologies with carbon capture, and the establishment of appropriate utilization strategies.

A post-disaster load supply restoration model for urban integrated energy systems based on multi-energy coordination

Urban integrated energy systems (UIES) have emerged as a promising solution to address the challenges of urban energy supply and consumption. However, UIES are vulnerable to extreme disasters, such as earthquakes, hurricanes, or floods, which can disrupt the energy infrastructure and lead to power outages and energy shortages. This study introduces a novel approach aimed at enhancing the resilience and load recovery capabilities of UIES in the face of extreme events. The proposed approach encompasses several key innovations, including the comprehensive coordination of local energy sources, prioritized restoration of critical loads, and a node-based modeling approach for gas and heat networks. Firstly, by fully integrating electricity, gas, and heat sources, the overall resilience of UIES is significantly improved, ensuring higher levels of load recovery even in the event of energy supply shortages. Secondly, the critical load recovery is prioritized by load classification, and the weights set can fully consider the connection status and load level of nodes to ensure priority provisioning of important node loads. In addition, the node-based modeling approach allows for accurate consideration of the flow of gas and heat in the pipe during modeling of the pipe energy storage. Finally, the case study section conducts simulation experiments with the UIES E33-G20-H6 test system to verify the effectiveness of the proposed approach and to demonstrate its potential in enhancing the post-disaster load recovery capability of UIES.

Capturing features of hourly-resolution energy models in an integrated assessment model: An application to the EU27 region

Hourly resolution is essential to realistically address the matching of supply and demand for fluctuating energy sources like solar and wind. This work introduces a novel method to model energy variability in an Integrated Assessment Model building upon a previous work, where regression analysis was utilized to extract hourly-level information from an energy system model. The enhancements include: (1) improved experimental design and more efficient computing, and (2) modelling the management of variability in an integrated assessment model by (i) incorporating a portfolio of flexibility options, and (ii) offering the ability to regulate system curtailment by limiting the expansion of renewables. The scenarios focus on the electricity sector, mirroring current EU27's policies that aim for higher renewable energy and electrification contributions by 2050. Without any variability control measures, significant curtailment (up to 60 %) is observed, the introduction of flexibility options reducing it to half (30 %). Controlling the capacity expansion of renewables is introduced to avoid this unrealistically high curtailment, allowing the model to achieve a penetration of renewables in electricity of 80 % and a 53 % reduction in greenhouse gas emissions compared to 2015 levels in the electricity system. In conclusion, the methodology employed yields broadly consistent outcomes.

Advancing cost-optimal residential decarbonisation pathways: An examination of heat pumps and thermal efficiency

In Ireland, residential energy policy has been influenced by thermal inefficiency, high electricity prices and energy poverty. These factors have driven the fabric-first approach, where buildings must undergo extensive thermal retrofitting to qualify for heat pump subsidies. The cost-effectiveness of this approach has not been properly scrutinised to date. This paper addresses this knowledge gap by exploring the cost-effectiveness of the fabric-first approach and other decarbonisation strategies for the residential sector and broader energy system. The study develops scenarios by modifying the Heat Loss Indicator (HLI) threshold, which evaluates the fabric and ventilation heat loss per unit of floor area and is used to determine heat pump subsidy eligibility. The paper also considers scenarios that permit installing sub-optimal performing heat pumps that do not achieve peak performance levels in dwellings with higher HLIs. The analysis uses the TIMES-Ireland Model (TIM), a model of the whole energy system that reflects the interdependence of mitigation pathways across different energy sectors. Our study shows that Ireland's fabric-first approach requires 22 times more thermal retrofits to meet climate targets than alternative pathways. The alternative pathways based on the latest heat pump performance data are more cost-effective, showing that higher heat pump HLI thresholds can reduce the average sectoral marginal CO2 emission price by 60% compared to the current fabric-first approach. The cost savings indicate that shifting to an HLI threshold of 2.3 W/K/m2 is close to optimal, while cost savings are minimal when moving from an HLI of 2.3 to 3 W/K/m2. Furthermore, electricity prices and household awareness are essential to the cost-optimal transition to residential heat pumps.

