A Sequential Linear Programming algorithm for economic optimization of Hybrid Renewable Energy Systems

Vaccari, Marco; Mancuso, G; Riccardi, Juri; Cantù, Matteo; Pannocchia, Gabriele

doi:10.1016/j.jprocont.2017.08.015

Cited by 45 publications

(25 citation statements)

References 28 publications

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“…The first is including a feasible region and feasible initial guess. The latter is the phase that the objective is optimized for nonempty feasible region [53]. The sequence of feasible iterates X k can be computed according to the equation below.…”

Section: Interior-point Methodsmentioning

confidence: 99%

Optimization Study of Hydraulic Power Take-off System for an Ocean Wave Energy Converter

Amini¹,

Mehdipour²,

Faraggiana³

et al. 2021

Preprint

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Ocean wave renewable energy is fast becoming a key part of renewable energy industries over the recent decades. By developing wave energy converters as the main converter technology in this process, their power take-off (PTO) systems have been investigated. Adjusting PTO parameters is a challenging optimization problem because there is a complex and nonlinear relationship between these parameters and the absorbed power output. In this regard, this study aims to optimize the PTO system parameters of a point absorber wave energy converter in the wave scenario in Perth, on Western Australian coasts. The converter is numerically designed to oscillate against irregular and multidimensional waves and a sensitivity analysis for PTO settings is performed. Then, to find the optimal PTO system parameters which lead to the highest power output, ten optimization algorithms are incorporated to solve the non-linear problem, Including Nelder-Mead search method, Active-set method, Sequential quadratic Programming method (SQP), Multi-Verse Optimizer (MVO), and six modified combination of Genetic, Surrogate and fminsearch algorithms. After a feasibility landscape analysis, the optimization outcome is carried out and gives us the best answer in terms of PTO system settings. Finally, the investigation shows that the modified combinations of Genetic, Surrogate, and fminsearch algorithms can outperform the others in the studied wave scenario, as well as the interaction between PTO system variables.

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Section: Interior-point Methodsmentioning

confidence: 99%

Optimization Study of Hydraulic Power Take-off System for an Ocean Wave Energy Converter

Amini¹,

Mehdipour²,

Faraggiana³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…A search space is established by setting the initial points and moving limits. And a linear programming method, e.g., an interior point method, is used to complete the search process [28,29]. Specifically, if the intersection of the search space and the linearized feasible solution space is empty, the search space needs to be expanded by increasing the moving limits.…”

Section: Ubmentioning

confidence: 99%

Slope Sliding Force Prediction via Belief Rule-Based Inferential Methodology

Feng¹,

Xu²,

Liu³

et al. 2021

IJCIS

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Slope sliding force can be measured by an anchor cable sensor with the negative Poisson's ratio (NPR) property. It is capable of reflecting the stability of the slope intuitively. Thus, predicting the variation trend of the sliding force is able to achieve early warning for landslide disaster, thereby avoiding losses to the lives and property of the people. In this paper, due to the uncertain variation of the sliding force, a belief rule-based (BRB) sliding force prediction model is established to describe the nonlinear and uncertain relationship between the history/current sliding force and the future sliding force. In this model, the activated belief rules are fused by adopting the evidence reasoning (ER) algorithm. And based on the fused results, the sliding force at a future time can be predicted accurately. Moreover, considering the variation of the sliding force on different slopes or different monitoring points in the same slope, a parameter transfer strategy of BRB model together with a corresponding online update method are proposed to achieve the adaptive design of the BRB prediction model. Finally, the effectiveness of the proposed sliding force prediction methods has been verified by experiments on the sub-section of the China West-East Gas Pipeline Project.

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“…Zhen et al [23] designed a fuzzy mixed integer programming method to support the planning of energy systems management and air pollution mitigation control under multiple uncertainties. Vaccari et al [24] developed an optimization tool for a general hybrid renewable energy system to generate an operating plan to meet electrical and thermal load requirements with possibly minimum operating costs plan over a specified time horizon.…”

Section: Scheduling Approachesmentioning

confidence: 99%

Energy Management of a Multi-Source Power System

2021

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This work focuses on energy management for a system operated by multiple energy sources which include batteries, super capacitors, a hydrogen fuel cell, and a photovoltaic cell. The overall objective is to minimize the power consumption from all sources needed to satisfy the system’s power demand by optimizing the switching between the different energy sources. A dynamic mathematical model representing the energy sources is developed taking into account the different constraints on the system, i.e., primarily the state-of-charge of the battery and the super capacitors. In addition to the model, a heuristic approach is developed and compared with the mathematical model. Both approaches were tested on a multi-energy source ground robot as a prototype. The novelty of this work is that the scheduling of an energy system consisting of four different types of sources is compared by performing analysis via dynamic programming, and a heuristic approach. The results generated using both methods are analyzed and compared to a standard mode of operation. The comparison validated that the proposed approaches minimize the average power consumption across all sources. The dynamic modeling approach performs well in terms of optimization and provided a superior switching sequence, while the heuristic approach offers the definite advantages in terms of ease of implementation and simple computation requirements. Additionally, the switching sequence provided by the dynamic approach was able to meet the power demand for all simulations performed and showed that the average power consumption across all sources is minimized.

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A Sequential Linear Programming algorithm for economic optimization of Hybrid Renewable Energy Systems

Cited by 45 publications

References 28 publications

Optimization Study of Hydraulic Power Take-off System for an Ocean Wave Energy Converter

Optimization Study of Hydraulic Power Take-off System for an Ocean Wave Energy Converter

Slope Sliding Force Prediction via Belief Rule-Based Inferential Methodology

Energy Management of a Multi-Source Power System

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