Stochastic Planning and Modeling for Energy Systems
Methods, Applications, and Developments
- 1st Edition - August 18, 2026
- Latest edition
- Editor: Miadreza Shafie-khah
- Language: English
Stochastic Planning and Modeling for Energy Systems: Methods, Applications, and Developments acts as a comprehensive resource on both modeling and planning techniques for stocha… Read more
Description
Description
Additionally, real-world planning challenges, including capacity expansion, microgrid design, and integration of new technologies like hydrogen, batteries, and supercapacitors are examined. Real-world case studies and algorithms are included to demonstrate stochastic workflows and methods. This is a valuable reference for transmission and distribution operators, system planners, market designers, power-system engineers, energy analysts, and MSc-level graduate students in power systems engineering.
Key features
Key features
- Demonstrates end-to-end stochastic workflows using detailed case studies, including islanded microgrids and high-EV scenarios
- Presents step-by-step treatments of sampling methods, reduction techniques, multistage programming, and risk-measure incorporation through proven algorithms
- Provides software tutorials on implementing Pyomo, Pandapower, GAMS, and PLEXOS
Readership
Readership
Table of contents
Table of contents
1. AI and data-driven methods in scenario generation and reduction
2. Scenario generation techniques: From Monte Carlo, Latin hypercube, and beyond
3. Scenario reduction methods: Clustering, fast forward selection and distance metrics
4. A synergistic framework for efficient and uncertainty-calibrated solar irradiance forecasting using data compression and optimized neural networks
5. Resilient microgrid operation under uncertainty
6. Case studies in renewable-dominant and islanded microgrids
7. Modeling electric vehicle uncertainty: Charging behavior and grid impact
8. Demand-side uncertainty and planning for flexibility provision
9. Navigating competition in retailing layer: A risk-averse decision-making model for electricity markets retailers
10. Stochastic reinforcement learning for uncertainty-aware power converter control using digital twin
11. Planning for distributed energy resources and microgrids—Scope: Stochastic siting, sizing, and control of DER clusters in diverse contexts
12. AI-driven energy management for renewable-dominated isolated microgrid under uncertainty
13. Microgrid and power network state estimation with the open-source tool GridCal (aPAC)
14. AI-driven scenario generation and reduction for renewable-rich energy systems: RNN-WGAN synthesis and deep clustering
15. Intelligent energy management for renewable energy communities and microgrids: Models, algorithms, and practical constraints
16. DER clusters in diverse contexts: Stochastic siting, sizing, and control for distributed energy resources and microgrids planning
17. Stochastic modeling for energy storage and hydrogen systems in hybrid electric platforms
18. A stochastic and nature-inspired electric distribution grids architecture: Data-driven futuristic power grids through emergent intelligence-based operational mechanism
Product details
Product details
- Edition: 1
- Latest edition
- Published: August 18, 2026
- Language: English
About the editor
About the editor
MS