Harder, better, faster, stronger: understanding and improving the tractability of large energy system models

BackgroundEnergy system models based on linear programming have been growing in size with the increasing need to model renewables with high spatial and temporal detail. Larger models lead to high computational requirements. Furthermore, seemingly small changes in a model can lead to drastic differences in runtime. Here, we investigate measures to address this issue.ResultsWe review the mathematical structure of a typical energy system model, and discuss issues of sparsity, degeneracy and large numerical range. We introduce and test a method to automatically scale models to improve numerical range. We test this method as well as tweaks to model formulation and solver preferences, finding that adjustments can have a substantial impact on runtime. In particular, the barrier method without crossover can be very fast, but affects the structure of the resulting optimal solution.ConclusionsWe conclude with a range of recommendations for energy system modellers: first, on large and difficult models, manually select the barrier method or barrier+crossover method. Second, use appropriate units that minimize the model’s numerical range or apply an automatic scaling procedure like the one we introduce here to derive them automatically. Third, be wary of model formulations with cost-free technologies and dummy costs, as those can dramatically worsen the numerical properties of the model. Finally, as a last resort, know the basic solver tolerance settings for your chosen solver and adjust them if necessary.

The pitfall in designing future electrical power systems without considering energy return on investment in planning

Measuring the limitations of transitioning to 100% renewable energy systems partly equates with the capability of quantifying associated net-energy production. To foresee future possibilities, an advanced systemwide energy-return-on-investment (EROI) model was constructed. Driven by the thorough consideration of the existing weaknesses of EROI, the model integrates the concept of energy statistics, life cycle assessment techniques and energy system modelling in order to overcome the underlying primary energy quality issues, boundary condition problems and energy system design related uncertainties that compromises comparability of EROI during the energy transition. This model was applied to the Israeli power system that presents a unique opportunity to examine the vulnerability of depending on limited resources and the connection of EROI to system design. This study demonstrates the dependency of EROI on the energy transition path, system design requirements expressed via interactive linkages of curtailment, variable renewable energy penetration and storage system design, and resource diversity. Achieving a very high variable renewable energy penetration by 2050 with solar photovoltaics carries a risk of falling below an EROI value of 10, such vulnerability can be largely minimised by well-conducted manoeuvring of the system design and resource diversification. Despite the large uncertainty of this study, the need for a multicriteria designing technique is out of the question.

Linear, Nonlinear, and Distributed-Parameter Observers Used for (Renewable) Energy Processes and Systems—An Overview

Full- and reduced-order observers have been used in many engineering applications, particularly for energy systems. Applications of observers to energy systems are twofold: (1) the use of observed variables of dynamic systems for the purpose of feedback control and (2) the use of observers in their own right to observe (estimate) state variables of particular energy processes and systems. In addition to the classical Luenberger-type observers, we will review some papers on functional, fractional, and disturbance observers, as well as sliding-mode observers used for energy systems. Observers have been applied to energy systems in both continuous and discrete time domains and in both deterministic and stochastic problem formulations to observe (estimate) state variables over either finite or infinite time (steady-state) intervals. This overview paper will provide a detailed overview of observers used for linear and linearized mathematical models of energy systems and review the most important and most recent papers on the use of observers for nonlinear lumped (concentrated)-parameter systems. The emphasis will be on applications of observers to renewable energy systems, such as fuel cells, batteries, solar cells, and wind turbines. In addition, we will present recent research results on the use of observers for distributed-parameter systems and comment on their actual and potential applications in energy processes and systems. Due to the large number of papers that have been published on this topic, we will concentrate our attention mostly on papers published in high-quality journals in recent years, mostly in the past decade.

