Portfolio Optimization of Power Generation Assets

Madlener, Reinhard

doi:10.1007/978-3-642-27431-2_12

Cited by 14 publications

(7 citation statements)

References 58 publications

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“…Additionally, today the efficiency and controllability of AC-DC and DC-AC converters have improved compared to previous times [18]. Thanks to the advantages that have been mentioned, HVDC systems are being used for the connection of offshore wind plants [19], since the inconveniences of AC transmission by underwater cable are reduced. Also, this type of transmission lines is being used for international connections and between networks of different characteristics in terms of frequency and voltage levels, since AC-DC converters with current technology allow to control the frequency of the system and adapt the level of voltage for energy exchange [18].…”

Section: Direct Current Transmissionmentioning

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: Direct Current Transmissionmentioning

confidence: 99%

Complex Energy Conversion System Analysis: An Overview

Norouzi

Fani

2021

WJEEE

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“…More specifically, they considered a two-dimensional optimization problem with fuel cost and risk minimization. More recent literature contains further applications of portfolio theory to energy markets in different countries or regions from a utility point of view (for a recent review, see [18]). For example, Awerbuch and Berger [19] used MVP analysis for the electricity market in the European Union.…”

Section: Applications Of Portfolio Analysis To Power Generation Assetsmentioning

confidence: 99%

“…They analyzed energy markets in the UK, and concluded that the optimal portfolio consists of natural-gas-combined cycle (NGCC) and a few nuclear power plants. Further applications of portfolio theory to the energy sector can be found in [18,21]. In [21], the cost approach was again applied and electricity production costs considered, which included fuel costs together with operating, capital, and external costs.…”

Section: Applications Of Portfolio Analysis To Power Generation Assetsmentioning

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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“…The literature on the subject contains examples of the use of optimization models in various economy areas. For example, Galanc et al (2016) used optimization models to support ICT decisions, Taghinezhad (2019) in food supply chain management, Madlener and Glensk (2013) in the energy industry to minimize costs and Maron and Maron (2019) on the financial market. In agricultural production, Juan et al (1999) optimized the use of available water for vegetable irrigation around Salvatierra (Spain).…”

Section: Introductionmentioning

confidence: 99%

Agricultural Production Planning Using a Multicriteria Optimization Model

Zaród¹

2020

ERSJ

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Purpose: This study aims to plan agricultural production on a real farm in Poland using an optimization model. Design/Methodology/Approach: Factors, especially variable ones (the weather, economic conditions), make it difficult to plan production on a farm. It is not uncommon for a decisionmaker to attempt at achieving several goals simultaneously. Solving such a problem is enabled by a linear-dynamic, multicriteria optimization model. In this study, the optimization criteria related to agricultural income are agricultural production, and organic matter losses in the soil. The empirical material consists of real data on a farm located in the West Pomeranian Voivodeship (Poland). Findings: The solution of a multicriteria, linear-dynamic model has indicated a production structure that ensures correct crop rotation, timely performance of agrotechnical works, and meets the conditions for receiving EU subsidies. It also allowed the highest agricultural income and the largest production under given conditions to be obtained. In contrast, a positive balance of organic matter shows that the environment is not degraded. Practical Implications: Linear-dynamic, multicriteria optimization models can be an effective tool supporting farm production planning. Originality/Value: The model applied for this paper's needs is of high application value. It can be used for crop cultivation farms or mixed production farms for determining alternative plans.

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Portfolio Optimization of Power Generation Assets

Cited by 14 publications

References 58 publications

Complex Energy Conversion System Analysis: An Overview

Complex Energy Conversion System Analysis: An Overview

Fuzzy Portfolio Optimization of Power Generation Assets

Agricultural Production Planning Using a Multicriteria Optimization Model

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