Techno-economic Model Research Articles

Optimal expansion of a multi-domain virtual power plant for green hydrogen production to decarbonise seaborne passenger transportation

Many industrialised nations recently concentrated their focus on hydrogen as a viable option for the decarbonisation of fossil-intensive sectors, including maritime transportation. A sustainable alternative to the conventional production of hydrogen based on fossil hydrocarbons is water electrolysis powered by renewable energy sources. This paper presents a detailed techno-economic optimisation model for sizing an electrolyser and a hydrogen storage embedded in a multi-domain virtual power plant to produce green hydrogen for seaborne passenger transportation. We base our numerical analysis on three years of historical data from a renewable-dominated 60/10kV substation on the Danish island of Bornholm, and on data for ferries to the mainland of Sweden. Our analysis shows that an electrolyser system serves as a valuable flexibility asset on the electrical demand side, while supporting the thermal management of the district heating system and contributing to meeting the ferries hydrogen demand. With a sized electrolyser of 9.63MW and a hydrogen storage of 1.45t, the hydrogen assets are able to take up a large share of the local excess electricity generation. The waste heat of the electrolyser delivers a significant share of 21.4% of the annual district heating demand. Moreover, the substation can supply 26% of the hydrogen demand of the ferries from local resources. We further examine the sensitivity of the asset sizing towards investment costs, electrolyser efficiency and hydrogen market prices.

Teaching the Complex Dynamics of Clean Energy Subsidies With the Help of a Model-as-Game

The economic and policy justifications for clean energy subsidies are complex and difficult to internalize. A subsidy induces additional consumers to buy, reducing carbon emissions through reduced fossil fuel consumption. Over the long term, subsidies encourage industry investment and cost reductions. Ideally, subsidies can be removed when the technology is broadly competitive. Deciding on an appropriate level of government subsidy is complex because a decision-maker should balance government expenditures and benefits over both time and space. A subsidy can be excessive when government costs are too high and/or many consumers would have purchased the unsubsidized product, but can also be too low if insufficient to encourage adoption. In order to educate non-experts on these ideas, we created a case study about the topic, consisting of teaching materials and a cooperative multiplayer game that is playable in small groups in 15–30 min. We have used the case study in both university courses and public-facing events and believe that it would be of interest as teaching material for cost-benefit analysis, government subsidy design, clean energy policy, and science and technology policy education or training. After 15 min with the game, players have a basic understanding of all the important factors and dynamics of subsidy design. For the reader, this article offers a specific example of how to translate a sophisticated technoeconomic decision model into an educational game and includes rules and supplementary materials needed to cover the topic of subsidy design and to try the game in courses and general public settings.

Techno-economic model for long-term revenue prediction in distribution grids incorporating distributed energy resources

Distributed energy resources (DER) is a prevalent technology in distribution grids. However, it poses challenges for distribution network operators to make optimal decisions, estimate total investment returns, and forecast future grid operation performance to achieve investment development objectives. Conventional methods mostly rely on current data to conduct a static analysis of distribution network investment, and fail to account for the impact of dynamic variations in relevant factors on a long-term scale on distribution network operation and investment revenue. Therefore, this paper proposes a techno-economic approach to distribution networks considering distributed generation. First, the analysis method of the relationship between each investment subject and distribution network benefit is established by using the system dynamics model, and the indicator system for distribution network investment benefit analysis is constructed. Next, the distribution network operation technology model based on the dist flow approach is employed. This model takes into account various network constraints and facilitates the comprehensive analysis of distribution network operation under dynamic changes in multiple factors. Consequently, the technical index parameters are updated to reflect these changes. This updated information is then integrated into the system dynamics model to establish an interactive simulation of the techno-economic model. Through rigorous verification using practical examples, the proposed method is able to obtain the multiple benefits of different investment strategies and be able to select the better solution. This can provide reference value for future power grid planning.

