The concepts of risk-aversion, chance-constrained optimization, and robust optimization
have developed significantly over the last decade. Statistical learning community has also …

The concepts of risk aversion, chance-constrained optimization, and robust optimization
have developed significantly over the last decade. The statistical learning community has …

The topic of this book is multistage stochastic optimization. Multistage reflects the fact that an
optimal decision is an entire strategy or policy, which is executed during subsequent instants …

This paper evaluates the scheduling problem for energy hub system consisting of wind
turbine, combined heat and power units, auxiliary boilers, and energy storage devices via …

We focus on design and planning of a biofuel supply chain (SC) network from biomass to
demand centers where biomass supply is stochastic and seasonal, and facilities' capacity …

Microgrids with different technologies in distributed generations (DGs), different control
facilities and power electronic interfaces require proper management and operation …

Addressing the rapidly growing penetration of renewable energy sources and the increasing
variations in loads has been a significant challenge in the planning and operation of modern …

To make informed decisions in futures markets of electric energy, stochastic programming
models are commonly used. Such models treat stochastic processes via a set of scenarios …

This paper presents a Two Stage stochastic Programming (TSSP) model for the planning of
Multi-Microgrids (MMGs) in Active Distribution Networks (ADNs). The model aims to …

Coupling different energy infrastructures, ie the concept of energy hub (EH), is an efficient
approach to the optimal operation of both electrical and natural gas systems. This paper …