Application of stochastic programming to electricity generation planning in South Africa

A two-stage stochastic programming model is used to solve the electricity generation planning problem in South Africa for the period 2013 to 2050, in an attempt to minimise expected cost. Costs considered are capital and running costs. Unknown future electricity demand is the source of uncertainty represented by four scenarios with equal probabilities. The results show that the main contributors for new capacity are coal, wind, hydro and gas/diesel. The minimum costs obtained by solving the two-stage stochastic programming models range from R2 201 billion to R3 094 billion.

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A risk-averse two-stage stochastic programming model for a joint multi-item capacitated line balancing and lot-sizing problem

European Journal of Operational Research ◽

10.1016/j.ejor.2021.09.043 ◽

2021 ◽

Author(s):

Yuchen Li ◽

Francisco Saldanha-da-Gama ◽

Ming Liu ◽

Zaoli Yang

Keyword(s):

Stochastic Programming ◽

Programming Model ◽

Lot Sizing ◽

Line Balancing ◽

Risk Averse ◽

Two Stage ◽

Lot Sizing Problem ◽

Stochastic Programming Model

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Developing a Two-Stage Stochastic Programming Model for CO2 Disposal Planning under Uncertainty

Industrial & Engineering Chemistry Research ◽

10.1021/ie201148x ◽

2012 ◽

Vol 51 (8) ◽

pp. 3368-3380 ◽

Cited By ~ 8

Author(s):

Jee-Hoon Han ◽

Jun-Hyung Ryu ◽

In-Beum Lee

Keyword(s):

Stochastic Programming ◽

Programming Model ◽

Planning Under Uncertainty ◽

Two Stage ◽

Stochastic Programming Model

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Two-stage stochastic programming model for the regional-scale electricity planning under demand uncertainty

Energy ◽

10.1016/j.energy.2016.09.112 ◽

2016 ◽

Vol 116 ◽

pp. 1145-1157 ◽

Cited By ~ 15

Author(s):

Yun-Hsun Huang ◽

Jung-Hua Wu ◽

Yu-Ju Hsu

Keyword(s):

Stochastic Programming ◽

Demand Uncertainty ◽

Programming Model ◽

Regional Scale ◽

Two Stage ◽

Electricity Planning ◽

Stochastic Programming Model

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An interval-fuzzy two-stage stochastic programming method for filter management of hydraulic systems

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1177/0954406214563737 ◽

2014 ◽

Vol 229 (15) ◽

pp. 2788-2809

Author(s):

Hui Ji ◽

Songlin Nie ◽

Yeqing Huang

Keyword(s):

Stochastic Programming ◽

Hydraulic System ◽

Programming Model ◽

Optimal Strategies ◽

Management Policy ◽

Continuous Variables ◽

Hydraulic Systems ◽

Two Stage ◽

Interval Numbers ◽

Stochastic Programming Model

An interval-fuzzy two-stage stochastic programming model for filter management of hydraulic system under uncertainties is proposed in this paper. The interval-fuzzy two-stage stochastic programming model integrates the two-stage stochastic programming, fuzzy programming, and interval parameter nonlinear programming into an optimization model of contamination control in hydraulic system. For a typical hydraulic system, it can be used for expressing the uncertainties existed in the purchase cost of filters, contamination ingression and generation rates, and contamination-holding capacity as probability functions, interval numbers, and fuzzy sets. The developed method is applied to examining the decisions on the adoption of bypass filter and selection of filters within multi-segments, multi-period, and multi-option context. All potential scenarios of filters management policy associated with different economic penalties, objectives, and reliability of system are analyzed. The results of the illustrative example show that the reasonable solutions are generated, including binary and continuous variables which help the decision maker identify optimal strategies for filter allocation and selection, planning the adoption of bypass filter under different working conditions.

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