TY - JOUR
T1 - Optimal planning of hybrid renewable energy system considering virtual energy storage of desalination plant based on mixed-integer NSGA-III
AU - Liu, Boyu
AU - Zhou, Bowen
AU - Yang, Dongsheng
AU - Li, Guangdi
AU - Cao, Jun
AU - Bu, Siqi
AU - Littler, Tim
N1 - Funding Information:
The authors acknowledge that this work is partially supported by the National Natural Science Foundation of China ( 61703081 ), the Fundamental Research Funds for the Central Universities ( N2004030 ), the Liaoning Revitalization Talents Program ( XLYC1801005 ), and the State Key Laboratory Of Alternate Electrical Power System With Renewable Energy Sources ( LAPS19005 ).
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - Due to the shortage of freshwater and energy crisis, seawater desalination with renewable energy has been proposed. A method for determining optimal planning of coastal hybrid renewable energy system (HRES) is proposed in this paper. Firstly, the system composition is introduced, and the virtual energy storage (VES) characteristics of the seawater reverse osmosis desalination plant is utilized to accommodate renewable energy generation. In order to reduce the system total cost, demand side management (DSM) measures are designed and applied to the regular electric load in the system. The methodology for planning optimization of the system is suggested, with objectives aiming at minimizing system total cost, end-user satisfaction loss caused by DSM, and tie-line power fluctuation. Since the problem has a mixed-integer manner, a modification of Non-dominated Sorting Genetic Algorithm-III (NSGA-III) is proposed. The newly-developed NSGA-III variant, named as MINSGA-III, is capable of solving mixed-integer optimization problem in an evolutionary algorithm fashion. This paper also presents several case studies to verify the feasibility and merits of the proposed method. The simulation results show that the proposed method is effective and feasible, and both DSM measures and VES approach have positive impact on the system modelling. The proposed MINSGA-III can effectively determine the solution of the multi-objective optimization problem.
AB - Due to the shortage of freshwater and energy crisis, seawater desalination with renewable energy has been proposed. A method for determining optimal planning of coastal hybrid renewable energy system (HRES) is proposed in this paper. Firstly, the system composition is introduced, and the virtual energy storage (VES) characteristics of the seawater reverse osmosis desalination plant is utilized to accommodate renewable energy generation. In order to reduce the system total cost, demand side management (DSM) measures are designed and applied to the regular electric load in the system. The methodology for planning optimization of the system is suggested, with objectives aiming at minimizing system total cost, end-user satisfaction loss caused by DSM, and tie-line power fluctuation. Since the problem has a mixed-integer manner, a modification of Non-dominated Sorting Genetic Algorithm-III (NSGA-III) is proposed. The newly-developed NSGA-III variant, named as MINSGA-III, is capable of solving mixed-integer optimization problem in an evolutionary algorithm fashion. This paper also presents several case studies to verify the feasibility and merits of the proposed method. The simulation results show that the proposed method is effective and feasible, and both DSM measures and VES approach have positive impact on the system modelling. The proposed MINSGA-III can effectively determine the solution of the multi-objective optimization problem.
KW - Demand side management
KW - Hybrid renewable energy system
KW - NSGA-III
KW - Reverse osmosis desalination
KW - Virtual energy storage
UR - http://www.scopus.com/inward/record.url?scp=85116568934&partnerID=8YFLogxK
U2 - 10.1016/j.desal.2021.115382
DO - 10.1016/j.desal.2021.115382
M3 - Journal article
AN - SCOPUS:85116568934
SN - 0011-9164
VL - 521
JO - Desalination
JF - Desalination
M1 - 115382
ER -