From exergoeconomics to Thermo-X Optimization in the transition to sustainable energy systems

Exergoeconomics has played an important role in the study of new energy systems in the last decades. The use of exergy as a “carrier of value” has made it possible to define an unambiguous criterion for allocating costs among energy systems products. The paper shows how exergoecomic procedures of analytical optimization and design improvement on heuristic basis have been progressively replaced by more efficient procedures aimed at minimizing an objective cost function, leaving exergoecomic cost evaluation as the final step. It also highlights how growing concerns about climate change and the continued growth of inequalities in energy availability have broadened the set of objectives in the search for the optimal integration of the design and operation of energy conversion units and network with intelligent methodologies to reduce energy demands. The objective of the article is twofold: i) present the evolution of the main Exergoeconomic methods and show how they have paved the way for Thermo-X Optimization methods; and ii) outline the path for developing a general model of society's entire energy system that includes a broader set of objectives and constraints in addition to economic ones to help build the energy system of the future with a more sustainable perspective.

Optimization method for capacity configuration and power allocation of electrolyzer array in off-grid integrated energy system

Hydrogen production using renewable energy is in line with China's the goal of carbon peak and carbon neutrality. The construction of off-grid hydrogen energy industrial park can effectively achieve local utilization of renewable energy and develop the green hydrogen industry. However, off-grid hydrogen energy industrial park has not the compensation and sustentation from large power grid, the stable operation and economic production of electrolyzer are affected by significant factors, such as power fluctuation and frequent start stop. Therefore, this paper proposed the optimization method for capacity configuration and power allocation of electrolyzer array in off-grid integrated energy system. Firstly, based on units of energy supply, energy conversion, and energy storage, a structural model of off-grid integrated energy system was established. Then, by analyzing the operational characteristics of single electrolyzer and electrolyzer array, flexible mode of multiple electrolyzers operating in combination was proposed. Furthermore, considering the hydrogen production cost, the mean of hydrogen production volatility and penalty cost, the capacity configuration and power allocation methods for electrolyzer array were proposed, and the optimization problem is solved with multi-objective particle swarm optimization algorithm. Finally, the hydrogen energy industrial park in Zhangye is taken as example to verify the effectiveness of above research content. Compared to a single type of alkaline electrolyzer, the mean of hydrogen production volatility of multiple electrolyzers operating in combination has decreased by 43.2 %, the hydrogen production quantity has increased by 9.74 %. Compared to a single type of proton exchange membrane electrolyzer, the hydrogen production cost has been reduced by 14.16 %. Compared with the balanced running mode, the flexible operation mode can improve the cost-effective and quantity of hydrogen production.

Moving control surfaces in a geometry-resolved CFD model of an airborne wind energy system

Properly understanding the unsteady interaction of the wind with the aircraft is critical to develop reliable airborne wind energy (AWE) systems. High-fidelity simulation tools are needed to accurately predict these interactions, providing insights into the design and operation of efficient and safe AWE systems. In this work, we present a computational fluid dynamics (CFD) framework of an airborne wind system which resolves all lifting surfaces and includes moving control surfaces. This work considers a reference multi-megawatt ground-gen pumping system. To simulate complex fluid flow problems, with large rigid-body motion and deflecting control surfaces using CFD, we opt for the Chimera/overset technique. The goal of this contribution is to demonstrate the effect of the control surfaces in the CFD framework. This work is a major milestone in the ongoing development of high-fidelity aero-servo-elastic simulation models for airborne wind energy systems.