An integrated techno-economic decision-support fiscal forecast model for sea cage mariculture enterprises for Asian seabass production in Indian territorial waters

Cage-based mariculture ventures in India are expanding, particularly emerging with the most sought-after candidate Asian seabass Lates calcarifer in territorial waters. However, comprehensive techno-economics have not been attempted, and thus hindering the sector's growth potential. To address this, a spatiotemporally validated decision-support model was developed to optimize investment decisions and forecast economic performance. Peer-reviewed contextual data was used to establish scientifically valid assumptions, and robust scenario simulations were conducted to benchmark production systems and species performance. Unit standards were defined and benchmarked for metric deployment for the first time. Capacity Utilization (CU) was found to be critical for success, achieving break-even at 31% CU with set model specifications derived from an inverse linkage with market price dynamics. The enterprise model demonstrated significant economic potential over a ten-year horizon, with low risk due to current policy initiatives by the Indian government. Furthermore, the model architecture and benchmarked specifications derived are adaptable to other candidates with its species-specific biological parameter application. The study can aid stakeholders in planning the enterprise budget. Most importantly, the study highlights the advantages of integrating technological, biological, and financial approaches to mitigate risks and promote the mariculture sector in India. The adaptability of the Asian seabass to farming systems, technical feasibility, and the availability of seeds and suitable sites along the Indian coast have been influential factors and these attributes in specific underpins the profitability. This research provides a way forward for the future of the sector in India, particularly with regard to farming of the Asian seabass, and emphasizes the importance of techno-economic models (TEM) in promoting strategic development of the mariculture sector through open sea cage farming.

Assessing the impact of climate change on the cost of production of green ammonia from offshore wind

Green ammonia has received significant interest as a zero-carbon energy vector. However, current techno-economic models used to estimate the cost of producing green ammonia only use historical weather datasets as their inputs. Climate change is beginning to have an observable impact on global weather systems, so it is therefore important to examine how resilient locations for green ammonia production will be to the effects of climate change on renewable energy resources. This work examines how the cost of producing green ammonia from offshore wind farms at four locations in the UK could change due to climate change. It uses the 1981–2000, 2021–2040 and 2061–2080 2.2km projections under the RCP8.5 scenario from the Met Office's UK Climate Projections 2018 dataset, which were bias corrected with reference to the ERA5 reanalysis dataset. Using an islanded green ammonia production model, the achievable levelised cost of ammonia (LCOA) was evaluated at four sites taken from confirmed projects in the UK's Offshore Wind Licensing Round 4, with the achievable LCOAs found to range between 935 and 1696 USD/t. Results from the three time periods were compared to assess the impact of climate change and were benchmarked against LCOAs from conventional production pathways. At all sites, increases of between 6% and 8% of the average LCOAs were observed for the 2021–2040 and 2061–2080 scenarios respectively, with the changes found to be statistically significant through application of a two tailed T-test with a confidence level of 5%.

Profitability of Alternative Battery Operation Strategies in Photovoltaic Self-Consumption Systems under Current Regulatory Framework and Electricity Prices in Spain

The decreasing costs of solar photovoltaic (PV) technology have led to an exponential growth in the use of PV self-consumption systems. This development has encouraged the consideration of battery energy storage systems (BESS) as a potential means of achieving even more independence from the fluctuating grid electricity prices. As PV technology and energy storage costs continue to decline, both technologies will likely play an increasingly important role in the renewable energy sector. The profitability of batteries in PV self-consumption systems is largely influenced by the price of consumed electricity and the price at which surplus energy is remunerated. However, strategies in PV-BESS self-consumption systems typically do not take electricity prices into consideration as a variable for decision making. This study simulates and analyzes battery operation strategies that take into account electricity prices. The simulations are performed using real industrial consumption data and real electricity prices and tariffs, they cover the entire lifespan of the batteries, and include aging and degradation due to use and cycling. A techno-economic model is used to evaluate the advantages of incorporating these battery operational strategies into an actual PV-BESS system. The results demonstrate that the proposed strategies enhance the savings that batteries can provide.

A Comparison of Power Take-Off Architectures for Wave-Powered Reverse Osmosis Desalination of Seawater with Co-Production of Electricity

