Precise Modeling and Process Integration from a Single Platform to Enhance Analytics in Power Generation, Transmission, and Distribution
To meet global emission reduction targets, renewable energy must account for at least 42% of energy consumption by 2030 and 60% by 2050, compared to 17% in 2021. Although the global power generation sector is moving toward renewable power to curb greenhouse gas emissions, renewable energy is intermittent. Therefore, its increased share in the power generation mix affects both conventional power plant operations and the transmission and distribution grid. The increased share of renewables has lowered dependence and capacity utilization of conventional steam turbine and coal-fired power generation plants. This trend poses several challenges to conventional power plants. Essentially, the intermittency of renewables can compromise grid stability. Digital twin technology addresses these challenges by enhancing the flexibility of conventional power generation, improving the predictability of renewable power generation, and improving grid resiliency.
This study covers the fundamentals and working principle of digital twin systems, offering detailed analysis of digital twin applications across power generation and transmission and distribution systems. It includes key growth opportunities, growth drivers and restraints, major innovations, and research and development activities in digital twin technology for the energy sector.
The study also includes multiple case studies that illustrate the advantages digital twins offer the energy sector. It discusses key stakeholders involved in the development of innovative digital twin solutions for energy applications, including an analysis of the global patent landscape that highlights key patent owners/applicants and the major areas of research.
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Companies Mentioned (Partial List)
A selection of companies mentioned in this report includes, but is not limited to:
- Envelio
- Siemens Energy
