NDLI: Stochastic optimization models for power generation capacity expansion with risk management

Content Provider	IEEE Xplore Digital Library
Author	Vespucci, M.T. Bertocchi, M. Zigrino, S. Escudero, L.F.
Copyright Year	2013
Description	Author affiliation: Dept. of Stat. & Oper. Res., Univ. Rey Juan Carlos, Mostoles, Spain (Escudero, L.F.) \|\| Dept. of Manage., Econ. & Quantitative Methods, Univ. of Bergamo, Bergamo, Italy (Vespucci, M.T.; Bertocchi, M.; Zigrino, S.)
Abstract	We propose a two-stage stochastic optimization model for maximizing the profit of a price-taker power producer who has to decide his own power generation capacity expansion plan in a long time horizon, taking into account the uncertainty of the following parameters: fuel costs; market electricity prices, as well as prices of green certificates and $CO_{2}$ emission allowances; market share. The parameter uncertainty is represented by scenarios on their values along the planning horizon and the associated probability of occurrence. We first discuss the risk neutral stochastic model, that maximizes over all scenarios the net present value of the expected profit along the planning horizon. The risk neutral model does not take into account the variability of the objective function value over the scenarios and, then, the possibility of realizing in some scenarios a very low profit. Several approches have been introduced in the literature for measuring the profit risk. In this work we consider the Conditional Value at Risk, that requires a confidence level to be defined, and the First-order Stochastic Dominance constraints, for which a benchmark need to be assigned. By using a realistic case study, we report the main results of considering risk averse strategies under different hypotheses of the available budget, analysing the impact on the expected profit.
Starting Page	1
Ending Page	8
File Size	377067
Page Count	8
File Format	PDF
ISBN	9781479920082
ISSN	21654093
DOI	10.1109/EEM.2013.6607352
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-27
Publisher Place	Sweden
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electricity Stochastic processes Production Coal Air pollution Planning Power generation
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Application of scenario reduction to LDC and risk based generation expansion planning

A preliminary investigation on transmission system expansion planning in competitive electricity market environment

Valuation of CHP power plant portfolios using recursive stochastic optimization

Dynamic risk management in electricity portfolio optimization via polyhedral risk functionals

Generation Capacity Expansion Planning under demand uncertainty using stochastic mixed-integer programming

Evaluation of uncertainties on generation expansion planning

Temporal versus stochastic granularity in thermal generation capacity planning with wind power

Power generation planning and risk management in a liberalised market

Microgrid's Generation Expansion Planning Considering Lower Carbon Economy

Stochastic optimization models for power generation capacity expansion with risk management

Similar Documents

Application of scenario reduction to LDC and risk based generation expansion planning

A preliminary investigation on transmission system expansion planning in competitive electricity market environment

Valuation of CHP power plant portfolios using recursive stochastic optimization

Dynamic risk management in electricity portfolio optimization via polyhedral risk functionals

Generation Capacity Expansion Planning under demand uncertainty using stochastic mixed-integer programming

Evaluation of uncertainties on generation expansion planning

Temporal versus stochastic granularity in thermal generation capacity planning with wind power

Power generation planning and risk management in a liberalised market

Microgrid's Generation Expansion Planning Considering Lower Carbon Economy

Stochastic optimization models for power generation capacity expansion with risk management