Several power take-off (PTO) architectures for wave-powered reverse osmosis (RO) desalination of seawater are introduced and compared based on the annual average freshwater production and the size of the components, which strongly relate to the costs of the system. The set of architectures compared includes a novel series-type PTO architecture not previously considered. These seawater hydraulic PTO architectures are composed of a WEC-driven pump, an RO module, an intake charge pump driven by an electric motor, and a hydraulic motor driving an electric generator for electric power production. This study is performed using an efficient two-way coupled steady-state model for the average performance of the system in a given sea state, including freshwater permeate production, electric power production, and electric power consumption. A multi-objective design problem is formulated for the purposes of this comparative study, with the objectives of maximizing annual freshwater production, minimizing the displacement of the WEC-driven pump, and minimizing the installed RO membrane area. This establishes a framework for comparison in the absence of a mature techno-economic model. The requirement that the system produces enough electric power to meet its consumption is applied as a constraint on the operation of the system. The oscillating wave surge converter Oyster 1 is assumed as the WEC. Weights on performance of the system in a given sea state are based on historical data from Humboldt Bay, CA. This study finds that (1) architectures in a series configuration allow for a reduction in the WEC-driven pump size of 59–92% compared to prior work, (2) varying the displacement of the WEC-driven pump between sea conditions does not provide any significant advantage in performance, and (3) varying the active RO membrane area between sea condition offers improvements between 7% and 41% in each design objective.

Hybrid emperor penguin glowworm swarm optimiser for techno-economical optimisation with demand side management in microgrid using multi-objective function

Recently, microgrids have been engaged with Demand Side Management (DSM), which helps to save more energy. Hence, the existing model suffers based on the slow response, and also it cannot restore the system voltage and frequency. Consequently, the voltage and frequency fluctuations in the microgrid become a challenging task. Thus, this research work aims to develop a new model for the microgrid. Here, a new Hybrid Emperor Penguin Glowworm Swarm Optimisation algorithm is developed with the integration of Emperor Penguin Optimiser (EPO) and Glowworm Swarm Optimisation (GSO). Moreover, the techno-economical model minimises the energy supply cost, Diesel Generator (DG), power loss and voltage variations. It implements the Wind Turbines, DG, optimal capacity of PV and Energy Storage Systems, through techno-economical optimisation for offering renewable energy sources. Moreover, the designed model helps to solve the multi-objective function regarding metrics like initial cost, operation cost, DSM, voltage fluctuations, fuel cost, Electricity Supply Costs and network power losses. The performance of the developed model shows 17.6%, 36.9%, 2.4% and 0.4% better performance than HHO, EPO, GSO and IMP-SPA in terms of voltage fluctuations. Throughout the validation, the offered model shows superior performance when compared with state-of-art models.

Highly-efficient natural gas desulfurization and simultaneous H2O2 synthesis based on the electrochemical coupling reaction strategy

Hydrogen sulfide (H2S) generated by natural gas exploitation is a dangerous and harmful gas that needs to be purified. Electrochemical Natural Gas Desulfurization offers a promising way for H2S purification and resource utilization in ambient conditions. However, poor energy efficiency and low resource value limit the prospective application in the industry. Herein, we propose a gas-liquid flow electrocatalysis system that couples H2S oxidation and O2 reduction processes to effectively recover sulfur and H2O2 with low energy consumption. Gas diffusion and mass transfer are accelerated by gas-liquid flow cells, which also significantly decrease the resistance. Besides, I-/I3- redox pairs promote selective H2S oxidation while inhibiting water decomposition, resulting in a 56% reduction in oxidation potential. Moreover, the surface proton concentration is elevated by employing a modified carbon gas diffusion electrode (GDE), which assists to maintains a high H2O2 faradic efficiency. The system is able to operate at a high current density of 102 mA/cm2 at an Ecell voltage of 3.5 V, yielding S and H2O2 at rates of 60 mg cm−2 h−1 and 50 mg cm−2 h−1 respectively. A techno-economic model forecasts the effects of system efficiency and energy prices on operational costs and illustrates potential routes to a plant-gate levelized application in the petrochemical industry.

The development of a techno-economic model for the assessment of asphaltene-based carbon fiber production

