Robust multi-objective optimization of a renewable based hybrid power system

Roberts, Justo J.; Cassula, Agnelo Marotta; Silveira, José Luz; Bortoni, Edson C.; Mendiburu, Andrés Z.

doi:10.1016/j.apenergy.2018.04.032

Cited by 88 publications

(62 citation statements)

References 45 publications

(58 reference statements)

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“…For the same optimization problem, this number of generations is much more important for RO than for NRO. So, as Roberts et al [20] remarked, when the computational resources or time are limited, other approaches can be better adapted.…”

Section: Discussion: Respective Contributions Of the Two Approachesmentioning

confidence: 99%

“…For both approaches applied to the sizing of renewable power energy systems, the whole set of uncertain parameters is often not taken into account and the analysis of uncertainty is classically reduced to the assessment of time series [20,21]. In addition, models of uncertainties are often very basic [6,10].…”

Section: Description Of Methods For Uncertainty Analysismentioning

confidence: 99%

“…Itwas first proposed by Cantoni et al[40] and further investigated by Marseguerra et al[41]. Recently, Roberts et al[20] used it to optimize a renewable based hybrid power system considering as uncertain the time series (renewable productions and load) and the components availability. In[20], the optimization criteria are based on the worst performance indicator (worst case observed in one sample), while in our paper one of the optimization criteria measures the variability of one performance indicator during the optimization itself.…”

mentioning

confidence: 99%

“…Recently, Roberts et al[20] used it to optimize a renewable based hybrid power system considering as uncertain the time series (renewable productions and load) and the components availability. In[20], the optimization criteria are based on the worst performance indicator (worst case observed in one sample), while in our paper one of the optimization criteria measures the variability of one performance indicator during the optimization itself. The added value of this method, in comparison to the classical genetic algorithm, is the improvement of the calculation of the optimization criteria.…”

mentioning

confidence: 99%

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Section: Discussion: Respective Contributions Of the Two Approachesmentioning

confidence: 99%

Section: Description Of Methods For Uncertainty Analysismentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Accounting for techno-economic parameters uncertainties for robust design of remote microgrid

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“…Abdelaziz and Moradzadeh presented a parallelized implementation of NSGA-II using OpenCL to solve the multi-objective renewable DG planning problem, where the IEEE 32-bus test system and two real distribution test systems were used as test examples [15]. Roberts et al proposed a probabilistic simulation-based multi-objective optimization approach for dimensioning robust renewable based Hybrid Power Systems, where a rural community of the Amazonian region of Brazil was used as a test example [16]. Ebrahimzadeh et al presented a multi-objective optimization procedure based on the genetic algorithm to decide optimum design of power converter current controllers in power electronics-based systems, where a 400-MW wind farm with 100-MW aggregated strings was used as a test example [17].…”

Section: Introductionmentioning

confidence: 99%

Application of Ordinal Optimization to Reactive Volt-Ampere Sources Planning Problems

2019

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Reactive volt-ampere sources planning is an effort to determine the most effective investment plan for new reactive sources at given load buses while ensuring appropriate voltage profile and satisfying operational constraints. Optimization of reactive volt-ampere sources planning is not only a difficult problem in power systems, but also a large-dimension constrained optimization problem. In this paper, an ordinal optimization-based approach containing upper and lower level is developed to solve this problem efficiently. In the upper level, an ordinal search (OS) algorithm is utilized to select excellent designs from a candidate-design set according to the system’s structural information exploited from the simulations executed in the lower level. There are five stages in the ordinal search algorithm, which gradually narrow the design space to search for a good capacitor placement pattern. The IEEE 118-bus and IEEE 244-bus systems with four load cases are employed as the test examples. The proposed approach is compared with two competing methods; the genetic algorithm and Tabu search, and a commercial numerical libraries (NL) mixed integer programming tool; IMSL Numerical Libraries. Experimental results illustrate that the proposed approach yields an outstanding design with a higher quality and efficiency for solving reactive volt-ampere sources planning problem.

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A Pareto optimum approach and a power management strategy for a stand‐alone wind turbine‐PV‐hydrogen with reformer hybrid renewable energy system

Tezer

Yaman

2021

Env Prog and Sustain Energy

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In this study, a multi‐objective and constrained optimization problem is discussed. The SAHRESOpt (multi‐objective and constrained optimization algorithm for SA‐HRES) which includes size optimization and minimization of the loss of power supply probability was developed based on non‐dominated sorting genetic algorithm‐II (NSGA‐II). Additionally, a power management strategy was designed to ensure that the power flow between the system elements minimizes the unmet load and/or the excess energy. In this context, with the aim of obtaining uninterrupted hydrogen energy in the system, a reformer was used transforming methane gas produced by an anaerobic reactor into hydrogen. Thus, a stand‐alone hybrid renewable energy system (SA‐HRES) that does not generate CO2 emissions was designed. Furthermore, within the scope of size optimization, both the types of system elements and the numbers of them were optimized. Then, the positive effects of reformer existence on both of the objective functions, and also the effects of considering the waste energy percentage as a constraint are presented. Also, Pareto solutions of SAHRESOpt and NSGA‐II are compared. Finally, a case study including photovoltaic panels, wind turbines, fuel cells, electrolyzers, hydrogen tanks, and a reformer is presented to prove the effectiveness of the presented algorithm and validate the results.

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Robust multi-objective optimization of a renewable based hybrid power system

Cited by 88 publications

References 45 publications

Accounting for techno-economic parameters uncertainties for robust design of remote microgrid

Accounting for techno-economic parameters uncertainties for robust design of remote microgrid

Application of Ordinal Optimization to Reactive Volt-Ampere Sources Planning Problems

A Pareto optimum approach and a power management strategy for a stand‐alone wind turbine‐PV‐hydrogen with reformer hybrid renewable energy system

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