scholarly journals Contracts in electricity markets under EU ETS: A stochastic programming approach

2021 ◽  
pp. 105309
Author(s):  
Arega Getaneh Abate ◽  
Rossana Riccardi ◽  
Carlos Ruiz
Keyword(s):  
Stochastic Programming ◽  
Electricity Markets ◽  
Programming Approach ◽  
Eu Ets

scholarly journals Multistage Stochastic Programming for VPP Trading in Continuous Intraday Electricity Markets

2021 ◽  
Author(s):  
Priyanka Shinde ◽  
Iasonas Kouveliotis-Lysikatos ◽  
Mikael Amelin
Keyword(s):  
Stochastic Programming ◽  
Electricity Markets ◽  
Electricity Market ◽  
Power Plants ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
Programming Approach ◽  
Multistage Stochastic Programming ◽  
Hydro Power ◽  
Dual Dynamic Programming

<div>The stochastic nature of renewable energy sources has increased the need for intraday trading in electricity markets. Intraday markets provide the possibility to the market participants to modify their market positions based on their updated forecasts. In this paper, we propose a multistage stochastic programming approach to model the trading of a Virtual Power Plant (VPP), comprising thermal, wind and hydro power plants, in the Continuous Intraday (CID) electricity market. The order clearing in the CID market is enabled by the two presented models, namely the Immediate Order Clearing (IOC) and the Partial Order Clearing (POC). We tackle the proposed problem with a modified version of Stochastic Dual Dynamic Programming (SDDP) algorithm. The functionality of our model is demonstrated by performing illustrative and large scale case studies and comparing the performance with a benchmark model.</div>

scholarly journals Multistage Stochastic Programming for VPP Trading in Continuous Intraday Electricity Markets

2021 ◽  
Author(s):  
Priyanka Shinde ◽  
Iasonas Kouveliotis-Lysikatos ◽  
Mikael Amelin
Keyword(s):  
Stochastic Programming ◽  
Electricity Markets ◽  
Electricity Market ◽  
Power Plants ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
Programming Approach ◽  
Multistage Stochastic Programming ◽  
Hydro Power ◽  
Dual Dynamic Programming

<div>The stochastic nature of renewable energy sources has increased the need for intraday trading in electricity markets. Intraday markets provide the possibility to the market participants to modify their market positions based on their updated forecasts. In this paper, we propose a multistage stochastic programming approach to model the trading of a Virtual Power Plant (VPP), comprising thermal, wind and hydro power plants, in the Continuous Intraday (CID) electricity market. The order clearing in the CID market is enabled by the two presented models, namely the Immediate Order Clearing (IOC) and the Partial Order Clearing (POC). We tackle the proposed problem with a modified version of Stochastic Dual Dynamic Programming (SDDP) algorithm. The functionality of our model is demonstrated by performing illustrative and large scale case studies and comparing the performance with a benchmark model.</div>

A Multi-Stage Stochastic Programming Approach to the Optimal Surveillance and Control of Emerald Ash Borer in Cities

2020 ◽  
Author(s):  
Eyyüb Y. Kıbış ◽  
I. Esra Buyuktahtakin ◽  
Robert G. Haight ◽  
Najmaddin Akhundov ◽  
Kathleen Knight ◽  
...  
Keyword(s):  
Stochastic Programming ◽  
Emerald Ash Borer ◽  
Programming Approach ◽  
Multi Stage ◽  
And Control

scholarly journals A stochastic programming approach for Shelter location and evacuation planning

2018 ◽  
Vol 52 (3) ◽  
pp. 779-805 ◽  
Author(s):  
Vedat Bayram ◽  
Hande Yaman
Keyword(s):  
Stochastic Programming ◽  
Shortest Paths ◽  
Evacuation Planning ◽  
Programming Approach ◽  
Mean Values ◽  
The Road ◽  
Traffic Allocation ◽  
Evacuation Plan ◽  
Allocation Decisions

Shelter location and traffic allocation decisions are critical for an efficient evacuation plan. In this study, we propose a scenario-based two-stage stochastic evacuation planning model that optimally locates shelter sites and that assigns evacuees to nearest shelters and to shortest paths within a tolerance degree to minimize the expected total evacuation time. Our model considers the uncertainty in the evacuation demand and the disruption in the road network and shelter sites. We present a case study for a potential earthquake in Istanbul. We compare the performance of the stochastic programming solutions to solutions based on single scenarios and mean values.

A stochastic programming approach for integrated nurse staffing and assignment

2013 ◽  
Vol 45 (10) ◽  
pp. 1059-1076 ◽  
Author(s):  
Prattana Punnakitikashem ◽  
Jay M. Rosenberber ◽  
Deborah F. Buckley-Behan
Keyword(s):  
Stochastic Programming ◽  
Nurse Staffing ◽  
Programming Approach

Solving Solid Transportation Problems With Multi-Choice Cost and Stochastic Supply and Demand

2018 ◽  
pp. 137-170 ◽  
Author(s):  
Sankar Kumar Roy ◽  
Deshabrata Roy Mahapatra
Keyword(s):  
Stochastic Programming ◽  
Objective Function ◽  
Transportation Problem ◽  
Supply And Demand ◽  
Optimal Solution ◽  
Programming Approach ◽  
Solid Transportation Problem ◽  
New Approach ◽  
Non Linear Programming ◽  
The Cost

In this chapter, the authors propose a new approach to analyze the Solid Transportation Problem (STP). This new approach considers the multi-choice programming into the cost coefficients of objective function and stochastic programming, which is incorporated in three constraints, namely sources, destinations, and capacities constraints, followed by Cauchy's distribution for solid transportation problem. The multi-choice programming and stochastic programming are combined into a solid transportation problem, and this new problem is called Multi-Choice Stochastic Solid Transportation Problem (MCSSTP). The solution concepts behind the MCSSTP are based on a new transformation technique that will select an appropriate choice from a set of multi-choice, which optimize the objective function. The stochastic constraints of STP converts into deterministic constraints by stochastic programming approach. Finally, the authors construct a non-linear programming problem for MCSSTP, and by solving it, they derive an optimal solution of the specified problem. A realistic example on STP is considered to illustrate the methodology.

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