Carbon fiber is a material consisting of strong filaments made essentially of atoms of carbons. Asphaltene is as a potential precursor in the manufacturing of carbon fiber. The technology for production of carbon fiber from asphaltene is in the early stage of development, therefore the economic feasibility of the process at large-scale production has not yet been stablished. This information is critical for those making investment decisions and for policy formulation, and is required for the further development of this pathway. A techno-economic assessment of the production of asphaltene-based carbon fiber derived from bitumen to estimate the production cost was performed through the development of process models. The material and energy requirements, sizing of the main equipment, and capital and operating costs were obtained from a data-intensive process model. The results show that for a plant capacity of 3,000 tonnes per year, the production cost is $10.16 per kg of carbon fiber. This cost estimate is most sensitive to the stabilization time, the process yield, and the flow of nitrogen required to set the atmosphere of the carbonization operation. The effect of scale and tow size were also studied; production cost decreased with those parameters. For a 12 k tow and capacities greater than a 890 t/y plant, the production cost is lower than the current market price of polyacrylonitrile (PAN)-based carbon fiber, while for capacities above 3,060 t/y, the production cost would be below $10/kg CF. The uncertainty analysis shows that production cost would likely range between 11.50 and 14.80 $/kg CF, indicating that it is potentially cheaper to produce carbon fiber from asphaltene than from polyacrylonitrile. These results are useful for making investment decisions, policy formulation, and identifying process variables important for low-cost carbon fiber.

Impact of Glasgow Climate Pact and Updated Nationally Determined Contribution on Mercury Mitigation Abiding by the Minamata Convention in India.

India is one of the largest emitters of atmospheric anthropogenic mercury (Hg) and the third-largest emitter of greenhouse gases in the world. In the past decade, India has been committed to the Minamata Convention (2017) in addition to the Paris Climate Change Agreement (2015) and the Glasgow Pact (2021). More than 70% to 80% of India's mercury and carbon dioxide emissions occur because of anthropogenic activities from coal usage. This study explores nine policy scenarios, the nationally determined contribution (NDC) scenario, and two deep decarbonization pathways (DDP) with and without mercury control technologies in the energy and carbon-intensive sectors using a bottom-up, techno-economic model, AIM/Enduse India. It is estimated that NDC scenarios reduce mercury emissions by 4%-10% by 2070; while coal intensive (DDP-CCS) pathways and focus on renewables (DDP-R) reduce emissions by 10%-54% and 15%-59%, respectively. Increase in the renewables share (power sector) can result in a significant reduction in the costs of additional pollution-abating technologies in the DDP-R scenario when compared with the coal intensive DDP-CCS scenario. However, the industry sector, especially iron and steel and metal production, will require stringent policies to encourage installation of pollution-abating technologies to mitigate mercury emissions under all the scenarios.

Development of data-intensive techno-economic models for the assessment of a biomass, waste heat, and MSW integrated waste-to-electricity facility

This study develops a framework for an assessment of the integrated processing of various types of waste in a single waste-to-energy (W2E) facility. The FUNdamental ENgineering PrinciplEs-based model for Estimation of Cost of Energy from Biomass and Municipal Solid Waste (MSW) (FUNNEL-Cost-Bio-waste) was developed and used to assess the conversion of MSW, agricultural residue, forest residue, and waste heat to electricity via gasification. A geographic information systems (GIS)-based model was developed to estimate the availability of wastes at collection points and the transportation distances to the facility. A case study for Alberta (Canada) was conducted to assess the techno-economic feasibility of a 199 MW gasification-based facility. Depending on whether one or two waste heat sources are used for drying MSW, internal rates of return and the costs of generating electricity were estimated to be 11.18 % and 8.09 % and US $21.90/MWh and US $33.23/MWh, respectively. This information can be used for investment decision-making.

The development of data-intensive techno-economic models for the comparison of renewable natural gas production from six different biomass feedstocks for the decarbonization of energy demand sectors

Renewable natural gas (RNG) from biomass can be used as an alternative to natural gas. However, there is limited understanding of the economic viability of RNG production from a wide range of feedstocks. In this study, a comprehensive comparative techno-economic assessment of RNG production via gasification from six biomass feedstocks with a wide range of moisture contents and characteristics was conducted. The feedstocks studied are corn stover (CS), wheat straw (WS), whole forest (WF), forest residues (FR), cow manure (CM), and the organic fraction of municipal solid waste (OFMSW). The RNG production plants were simulated and the simulation results were used to develop techno-economic models for each feedstock to estimate the production cost of RNG. The pathways were compared in terms of RNG yield, RNG production quantity, electricity generation, as well as RNG production costs and cost components. Sensitivity analyses were conducted on a wide range of factors and effect of including cardon credit on the production cost were studied. RNG production costs from the gasification of the OFMSW and CS were lower than those of other feedstocks at 6.28 $/GJ and 6.32 $/GJ, respectively. If the avoided cost (as a source of revenue) of landfilling of the OFMSW or carbon credit (minimum 90 $/t CO2) is considered, the RNG production cost can be competitive with natural gas price (1.4 $/GJ). The information developed in study is critical for decision makers in policy formulation and investment decisions.

