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Integrated System Planning: Emerging Software Requirements in the Power Industry

  • Open Energy Transition

Research output: Contribution to journal › Article › peer-review

2 Scopus Citations

Abstract

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.
Original languageAmerican English
Pages (from-to)100-115
Number of pages16
JournalIEEE Power and Energy Magazine
Volume24
Issue number4
DOIs
StatePublished - 2026

NLR Publication Number

  • NLR/JA-6A40-98621

Keywords

  • artificial intelligence
  • costs
  • intserv networks
  • life cycle assessment
  • machine learning
  • power system economics
  • power system planning
  • requirements engineering
  • software development management
  • software tools

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