Abstract
This paper presents a simulation-optimization model integrating particle swarm optimization (PSO) algorithm and sequential streamflow routing (SSR) method to maximize the net present value (NPV) of a hydropower storage development project. In the PSO-SSR model, the SSR method simulates the operation of reservoir and its powerplant on a monthly basis over long term for each set of controllable design and operational variables, which includes dam reservoir and powerplant capacities as well as reservoir rule curve parameters, being searched for by the PSO algorithm. To evaluate the project NPV for each set of the controllable variables, the “alternative thermal powerplant (ATP)” approach is employed to determine the benefit term of the project NPV. The PSO-SSR model has been used in the problem of optimal design and operation of Garsha hydropower development project in Iran. Results show that the model with a simple, hydropower standard operating policy results in an NPV comparable to another model optimizing operating policies.
| Original language | English |
|---|---|
| Title of host publication | Advances in Intelligent Systems and Computing |
| Publisher | Springer Verlag |
| Pages | 353-363 |
| Number of pages | 11 |
| Volume | 382 |
| ISBN (Print) | 9783662479254 |
| DOIs | |
| Publication status | Published - 2016 |
| Event | 2nd International Conference on Harmony Search Algorithm, ICHSA 2015 - Seoul, Korea, Republic of Duration: 2015 Aug 19 → 2015 Aug 21 |
Publication series
| Name | Advances in Intelligent Systems and Computing |
|---|---|
| Volume | 382 |
| ISSN (Print) | 21945357 |
Other
| Other | 2nd International Conference on Harmony Search Algorithm, ICHSA 2015 |
|---|---|
| Country | Korea, Republic of |
| City | Seoul |
| Period | 15/8/19 → 15/8/21 |
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Keywords
- Alternative thermal powerplant
- Hydropower
- Operating policy
- Particle swarm optimization
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science(all)
Cite this
Economic optimization of hydropower storage projects using alternative thermal powerplant approach. / Raeisi, Sina; Mousavi, S. Jamshid; Beidokhti, Mahmoud Taleb; Rousta, Bentolhoda A.; Kim, Joong Hoon.
Advances in Intelligent Systems and Computing. Vol. 382 Springer Verlag, 2016. p. 353-363 (Advances in Intelligent Systems and Computing; Vol. 382).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Economic optimization of hydropower storage projects using alternative thermal powerplant approach
AU - Raeisi, Sina
AU - Mousavi, S. Jamshid
AU - Beidokhti, Mahmoud Taleb
AU - Rousta, Bentolhoda A.
AU - Kim, Joong Hoon
PY - 2016
Y1 - 2016
N2 - This paper presents a simulation-optimization model integrating particle swarm optimization (PSO) algorithm and sequential streamflow routing (SSR) method to maximize the net present value (NPV) of a hydropower storage development project. In the PSO-SSR model, the SSR method simulates the operation of reservoir and its powerplant on a monthly basis over long term for each set of controllable design and operational variables, which includes dam reservoir and powerplant capacities as well as reservoir rule curve parameters, being searched for by the PSO algorithm. To evaluate the project NPV for each set of the controllable variables, the “alternative thermal powerplant (ATP)” approach is employed to determine the benefit term of the project NPV. The PSO-SSR model has been used in the problem of optimal design and operation of Garsha hydropower development project in Iran. Results show that the model with a simple, hydropower standard operating policy results in an NPV comparable to another model optimizing operating policies.
AB - This paper presents a simulation-optimization model integrating particle swarm optimization (PSO) algorithm and sequential streamflow routing (SSR) method to maximize the net present value (NPV) of a hydropower storage development project. In the PSO-SSR model, the SSR method simulates the operation of reservoir and its powerplant on a monthly basis over long term for each set of controllable design and operational variables, which includes dam reservoir and powerplant capacities as well as reservoir rule curve parameters, being searched for by the PSO algorithm. To evaluate the project NPV for each set of the controllable variables, the “alternative thermal powerplant (ATP)” approach is employed to determine the benefit term of the project NPV. The PSO-SSR model has been used in the problem of optimal design and operation of Garsha hydropower development project in Iran. Results show that the model with a simple, hydropower standard operating policy results in an NPV comparable to another model optimizing operating policies.
KW - Alternative thermal powerplant
KW - Hydropower
KW - Operating policy
KW - Particle swarm optimization
UR - http://www.scopus.com/inward/record.url?scp=84946761029&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84946761029&partnerID=8YFLogxK
U2 - 10.1007/978-3-662-47926-1_34
DO - 10.1007/978-3-662-47926-1_34
M3 - Conference contribution
AN - SCOPUS:84946761029
SN - 9783662479254
VL - 382
T3 - Advances in Intelligent Systems and Computing
SP - 353
EP - 363
BT - Advances in Intelligent Systems and Computing
PB - Springer Verlag
ER -