Comparison of Techno-Economic Models for Upgrading PV System without Net-Metering Option and Long Term Impact on Energy Bills

This article presents a techno-economic analysis of upgrading a Photovoltaic (PV) power system at large. A comparative study has been carried out considering various technical and economic factors like per unit cost, annual load, energy demand growth, and PV panel efficiency, annual performance degradation of system, cost of electricity, payback period, initial capital expenditure, and rate of return in the form of saving in energy bills. The PV system is proposed to be upgraded from 1 MW to 2 MW at the National University of Sciences & Technology (NUST), Islamabad. The PV system is subject to be upgraded due to the growth rate of annual load and amount saved by PV contribution, which has been forecasted using data trends of the above-mentioned technical and economic factors. While considering these factors, four economic models have been evaluated and compared, which include Self-Built via Contractor with self-financing, Self-Built with bank financing, Power purchase agreement (PPA), also known as rental agreement and Built, Own, Operate & Transfer (BOOT) model. Merits and demerits of these models have been discussed, and the most feasible model has been proposed based on the mentioned key factors and long-term sustainable development goals (SDG) for affordable clean energy to contribute to climate action, i.e., adaptation of renewable energy resources (RER) and reduction of greenhouse gases (GHG).

Considering Socio-Technical Parameters in Energy System Models—The Current Status and Next Steps

The energy transition is a complex development towards a climate-neutral, economic, safe, and fair energy system. Therefore, numerical energy system models, among others, can make a significant contribution by simulating, optimizing and thus demonstrating possible transition pathways. Representative models and forecasting tools are needed to illustrate the next necessary steps and measures for the various target groups. In the literature, such energy system models have been studied and evaluated many times. This paper presents the approaches of previous reviews and analyses of how technical, economic, and social aspects of energy system models have been investigated so far. It is shown that especially recent studies already address this topic, but still receive insufficient recognition. Besides the general structural features, the technical modeling details were evaluated in the previous literature. Thereby, a part of the examined general reviews assesses the representation of consumer behavior in the models as a representative for social system aspects. Only a minor amount of the energy system models analyzed there per se represent consumer behavior. Furthermore, this article identifies possible linking strategies of social science parameters and energy system models from the literature based on their opportunities and challenges. This analysis forms a basis on which the already established majority of techno-economic energy system models can be extended in order to provide a more holistic view of the energy system. To do so, further research and development to improve future interdisciplinary processes are required.

The effects of local interventions on global technological change through spillovers: A modeling framework and application to the road-freight sector

To address global sustainability challenges, (public) policy interventions are needed to induce or accelerate technological change. While most policy interventions occur on the local level, their innovation effects can spill over to other jurisdictions, potentially having global impact. These spillovers can increase or reduce the incentive for interventions. Lacking to date are computational models that capture these spillover dynamics. Here, we devise a conceptual and methodological approach to quantify ex ante the effects of local demand-side interventions on global competition between incumbent and novel technologies. We introduce two factors that moderate global spillovers-relative size of selection environments and relative innovation potential of competing technologies. Our approach incorporates both factors in a techno-economic discrete choice model that evaluates technology competition over time through endogenized technological learning. We apply this modeling framework to the case of road freight. Different demand-pull interventions and shocks are modeled to assess spillover effects. In the case of road freight, electric vehicles experience growth in most application segments but can still be accelerated substantially through public policy intervention-spillovers occur if strong public interventions are introduced in large regions or in multiple combined regions under club policy interventions. These findings are discussed in the context of club policy interventions and a modeled geopolitical shock in China. A full sensitivity analysis of model input parameters and intervention or shock dynamics reveals high model robustness. Finally, we discuss the implications of the road-freight case study as it might inform the progress of other niche technologies in transitioning sectors.

