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Stochastic Planning and Modeling for Energy Systems : Methods, Applications, and Developments
Stochastic Planning and Modeling for Energy Systems : Methods, Applications, and Developments
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ISBN No.: 9780443452987
Pages: 350
Year: 202608
Format: Trade Paper
Price: $ 280.00
Dispatch delay: Dispatched between 7 to 15 days
Status: Available (Forthcoming)

1. Introduction to Stochastic Planning and Modeling in Energy Systems Scope: Concepts, motivations, structure; modern uncertainty sources 2. Characterizing Uncertainty in Energy Systems: Data and Statistical Foundations Scope: Load, renewable, price, and demand-side statistical models; data preprocessing 3. Scenario Generation Techniques: Monte Carlo, Latin Hypercube & Beyond Scope: Sampling-based and quasi-Monte Carlo methods; trade-offs in accuracy vs. cost 4. Scenario Reduction Methods: Clustering, Fast Forward Selection & Distance Metrics Scope: Backward/forward reduction, moment-matching, distance measures 5. Stochastic Investment Planning: Generation, Transmission & Distribution Scope: Multistage programming for capacity expansion; CVaR, robust optimization 6. Operational Planning under Uncertainty: Unit Commitment and Economic Dispatch Scope: Day-ahead and real-time dispatch; renewables, storage, demand response 7.


Case Studies in Renewable-Dominant and Islanded Microgrids Scope: High-penetration PV/wind and off-grid microgrids; performance metrics 8. Modeling Electric Vehicle Uncertainty: Charging Behavior & Grid Impact Scope: Aggregate EV load scenarios and distribution impacts 9. Demand-Side Uncertainty and Planning for Flexibility Provision Scope: End-use variability, demand-response design, flexibility markets 10. Stochastic Modeling for Energy Storage and Hydrogen Systems Scope: Battery degradation, supercapacitors, electrolyzer scenarios, flexibility roles 11. Software Tools and Simulation Frameworks for Stochastic Planning Scope: Pyomo, Pandapower, GAMS, PLEXOS tutorials for scenario modeling 12. AI and Data-Driven Methods in Scenario Generation and Reduction Scope: GANs, deep clustering, and other ML techniques for efficient scenarios 13. Market Design, Policy and Regulatory Implications of Stochastic Planning Scope: Tariff structures, capacity markets, and regulatory frameworks under uncertainty 14. Strategic Capacity Expansion Planning under Uncertainty Scope: High-level investment strategies balancing cost, risk, and flexibility 15.


Planning for Distributed Energy Resources and Microgrids Scope: Stochastic siting, sizing, and control of DER clusters in diverse contexts.


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Browse Subject Headings