Increasing electricity access for health facilities in Ghana through solar powered mini-grids—a GIS-based energy system modelling approach

The research aims to identify which healthcare facilities (HCFs) in Ghana are suitable for electrification using photovoltaic mini-grids to increase their energy self-sufficiency and reliability of services provided. Additionally, the study categorises the HCFs in two groups: those with and without or with poor access to electricity supply, identify settlements within their catchment area, and determine the electricity demand for identified HCF sites and their surrounding communities. The research assesses the most suitable mini-grid system setup to electrify identified HCF sites and the impact of including the demand of surrounding communities into the energy system modelling. Finally, the study aims to determine the accumulated solar mini-grid potential to electrify all identified HCF sites. The study findings highlight the importance of integrated planning between the health and energy sectors to ensure high-quality health services. Solar mini-grids are identified as a promising solution for electrifying HCFs and improving energy self-sufficiency. However, it is recommended to avoid transferring findings between different types of health facilities due to their unique characteristics. The study also emphasizes the importance of balancing the energy flow and stabilizing the energy system through the combination of HCFs and surrounding communities’ demand. It is crucial to assess the electricity demand carefully based on context-specific characteristics, such as the type of HCF and the number of households considered. Overall, the study provides valuable insights into the potential of solar mini-grids to increase energy self-sufficiency in HCFs and the importance of careful planning and context-specific assessments.

System flexibility in the context of transition towards a net-zero sector-coupled renewable energy system—case study of Germany

To integrate variable renewable energy sources into the energy system and achieve net-zero emissions, the flexible operation of the power system is essential. Options that provide flexibility include electrolysis, demand side management, import and export of electricity, and flexible power plants. However, the interplay of these flexibility options in a renewable energy system with highly interacting energy and end-use sectors (known as sector coupling) is not yet fully understood. The aim of this paper is to improve the understanding of energy flexibility from a system perspective by explaining which flexibility options can provide how much flexibility and when are they operated. The analysis of the hourly results of the sector-coupled, long-term energy system model REMod shows that in times with high renewable electricity production, sector coupling technologies, specifically electrolysis and power-to-heat, dominate the annual flexibility shares. On the other hand, in times with low renewable production and high non-flexible demand, combined and open cycle gas turbines and electricity imports dominate in winter, while discharging electricity storage technologies dominate in summer. The operation of short-term electricity storage aligns in particular with photovoltaic production, while the operation of electrolysis is especially aligned to wind production. Non-flexible demand variations are driving the operation of combined and open cycle gas turbines and electricity imports. The results emphasize the pivotal role of flexibility, highlighting the need for efficient surplus electricity utilization and sector coupling. The results further suggest that it is crucial to establish market conditions that facilitate the flexible operation of various technologies in order to achieve economic efficiency.

Sensitivity of a Lumped-Capacitance Building Thermal Modelling Approach for Energy-Market-Scale Flexibility Studies

Despite all the literature on building energy management, building-stock-scale models depicting its impact for energy-market-scale optimisation models are lacking. To address this shortcoming, an open-source tool called ArchetypeBuildingModel.jl has been developed for aggregating building-stock-level data into simplified lumped-capacitance thermal models compatible with existing open-source energy-system modelling frameworks. This paper aims to demonstrate the feasibility of these simplified thermal models by comparing their performance against dedicated building simulation software, as well as examining their sensitivity to key modelling and parameter assumptions. Modelling and parameter assumptions comparable to the existing literature achieved an acceptable performance according to ASHRAE Guideline 14 across all tested buildings and nodal configurations. The most robust performance was achieved with a period of variations above 13 days and interior node depth between 0.1 and 0.2 for structural thermal mass calibrations, and with external shading coefficients between 0.6 and 1.0 and solar heat gain convective fractions between 0.4 and 0.6 for solar heat gain calibrations. Furthermore, three-plus-node lumped-capacitance thermal models are recommended when modelling buildings with structures varying in terms of thermal mass. Nevertheless, the ArchetypeBuildingModel.jl performance was found to be robust against uncertain key parameter assumptions, making it plausible for energy-market-scale applications.