Techno-economic modelling for energy cost minimisation of a university campus to support electric vehicle charging with photovoltaic capacity optimisation

Workplace charging of Electric Vehicles (EV) is a promising approach for transport decarbonization while addressing issues emerging from renewable energy growth. For workplaces, the decision to invest in EV charging infrastructure depends on the overall cost of providing this service. This study proposes a novel modelling approach to minimize the net annual energy cost of a university campus providing EV charging service using optimum capacity solar photovoltaic (PV) systems. The research includes an innovative approach to determine the campus EV charging demand and a novel net annual energy cost minimisation method combining PV size optimisation and EV charging control. A comprehensive analysis is presented to illustrate the influence of EV penetration, charging strategy, charging fees, charger cost and PV generation cost on the campus net annual energy cost. The influence of these parameters are also analysed on the optimal PV capacity, power and energy demand, and PV self-utilisation. Results show that, by using the proposed method, for 25 % EV penetration, the campus's peak demand is reduced by around 12 % and net annual energy cost is reduced by up to 9.2 % while providing free EV charging. The net annual energy cost reduction increases to over 20 % for 100 % EV penetration.

Large size heat pumps advanced cost functions introducing the impact of design COP on capital costs

Power-to-heat technologies offer low-carbon heat and integrate electricity and heating sectors. Moreover, high-temperature heat pumps can supply process heat for industries, like food, and feed early district heating networks. However, their viability is often jeopardized by high capital costs. Fluid selection affects variable and capital (TCI) costs, impacting the Coefficient of Performance (COP) and equipment sizing. Therefore, identifying the best fluid and estimating capital costs with simple and reliable cost functions are crucial for assessing heat pump market opportunities. This paper presents a multi-objective optimization, based on a detailed technoeconomic model, to find the optimal heat pump solution for different applications. Moreover, the proposed Pareto analysis is employed to derive new cost functions considering the working fluid, source/supply temperatures, and the impact of design COP on TCI, with a formulation facilitating understanding and quantification of each factor. This methodology promotes heat pump adoption in industrial electrification, especially for high-temperature applications, potentially replacing natural gas boilers. Three case studies demonstrate the robustness of the approach to assessing capital costs, showing low deviation (<8%) between the detailed technoeconomic model and the fast-to-applicate new cost functions. The innovative cost functions ensure easy but accurate assessments, fostering confidence in transitioning to heat pump solutions.

Feasibility of Carbon Dioxide Storage Resource Use within Climate Change Mitigation Scenarios for the United States.

To progress decarbonization in the United States, numerous techno-economic models that project CO2 storage deployment at annual injection rates of 0.3-1.7 Gt year-1 by 2050 have been built. However, these models do not consider many geological, technical, or socio-economic factors that could impede the growth of geological storage resource use, and there is uncertainty about the feasibility of the resulting projections. Here, we evaluate storage scenarios across four major modeling efforts. We apply a growth modeling framework using logistic curves to analyze the feasibility of growth trajectories under constraints imposed by the associated storage resource availability. We show that storage resources are abundant, and resources of the Gulf Coast alone would be sufficient to meet national demand were it not for transport limitations. On the contrary, deployment trajectories require sustained average annual (exponential) growth at rates of >10% nationally for two of the three reports and between 3% and 20% regionally across four storage hubs projected in both reports with regional resolution. These rates are high relative to historical rates of growth in analogous large scale energy infrastructure in the United States. Projections for California appear to be particularly infeasible. Future modeling efforts should be constrained to more realistic deployment trajectories, which could be done with simple constraints from the type of modeling framework presented here.

Optimal scheduling and management of pumped hydro storage integrated with grid-connected renewable power plants

Pumped hydro-energy storage will become a fundamental element of power systems in the coming years by adding value to each link in electricity production and the supply chain. The growth of these systems is essential for improving the integration of renewables and avoiding dependence on fossil fuel sources, such as gas or oil. This paper presents the modeling and application of an optimal hourly management model of grid-connected photovoltaic and wind power plants integrated with reversible pump-turbine units to maximize the monthly operating profits of the energy system and meet electricity demand. The techno-economic dispatch model is formulated as a mixed-integer optimization problem. To assess the proposed model, it is applied to a Spanish case study system, and the results are obtained for an entire year. The combination of renewable energy and pumped hydro energy storage reduces energy dependence by decreasing energy costs by 27 % compared with a system without storage to satisfy the required electricity demand. The findings confirm that storage plays a key role in energy transition to ensure the security and stability of power systems with a higher share of renewable generation.