Call For Papers

PMAPS 2026, hosted by the University of Utah and WECC, and technically sponsored by the IEEE Power & Energy Society (IEEE PES), invites original, unpublished papers presenting new research, methodologies, and applications of probabilistic methods in power systems. The conference provides a premier international platform for sharing advances in modeling, simulation, planning, operation, and decision-making under uncertainty. All papers accepted and presented in the conference will be published in the IEEE Xplore Digital Library.

Technical Sponsors

This topic focuses on advancing probabilistic and risk-based methods for forecasting, planning, and operating modern power systems under uncertainty.

Papers may cover, but are not limited to, the following subtopics:
- Demand, generation, and market forecasting and uncertainty modeling
- Integration and coordination of inverter-based resources, distributed energy resources, and virtual power plants
- AI for stochastic/probabilistic grid control
- Emerging applications of generative AI, large language models (LLMs), foundation models, and federated learning

This topic addresses the modeling, planning, and operational challenges posed by large and rapidly growing loads, including data centers and electrified industries.

Papers may cover, but are not limited to, the following subtopics:
- Characterization, modeling, and forecasting of large loads
- Bulk power system operation and planning considering large loads
- Power system adequacy analysis considering large loads integration
- Stability analysis of grids with extensive large loads integration
- Siting, permitting, and policy implications for new large loads and associated generation projects (e.g., nuclear and geothermal)
- Market design and flexibility mechanisms for large load variability management

This topic highlights methods to understand, model, and mitigate the effects of extreme events and cascading failures to enhance grid resilience.

Papers may cover, but are not limited to, the following subtopics:
- High-impact, low-probability event analysis
- Grid resilience metrics, frameworks, and enhancements
- Cascading failures in electric power systems
- Event-driven planning and operational strategies
- Compounding hazards modeling and mitigation
- Outage data analysis and data-driven resilience assessment tools

This topic focuses on leveraging data analytics and probabilistic methods to optimize asset performance, maintenance, and lifecycle management in power systems.

Papers may cover, but are not limited to, the following subtopics:
- Asset condition monitoring, data management, and analysis
- Reliability-centered and condition-based maintenance and asset management
- Power quality monitoring and enhancement tools
- End-of-life prognosis and aging assessment tools

Important Author Information

Please read the following requirements carefully before submitting your paper.

All submissions must be written in English.
Papers should present original, unpublished research results, methodologies, or applications relevant to probabilistic methods in power systems. Submissions must align with the scope of the conference tracks.
Manuscripts should follow the IEEE standard two-column conference paper format and be submitted as a PDF file.
The maximum paper length is six (6) pages, including figures, tables, and references.
All papers will undergo a peer-review process conducted by the PMAPS Technical Committee.
Corresponding authors will be notified of the decision by email.

Accepted papers will be published in the IEEE Xplore Digital Library. For publication, at least one author must register and present the paper at the conference.

Authors are requested to prepare their manuscripts using the following templates.

Latex Template：Click to download

Word Template：Click to download

Once prepared, manuscripts should be submitted using the submission portal here.

PMAPS 2026 Salt Lake City, UT

Call for Papers

Conference Topics

Important Author Information

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