A Study on Fishing Vessel Energy System Optimization Using Bond Graphs

Recently, environmental regulations have been strengthened due to climate change. This change comes in a way that limits emissions from ships in the shipbuilding industry. According to these changes, the trend of ship construction is changing installing pollutant emission reduction facilities such as scrubbers or applying alternative fuels such as low sulfur oil and LNG to satisfy rule requirements. However, these changes are focused on large ships. Small ships are limited in size. So, it is hard to install large facilities such as scrubbers and LNG propulsion systems, such as fishing boats that require operating space. In addition, in order to apply the pure electric propulsion method, there is a risk of marine distress during battery discharge. Therefore, the application of the electric–diesel hybrid propulsion method for small ships is being studied as a compromised solution. Since hybrid propulsion uses various energy sources, a method that can estimate effective efficiency is required for efficient operation. Therefore, in this study, a Bond graph is used to model the various energy sources of hybrid propulsion ships in an integrated manner. Furthermore, based on energy system modeling using the Bond graph, the study aims to propose a method for finding the optimal operational scenarios and reduction ratios for the entire voyage, considering the navigation feature of each different maritime region. In particular, the reduction gear is an important component at the junction of the power transmission of the hybrid propulsion ship. It is expected to be useful in the initial design stage as it can change the efficient operation performance with minimum design change.

Techno-economic modeling and optimal sizing of autonomous hybrid microgrid renewable energy system for rural electrification sustainability using HOMER and grasshopper optimization algorithm

This research paper focuses on techno-economic modeling and optimal sizing of autonomous hybrid microgrid systems. The optimal configuration of the suggested stand-alone system was performed by developing a size optimization model based on the metaheuristic novel Grasshopper Optimization algorithm (GOA) method to minimize the Total Net Present Cost (TNPC), unmet load, and Cost of Energy (COE) in the Nsukka Community which comprises 88 villages. The GOA and HOMER Pro Software are employed to compare results across four possible configurations of hybrid renewable power systems (HRES). The comparative analysis between GOA and HOMER shows that configuration-4 (biogas/Diesel), emerges as the optimal solution, with a 0 % unmet load at the COE of $0.01783 per kWh. The findings indicated that the GOA-based HRES, with a higher saturation of Biogas and photovoltaics (PV), proves to be more affordable in comparison to the HOMER-based solutions. The reduction in the COE and NPC of renewable energy for peak demands highlights the growing importance of biogas generators as an affordable local power supply to meet energy demands. This underscores the potential of the GOA in optimizing hybrid renewable energy systems for remote communities, producing an economically viable and sustainable energy solution.

Integration of a computable general equilibrium model with an energy system model: Application of the AIM global model

An integrated assessment model AIM (Asia-Pacific Integrated Model) has been used climate change mitigation studies and the core of AIM is a computable general equilibrium model, AIM/Hub. However, the energy representation in the AIM/Hub is abstract and to overcome that shortcoming, this study integrated AIM/Hub with the energy system model AIM/Technology. First, we assessed how the new integrated model differ from the original standalone AIM/Hub. Second, we conducted the exchange of model outputs iteratively and evaluated how the model results converged. Comparing previous and corresponding iteration, the data points with discrepancies greater than 5% at the third iteration were only 5 variables which were minor variables from the full energy system point of view. The macroeconomic implications of climate change mitigation differ between the standalone AIM/Hub and the new integrated model, and however, there was no systematic discrepancies. Overall, the new model is valid for exploring energy-economic scenarios.

Sustainable development goals in energy system models: A systematic interlinkages mapping analysis

