Journal ArticleDOI
Stochastic generation expansion planning by means of stochastic dynamic programming
TLDR
In this paper, a method based on stochastic dynamic programming is proposed to handle uncertainties in important variables such as energy demand and prices of energy carriers together with the dynamics of the system.Abstract:
Most generation expansion planning tools do not model uncertainties in important variables such as energy demand and prices of energy carriers together with the dynamics of the system. A method for handling these uncertainties in generation expansion problems is described. The method is based on stochastic dynamic programming. As the uncertain variables are modeled by Markov chains they give a natural year-to-year dependence of the variables. This modeling makes it possible to describe the connection between investment decisions, time, construction periods, and uncertainty. The importance of modeling these connections is demonstrated by a realistic example. >read more
Citations
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Journal ArticleDOI
Optimization methods for electric utility resource planning
TL;DR: This review is to examine how the needs of utility planners for optimization models have changed in response to environmental concerns, increased competition, and growing uncertainty.
Journal ArticleDOI
Planning and Scheduling under Uncertainty: A Review Across Multiple Sectors
TL;DR: This paper provides an overview of the key contributions within the planning and scheduling communities with specific emphasis on uncertainty analysis, and is the first work which attempts to provide a comprehensive description of two-stage stochastic programming and parametric programming.
Journal ArticleDOI
Optimal investments in power generation under centralized and decentralized decision making
TL;DR: In this paper, a stochastic dynamic programming algorithm is used to solve the investment problem, where uncertainty in demand is represented as a discrete Markov chain, and the stochastically dynamic model allows us to evaluate investment projects in new base and peak load power generation as real options, and determine optimal timing of the investments.
Journal ArticleDOI
Two-Stage Robust Generation Expansion Planning: A Mixed Integer Linear Programming Model
TL;DR: In this article, a new uncertainty handling framework for optimal generation expansion planning (GEP) amalgamating the notions of single-stage and two-stage robust optimization (RO) is presented.
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Designing effective and efficient incentive policies for renewable energy in generation expansion planning
TL;DR: In this article, the authors present a bilevel optimization approach to design effective and efficient incentive policies for stimulating investment in renewable energy. And they obtain the most effective incentive policies in the context of generation expansion planning, in which a centralized planner makes investment decisions for the energy system to serve projected demand of electricity.
References
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Journal ArticleDOI
Optimal Generation Planning Considering Uncertainty
TL;DR: In this paper, a procedure for determining the optimal plan for the expansion of the generation facilities of a power system over a long period of time is described, based on probabalistic simulation methods and an advanced dynamic programming formulation of the problem.
Journal ArticleDOI
Planning for New Electric Generation Technologies A Stochastic Dynamic Programming Approach
TL;DR: In this article, an expansion planning method was developed which considered the complex, uncertain and dynamic nature of the electric utility decision environment, and a stochastic dynamic programming model was formkilated and applied in case studies.
Journal ArticleDOI
Decision Framework for New Technologies: A Tool for Strategic Planning of Electric Utilities
TL;DR: The DECISION Framework for New Technologies (DEFNET) as mentioned in this paper is one such tool that has been developed at SC (Systems Control) under the sponsorship of EPRI (Electric Power Research Institute).