TY - JOUR
T1 - Multi-Objective Hydrothermal Generation Scheduling and Fuel Dispatch Management considering Liquid Fuel Dispatch Network Modeling
AU - Lasemi, Mohammad Ali
AU - Assili, Mohsen
AU - Hajizadeh, Amin
PY - 2020/10
Y1 - 2020/10
N2 - Nowadays, to achieve sustainability and reliability in the electrical energy production sector, the utilization of flexible technologies, such as the power plants with multiple fuel options, and proper management of hydropower resources are substantial. In this paper, integrated scheduling for fuel dispatching and the generation planning of the power system comprising multi-fuel-fired thermal power plants and hydro units is presented considering a competitive environment of the fuel market. The main focus of this study is on the supply management of the primary energy sources including storable fuel and water resources for the generation of electrical power. The proposed model is given as a multi-objective optimization problem with different objective functions such as fuel consumption cost, fuel transportation cost, penalty cost of hydropower station disposable water, and valve point effect losses. The fuelling network limitations, including natural gas network as well as liquid fuel dispatch network constraints, and power system limitations, including power transmission and power generation constraints, are considered in the proposed model with the aim of achieving appropriate planning for simultaneous fuel dispatching and power generation scheduling. The problem is solved by the augmented e-constraint method and then an analytical hierarchy process technique is employed to select the best possible solution. Finally, the proposed algorithm is performed on the two test systems including the modified IEEE 30-bus system and IEEE 118-bus system integrated with a gas network and a fuelling network for liquid fuel. The obtained results demonstrate the effectiveness and benefits of the proposed scheme.
AB - Nowadays, to achieve sustainability and reliability in the electrical energy production sector, the utilization of flexible technologies, such as the power plants with multiple fuel options, and proper management of hydropower resources are substantial. In this paper, integrated scheduling for fuel dispatching and the generation planning of the power system comprising multi-fuel-fired thermal power plants and hydro units is presented considering a competitive environment of the fuel market. The main focus of this study is on the supply management of the primary energy sources including storable fuel and water resources for the generation of electrical power. The proposed model is given as a multi-objective optimization problem with different objective functions such as fuel consumption cost, fuel transportation cost, penalty cost of hydropower station disposable water, and valve point effect losses. The fuelling network limitations, including natural gas network as well as liquid fuel dispatch network constraints, and power system limitations, including power transmission and power generation constraints, are considered in the proposed model with the aim of achieving appropriate planning for simultaneous fuel dispatching and power generation scheduling. The problem is solved by the augmented e-constraint method and then an analytical hierarchy process technique is employed to select the best possible solution. Finally, the proposed algorithm is performed on the two test systems including the modified IEEE 30-bus system and IEEE 118-bus system integrated with a gas network and a fuelling network for liquid fuel. The obtained results demonstrate the effectiveness and benefits of the proposed scheme.
KW - fuel dispatch
KW - fuel market
KW - Hydrothermal scheduling
KW - multiple fuel options
KW - optimal power flow
KW - valve point effects
UR - http://www.scopus.com/inward/record.url?scp=85086075902&partnerID=8YFLogxK
U2 - 10.1016/j.epsr.2020.106436
DO - 10.1016/j.epsr.2020.106436
M3 - Journal article
AN - SCOPUS:85086075902
SN - 0378-7796
VL - 187
JO - Electric Power Systems Research
JF - Electric Power Systems Research
M1 - 106436
ER -