Fuzzy Portfolio Optimization of Onshore Wind Power Plants

Madlener, Reinhard; Glensk, Barbara; Weber, Veronika

doi:10.2139/ssrn.2353944

Cited by 81 publications

(2 citation statements)

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“…On the other hand, Shahzad et al introduced the concept of load concentration factor (LCF) to optimize the location of distributed generation, the proposed method simplifies the necessary calculations to minimize losses and adapt the stress profile [44]. The load concentration factor indicates the amount of load connected at a certain point in the power system.…”

Section: Models For the Design And Operation Of Distributed Generation And Microgridsmentioning

confidence: 99%

Complex Energy Conversion System Analysis: An Overview

Norouzi

Fani

2021

WJEEE

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This article describes the optimization models recently applied to the design and operation of power systems towards forming smart grids and identifies trends, barriers, and possible gaps in this area. Models are described to optimize the design and operation of power systems considering renewable energies, distributed generation, microgrids, demand management, and energy storage systems. It was concluded that it is necessary to validate many of the models formulated recently to optimize the operation through tests with real data and on a large scale. Furthermore, demand management and microgrids are aspects in which it is necessary to develop models for optimal power flow. Finally, it is necessary to predict stochastic variables with greater precision so that these models adapt to the real behavior of the system.

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Section: Models For the Design And Operation Of Distributed Generation And Microgridsmentioning

confidence: 99%

Complex Energy Conversion System Analysis: An Overview

Norouzi

Fani

2021

WJEEE

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“…Therefore, the portfolio selection model presented is convenient for different investors and their individual investment strategies. The application of this model for onshore wind power plants can be found in [43].…”

Section: Fuzzy Semi-mean-absolute Deviation (Fsmad) Modelmentioning

confidence: 99%

Fuzzy Portfolio Optimization of Power Generation Assets

Glensk

Madlener

2018

Energies

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Fuzzy theory is proposed as an alternative to the probabilistic approach for assessing portfolios of power plants, in order to capture the complex reality of decision-making processes. This paper presents different fuzzy portfolio selection models, where the rate of returns as well as the investor’s aspiration levels of portfolio return and risk are regarded as fuzzy variables. Furthermore, portfolio risk is defined as a downside risk, which is why a semi-mean-absolute deviation portfolio selection model is introduced. Finally, as an illustration, the models presented are applied to a selection of power generation mixes. The efficient portfolio results show that the fuzzy portfolio selection models with different definitions of membership functions as well as the semi-mean-absolute deviation model perform better than the standard mean-variance approach. Moreover, introducing membership functions for the description of investors’ aspiration levels for the expected return and risk shows how the knowledge of experts, and investors’ subjective opinions, can be better integrated in the decision-making process than with probabilistic approaches.

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