Against this backdrop, three capabilities are behind the innovation of Hitachi Energy’s next generation of ETRM software solutions.
1. Integration across the energy portfolio
The structures and systems of the global energy market are transforming. The rapid rise of renewable generation and increasing electrification pressures, combined with portfolios that now include physical assets, interconnected markets, and regulatory constraints, mean that end-to-end visibility is essential.
Organizations need the ability to quickly evaluate price, volume, credit, regulatory, and operational risks together rather than in isolation. Integrated energy portfolio management is quickly emerging as a foundational capability that unifies market insights, physical assets, and commercial execution to improve decision-making quality, consistency, and speed in volatile markets.
Integration also helps ensure that commercial operations, planning, investment analysis, and decision-making are all supported by a consistent, shared data foundation. This reduces the discrepancies that can arise when teams rely on disconnected data sources across the asset and commodity lifecycle.
2. Embedding AI-powered forecasting, optimization, and bid-to-bill in ETRM workflows
Energy markets are inherently uncertain, influenced by changes in weather, renewables generation, and consumption demand.
AI-powered forecasting introduces several structural improvements over traditional approaches, including more frequent updates, improved modelling of price drivers, such as supply and demand, and dynamic, probabilistic outputs that reflect uncertainty rather than single-point estimates.
With trading timelines shrinking and instability rising, inaccurate or slow forecasts directly impact hedging effectiveness, margin exposure, and intraday profit capture. However, forecasting alone is not enough.
ETRM solutions need to embed forecasting directly into optimization and execution workflows, enabling commercial teams to seamlessly translate insights into optimal trading, hedging, and dispatch decisions in real time. At the same time, integrated bid-to-bill capabilities ensure those decisions are consistently executed through scheduling, settlement, and invoicing, reducing manual effort, improving accuracy, and staying in compliance across all energy markets.
Together, these integrated, embedded capabilities enable faster, optimal, and more coordinated decisions from forecast to final invoice, improving performance across the energy portfolio.
3. Model simple and complex business processes at scale
Energy trading and commercial operations are becoming more diverse and higher in volumes due to evolving complex markets, contract structures, and regulatory environments. Scalability is no longer a technical consideration. It is a commercial requirement.
Legacy ETRM solutions can struggle to keep pace with changing requirements, leading to delays in launching new products or supporting new market structures, increased operational workarounds, higher costs, and vendor dependency.
As strategies evolve in real time, ETRM solutions must support both simple and highly complex, specialized business processes without extensive system modifications. Future-ready, cloud-native architecture enables faster processing and improved performance in positions, MTM, and risk calculations.
The ETRM architecture needs to include distributed processing layers (middle-tier services) and cloud-native software technologies, such as containerization and Kubernetes, allowing ETRM solutions to scale capacity dynamically, process large data volumes in parallel, and maintain resilient performance during periods of extreme market volatility. Combined with flexible, configurable data models, workflows, and calculations, this enables faster execution of new commercial strategies with lower long-term system costs.