TY - GEN
T1 - Expansion co-planning with uncertainties in a coupled energy market
AU - Qiu, Jing
AU - Dong, Zhao Yang
AU - Zhao, Jun Hua
AU - Meng, Ke
AU - Tian, Huiqiao
AU - Wong, Kit Po
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2014/10/29
Y1 - 2014/10/29
N2 - Natural gas is an important fuel source in the power industry. Electricity and natural gas are both energy that can be directly consumed. It is imperative that gas power plants, electricity transmission lines and gas pipelines are co-planned in future energy transmission expansion. The co-planning process is modeled as a mixed integer nonlinear programming problem to handle the multi-stage and conflicting objectives simultaneously. We propose a novel optimization algorithm called Historical Driven Differential Evolution (HDDE) to identify the optimal co-expansion plan in terms of the social welfare. Planning risks due to uncertainties of energy load, load percentages that can be mutually transferred between gas and electricity, and market price are effectively evaluated by the flexibility criterion in stochastic programming. Meanwhile, we use the sequential importance sampling (SIS) to deploy scenario reduction for a higher computational efficiency. After a test in the IEEE 14-bus system, promising results are obtained to validate our approach. © 2014 IEEE.
AB - Natural gas is an important fuel source in the power industry. Electricity and natural gas are both energy that can be directly consumed. It is imperative that gas power plants, electricity transmission lines and gas pipelines are co-planned in future energy transmission expansion. The co-planning process is modeled as a mixed integer nonlinear programming problem to handle the multi-stage and conflicting objectives simultaneously. We propose a novel optimization algorithm called Historical Driven Differential Evolution (HDDE) to identify the optimal co-expansion plan in terms of the social welfare. Planning risks due to uncertainties of energy load, load percentages that can be mutually transferred between gas and electricity, and market price are effectively evaluated by the flexibility criterion in stochastic programming. Meanwhile, we use the sequential importance sampling (SIS) to deploy scenario reduction for a higher computational efficiency. After a test in the IEEE 14-bus system, promising results are obtained to validate our approach. © 2014 IEEE.
KW - flexibility
KW - power system planning
KW - risk management
UR - https://www.scopus.com/pages/publications/84930989597
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84930989597&origin=recordpage
U2 - 10.1109/PESGM.2014.6939050
DO - 10.1109/PESGM.2014.6939050
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781479964154
VL - 2014-October
T3 - IEEE Power and Energy Society General Meeting
BT - 2014 IEEE PES General Meeting / Conference and Exposition
PB - IEEE Computer Society
T2 - 2014 IEEE Power and Energy Society General Meeting
Y2 - 27 July 2014 through 31 July 2014
ER -