TY - JOUR
T1 - The energy management strategy of two-by-one combined cycle gas turbine based on dynamic programming
AU - Lu, Nianci
AU - Pan, Lei
AU - Cui, Guomin
AU - Pedersen, Simon
AU - Shivaie, Mojtaba
AU - Arabkoohsar, Ahmad
PY - 2024/12/30
Y1 - 2024/12/30
N2 - The complexity and nonlinearity of components in large-scale thermal facilities have resulted in a lack of recognized energy management models, and simple rule-based energy management strategies are still the main approach, which reduces their operating efficiency. In this study, a dynamic programming (DP) method for globally optimal power distribution and operation mode decision for two-by-one combined cycle gas turbine is proposed. First, the energy management model of system is established. Then the drum pressure of the heat recovery steam generator, which indicates the thermal energy storage of the system, is chosen as the state variable, while the control variables are the gas turbine power, turbine power and operation mode. In addition, the system response time is considered to re-evaluated the mode switch command. The simulation results show that the DP optimizes the thermal storage management, which allows the gas turbine to run in the high-efficiency operating range for a longer time. The DP-based strategy saves 6.25 %, 5.89 %, and 4.92 % of fuel at initial drum pressure 8 MPa, 9 MPa, and 10 MPa, respectively, compared to the rule-based strategy. The results of this study can be used as a benchmark to evaluate online energy management strategies in future work.
AB - The complexity and nonlinearity of components in large-scale thermal facilities have resulted in a lack of recognized energy management models, and simple rule-based energy management strategies are still the main approach, which reduces their operating efficiency. In this study, a dynamic programming (DP) method for globally optimal power distribution and operation mode decision for two-by-one combined cycle gas turbine is proposed. First, the energy management model of system is established. Then the drum pressure of the heat recovery steam generator, which indicates the thermal energy storage of the system, is chosen as the state variable, while the control variables are the gas turbine power, turbine power and operation mode. In addition, the system response time is considered to re-evaluated the mode switch command. The simulation results show that the DP optimizes the thermal storage management, which allows the gas turbine to run in the high-efficiency operating range for a longer time. The DP-based strategy saves 6.25 %, 5.89 %, and 4.92 % of fuel at initial drum pressure 8 MPa, 9 MPa, and 10 MPa, respectively, compared to the rule-based strategy. The results of this study can be used as a benchmark to evaluate online energy management strategies in future work.
KW - Dynamic programming, Energy management strategy, Globally optimal power distribution, Operation mode decision, Thermal storage management
KW - Energy management strategy
KW - Globally optimal power distribution
KW - Operation mode decision
KW - Thermal storage management
KW - Dynamic programming
KW - Energy management strategy
KW - Globally optimal power distribution
KW - Operation mode decision
KW - Thermal storage management
UR - https://www.sciencedirect.com/science/article/pii/S0360544224038611
UR - http://www.scopus.com/inward/record.url?scp=85211084774&partnerID=8YFLogxK
U2 - 10.1016/j.energy.2024.134083
DO - 10.1016/j.energy.2024.134083
M3 - Journal article
SN - 0360-5442
VL - 313
JO - Energy
JF - Energy
M1 - 134083
ER -