Last updated on Jun 22, 2024

What are the current and emerging trends in energy sector modeling and simulation tools?

Energy sector modeling and simulation tools are essential for analyzing and optimizing the performance, reliability, and sustainability of various energy systems and scenarios. These tools can help decision-makers, planners, engineers, and researchers address the complex and dynamic challenges of the energy transition, such as integrating renewable sources, managing demand and supply, reducing emissions, and enhancing resilience. In this article, we will explore some of the current and emerging trends in energy sector modeling and simulation tools, and how they can benefit different stakeholders and applications.

1 Multi-scale and multi-domain modeling

One of the current trends in energy sector modeling and simulation tools is the development and integration of multi-scale and multi-domain models, which can capture the interactions and dependencies between different levels and aspects of the energy system. For example, multi-scale models can span from the micro-level (such as individual devices or buildings) to the macro-level (such as regional or national grids), while multi-domain models can cover different energy vectors (such as electricity, heat, gas, or hydrogen) and sectors (such as transport, industry, or agriculture). These models can provide a more comprehensive and realistic representation of the energy system, and enable the analysis of cross-sectoral synergies, trade-offs, and impacts.

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Abiola Owosibo

R.Eng || MNSE || Data Analyst || STEM Advocate || Counsellor || Engineering & Research
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Successful development and integration of multi-scale and multi-domain models are necessary in the management of energy consequently enhancing decarbonization

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2 Data-driven and artificial intelligence methods

Another current trend in energy sector modeling and simulation tools is the incorporation of data-driven and artificial intelligence (AI) methods, which can leverage the increasing availability and quality of data from various sources, such as smart meters, sensors, satellites, or social media. These methods can enhance the accuracy, flexibility, and scalability of the models, and enable the discovery of new insights, patterns, and solutions. For example, data-driven and AI methods can be used for forecasting demand and supply, optimizing operation and planning, detecting anomalies and faults, and learning from feedback and adaptation.

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MOHSIN IQBAL

Advisor | Top Voice Corporate Sustainability | Top Voice Energy Management [All Posts are personal opinions only]
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At a commercial scale data driven decision making towards infrastructure investments, grid designs, energy production targets, etc. is being further complimented by scenario modelling abilities of AI tools allowing for additional variables to be included such as fossil fuel source dependency vs. renewable energy, or producer & consumer model vs. prosumer models.

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Abiola Owosibo

R.Eng || MNSE || Data Analyst || STEM Advocate || Counsellor || Engineering & Research
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In addition, data driven and AI methods can also be used to carry out sensitivity analysis in which different basic parameters are varied to know the performance of the system making predictive control easier

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3 Cloud-based and collaborative platforms

A third current trend in energy sector modeling and simulation tools is the migration and development of cloud-based and collaborative platforms, which can offer more accessibility, affordability, and interoperability of the tools. These platforms can enable the users to access and run the models online, without the need for installing or maintaining software or hardware. They can also facilitate the sharing and integration of data, models, and results among different users, organizations, or domains, and support the co-creation and co-evaluation of energy scenarios and policies.

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Abiola Owosibo

R.Eng || MNSE || Data Analyst || STEM Advocate || Counsellor || Engineering & Research
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This is a novel strategy. However, there is need to educate the users on the wherewithal of the system for effective use. Errors should be avoided to prevent disruption of the energy management system.

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4 Virtual and augmented reality technologies

One of the emerging trends in energy sector modeling and simulation tools is the adoption and integration of virtual and augmented reality (VR/AR) technologies, which can provide more immersive and interactive experiences of the energy system. These technologies can enhance the visualization, communication, and engagement of the models and simulations, and enable the users to explore and manipulate different aspects and scenarios of the energy system in a virtual or augmented environment. For example, VR/AR technologies can be used for training and education, stakeholder consultation, public awareness, or design and testing.

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5 Blockchain and distributed ledger technologies

Another emerging trend in energy sector modeling and simulation tools is the application and integration of blockchain and distributed ledger technologies (DLT), which can provide more security, transparency, and efficiency of the energy system. These technologies can enable the creation and management of decentralized and distributed energy networks, markets, and transactions, and support the integration of distributed energy resources, such as rooftop solar panels, batteries, or electric vehicles. For example, blockchain and DLT can be used for peer-to-peer energy trading, grid balancing, demand response, or carbon tracking.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Steven Henry

💚 Expert in retrofit energy efficiency and decarbonising solutions to reduce energy consumption and cut costs to education, the public sector, and commercial premises.
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Tools are increasingly designed to model hybrid systems that combine various renewable sources like solar, wind, and hydropower with traditional fossil fuels. Advanced simulations now consider the variability and intermittency of renewables, integrating real-time weather data and forecasting.

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What are the current and emerging trends in energy sector modeling and simulation tools?

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1 Multi-scale and multi-domain modeling

2 Data-driven and artificial intelligence methods

3 Cloud-based and collaborative platforms

4 Virtual and augmented reality technologies

5 Blockchain and distributed ledger technologies

6 Here’s what else to consider

Energy Management

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