TY - JOUR
T1 - Multi-period multi-objective electricity generation expansion planning problem with Monte-Carlo simulation
AU - Tekiner, Hatice
AU - Coit, David W.
AU - Felder, Frank A.
PY - 2010/12
Y1 - 2010/12
N2 - A new approach to the electricity generation expansion problem is proposed to minimize simultaneously multiple objectives, such as cost and air emissions, including CO2 and NOx, over a long term planning horizon. In this problem, system expansion decisions are made to select the type of power generation, such as coal, nuclear, wind, etc., where the new generation asset should be located, and at which time period expansion should take place. We are able to find a Pareto front for the multi-objective generation expansion planning problem that explicitly considers availability of the system components over the planning horizon and operational dispatching decisions. Monte-Carlo simulation is used to generate numerous scenarios based on the component availabilities and anticipated demand for energy. The problem is then formulated as a mixed integer linear program, and optimal solutions are found based on the simulated scenarios with a combined objective function considering the multiple problem objectives. The different objectives are combined using dimensionless weights and a Pareto front can be determined by varying these weights. The mathematical model is demonstrated on an example problem with interesting results indicating how expansion decisions vary depending on whether minimizing cost or minimizing greenhouse gas emissions or pollutants is given higher priority.
AB - A new approach to the electricity generation expansion problem is proposed to minimize simultaneously multiple objectives, such as cost and air emissions, including CO2 and NOx, over a long term planning horizon. In this problem, system expansion decisions are made to select the type of power generation, such as coal, nuclear, wind, etc., where the new generation asset should be located, and at which time period expansion should take place. We are able to find a Pareto front for the multi-objective generation expansion planning problem that explicitly considers availability of the system components over the planning horizon and operational dispatching decisions. Monte-Carlo simulation is used to generate numerous scenarios based on the component availabilities and anticipated demand for energy. The problem is then formulated as a mixed integer linear program, and optimal solutions are found based on the simulated scenarios with a combined objective function considering the multiple problem objectives. The different objectives are combined using dimensionless weights and a Pareto front can be determined by varying these weights. The mathematical model is demonstrated on an example problem with interesting results indicating how expansion decisions vary depending on whether minimizing cost or minimizing greenhouse gas emissions or pollutants is given higher priority.
KW - Generation expansion
KW - Generation planning
KW - Monte-Carlo simulation
KW - Multi-objective optimization
UR - http://www.scopus.com/inward/record.url?scp=77956341790&partnerID=8YFLogxK
U2 - 10.1016/j.epsr.2010.05.007
DO - 10.1016/j.epsr.2010.05.007
M3 - Article
AN - SCOPUS:77956341790
SN - 0378-7796
VL - 80
SP - 1394
EP - 1405
JO - Electric Power Systems Research
JF - Electric Power Systems Research
IS - 12
ER -