With less than 6 years left to achieve the global sustainable development goals (SDGs) by 2030, there is a growing urgency to increase the effectiveness of policy actions by targeting multiple SDGs. Mathematical modeling tools facilitate sustainability assessment in support of integrated policymaking. This study examines the interlinkages between the SDGs with commonly used and broadly applicable energy system models (ESMs) using the 248 indicators defined by the United Nations. The SDGs are classified under the environment (SDGs 6, 7, 12, 13, 14, 15), economy (SDGs 8, 9, 10, 11, 17), and society (SDGs 1, 2, 3, 4, 5, 16) domains governing the sustainability framework. The results ascertain that current ESMs are conceived to prioritize energy-related environmental indicators related to SDG7 (Affordable and Clean Energy), SDG12 (Responsible Consumption and Production) and SDG13 (Climate Action) with limited focus on non-energy indicators of the environmental domain, along with little to no coverage of SDGs-indicators allocated within the economic and social domains, respectively. The findings call for expanding the frontiers of ESMs to incorporate emerging systemic interdependencies that extend beyond the traditional “energy-environmental” nexus considering the multi-dimensional facets of sustainable development. For this purpose, a conceptual integrated framework was developed underscoring procedural protocols and technical directives to advance the ESMs-SDGs modeling paradigm through the application of methodological improvement opportunities. Theoretical and practical implications driven by policy and managerial perspectives were also discussed. In closure, this study can inform stakeholders about the gaps (sustainability issues and corresponding targets-indicators) that are imperative to address in modeling the SDGs and how to leverage existing ESMs into integrating a broader range of SDGs beyond traditional considerations. The improved outcomes are expected to facilitate integrated sustainable policy planning and formulation in pursuit of operationalizing the SDGs for the timely attainment of the 2030 agenda.

EnergyModelsX: Flexible Energy Systems Modelling with Multiple Dispatch

EnergyModelsX: Flexible Energy Systems Modelling with Multiple Dispatch

Integrated life cycle assessment in off-grid energy system design—Uncovering low hanging fruit for climate mitigation

We perform an ex-ante life cycle assessment, integrating cradle-to-gate greenhouse gas emissions into an off-grid energy system model. By applying a multi-objective optimization, minimizing both costs and carbon dioxide equivalent (CO2e) emissions, we find the Pareto boundary between these two goals. As a case study, we chose the power supply to an astronomical observatory in Chile, using mostly solar power and energy storage in batteries and hydrogen. We compare the ex-ante study to a prior ex-post life cycle assessment, and furthermore dive into sensitivities of our model regarding component lifetimes and costs. We find (i) low-hanging fruit in lowering emissions with small cost increases, (ii) ex-ante life cycle assessments’ possibility to find less CO2e intensive power systems compared to ex-post conducted studies, (iii) a pronounced sensitivity of the optimization model on assumed lifetimes of energy storage components. This study shows the importance of including life cycle CO2e emissions into the optimization objective of energy system models. This method uncovers the environmental and economic trade-offs associated with high shares of renewable energies in off-grid energy systems.

Optimal scheduling of multi-regional energy system considering demand response union and shared energy storage

In the current context of the scarcity of fossil energy and the large-scale development and utilization of new energy sources, the power system is developing in the direction of multi-source synergy and interconnection. Demand response technology and energy storage technology have become important adjustment means of integrated energy system because of their efficient coordination ability and flexible adjustment ability. However, in the system where multiple energy systems operate cooperatively, there are still some limitations in time and capacity scales. Therefore, in order to enhance the demand-side response capability in multi-energy systems and give full play to the function of energy storage power stations, this paper proposes an optimal scheduling model for multi-area energy systems that considers joint demand response and shared energy storage. First, the system energy coupling matrix is constructed based on energy hubs, and the modeling framework for joint demand-side response and shared energy storage is established. Second, the multi-objective optimization problem is solved using NSGA-II algorithm solution with the optimization objectives of minimizing the total operating cost of the system and maximizing the net environmental impact. Finally, the simulation analysis is carried out. The simulation results show that the addition of joint demand response and shared energy storage can guide the scheduling optimization of multiple energy sources in each region in time and space, and realize the energy complementarity and mutual assistance of multi-regional energy systems. Compared with the traditional multi-regional energy system optimization scheduling scheme, the operation cost of the scheme is reduced by 4.2 %, and the environmental protection is improved by 41.9 %, which proves the feasibility of the optimal scheduling model proposed in this paper.