Simulation-based optimization methods for renewable energy applications

2022 ◽  
pp. 343-372
Author(s):  
Yun Peng ◽  
Xiangda Li
SIMULATION ◽  
2020 ◽  
Vol 96 (10) ◽  
pp. 791-806
Author(s):  
Milad Yousefi ◽  
Moslem Yousefi ◽  
Flavio S Fogliatto

Since high performance is essential to the functioning of emergency departments (EDs), they must constantly pursue sensible and empirically testable improvements. In light of recent advances in computer science, an increasing number of simulation-based approaches for studying and implementing ED performance optimizations have become available in the literature. This paper aims to offer a survey of these works, presenting progress made on the topic while indicating possible pitfalls and difficulties in EDs. With that in mind, this review considers research studies reporting simulation-based optimization experiments published between 2007 and 2019, covering 38 studies. This paper provides bibliographic background on issues covered, generates statistics on methods and tools applied, and indicates major trends in the field of simulation-based optimization. This review contributes to the state of the art on ED modeling by offering an updated picture of the present state of the field, as well as promising research gaps. In general, this review argues that future studies should focus on increasing the efficiency of multi-objective optimization problems by decreasing their cost in time and labor.


Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2236
Author(s):  
Hsien-Pin Hsu ◽  
Chia-Nan Wang ◽  
Hsin-Pin Fu ◽  
Thanh-Tuan Dang

The joint scheduling of quay cranes (QCs), yard cranes (YCs), and yard trucks (YTs) is critical to achieving good overall performance for a container terminal. However, there are only a few such integrated studies. Especially, those who have taken the vessel stowage plan (VSP) into consideration are very rare. The VSP is a plan assigning each container a stowage position in a vessel. It affects the QC operations directly and considerably. Neglecting this plan will cause problems when loading/unloading containers into/from a ship or even congest the YT and YC operations in the upstream. In this research, a framework of simulation-based optimization methods have been proposed firstly. Then, four kinds of heuristics/metaheuristics has been employed in this framework, such as sort-by-bay (SBB), genetic algorithm (GA), particle swarm optimization (PSO), and multiple groups particle swarm optimization (MGPSO), to deal with the yard crane scheduling problem (YCSP), yard truck scheduling problem (YTSP), and quay crane scheduling problem (QCSP) simultaneously for export containers, taking operational constraints into consideration. The objective aims to minimize makespan. Each of the simulation-based optimization methods includes three components, load-balancing heuristic, sequencing method, and simulation model. Experiments have been conducted to investigate the effectiveness of different simulation-based optimization methods. The results show that the MGPSO outperforms the others.


2021 ◽  
Vol 10 (4) ◽  
pp. 667-686
Author(s):  
Akinola Sunday Oladeji ◽  
Mudathir Funsho Akorede ◽  
Salihu Aliyu ◽  
Abdulrasaq Apalando Mohammed ◽  
Adebayo Wahab Salami

There is a need to develop an optimization tool that can be applied in the feasibility study of a hybrid renewable energy system to find the optimal capacity of different renewable energy resources and support the decision makers in their performance investigation. A multi-objective function which minimizes the Levelized Cost of Energy (LCOE) and Loss of Load Probability Index (LLPI) but maximizes the novel Energy Match Ratio (EMR) was formulated. Simulation-based optimization method combined with ε-constraint technique was developed to solve the multi-objective optimization problem. In the study, ten-year hourly electrical load demand, using the end-use model, is estimated for the communities. The performance of the developed algorithm was evaluated and validated using Hybrid Optimization Model for Electric Renewables (HOMER®) optimization software. The developed algorithm minimized the LCOE by 6.27% and LLPI by 167% when compared with the values of LCOE ($0.444/kWh) and LLPI (0.000880) obtained from the HOMER® optimization tool. Also, the LCOE with the proposed approach was calculated at $0.417/kWh, which is lower than the $0.444/kWh obtained from HOMER®. From environmental perspective, it is found that while 141,370.66 kg of CO2 is saved in the base year, 183,206.51 kg of CO2 is saved in the ninth year.The study concluded that the approach is computationally efficient and performed better than HOMER® for this particular problem.The proposed approach could be adopted for carrying out feasibility studies and design of HRES for Off-Grid electrification, especially in the rural areas where access to the grid electricity is limited


Author(s):  
Akinola Sunday Oladeji ◽  
Mudathir Funsho Akorede ◽  
Salihu Aliyu ◽  
Abdulrasaq Apalando Mohammed ◽  
Adebayo Wahab Salami

There is a need to develop an optimization tool that can be applied in the feasibility study of a hybrid renewable energy system to find the optimal capacity of different renewable energy resources and support the decision makers in their performance investigation. A multi-objective function which minimizes the Levelized Cost of Energy (LCOE) and Loss of Load Probability Index (LLPI) but maximizes the novel Energy Match Ratio (EMR) was formulated. Simulation-based optimization method combined with ε-constraint technique was developed to solve the multi-objective optimization problem. In the study, ten-year hourly electrical load demand, using the end-use model, is estimated for the communities. The performance of the developed algorithm was evaluated and validated using Hybrid Optimization Model for Electric Renewables (HOMER®) optimization software. The developed algorithm minimized the LCOE by 6.27% and LLPI by 167% when compared with the values of LCOE ($0.444/kWh) and LLPI (0.000880) obtained from the HOMER® optimization tool. Also, the LCOE with the proposed approach was calculated at $0.417/kWh, which is lower than the $0.444/kWh obtained from HOMER®. From environmental perspective, it is found that while 141,370.66 kg of CO2 is saved in the base year, 183,206.51 kg of CO2 is saved in the ninth year.The study concluded that the approach is computationally efficient and performed better than HOMER® for this particular problem.The proposed approach could be adopted for carrying out feasibility studies and design of HRES for Off-Grid electrification, especially in the rural areas where access to the grid electricity is limited


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