Fuzzy logic home energy consumption modeling for residential photovoltaic plant sizing in the new Italian scenario

Ciabattoni, Lucio; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro

doi:10.1016/j.energy.2014.06.100

Cited by 58 publications

(30 citation statements)

References 20 publications

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“…Assuming an energy selling prize with incentives-for example, 240 €/MWh-the breakeven time falls to five years. This incentivized prize is supposed, considering that this value is very lower than incentivized prizes used in Italy for photovoltaic panels during the first years of the mechanism "Conto Energia" [43].…”

Section: Economic Assessmentmentioning

confidence: 92%

Energetic Sustainability Using Renewable Energies in the Mediterranean Sea

2016

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Abstract:The paper is focused on the analysis of the electrical energy sector in the Maltese islands, focusing on the employment of Renewable Energies in order to increase its energy independence. The main renewable source here proposed is wave energy: thanks to its strategic position, Malta will be able to generate electrical energy through the use of an innovative type of Wave Energy Converter (WEC) based on the prototype of linear generator designed and developed by the University of Palermo. This new technology will be able to cut down the electrical energy production from traditional power plants and, consequently, the greenhouse gas emissions (GHG). Wave energy source and off-shore photovoltaic (PV) technology are proposed here. Particularly, the installation of 18 wave farms, for a total installed capacity of 130 MW, will generate about 5.7% of Malta's energy requests in 2025, while the installation of 60 MW of off-shore PV will generate about 4.4%.

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Section: Economic Assessmentmentioning

confidence: 92%

Energetic Sustainability Using Renewable Energies in the Mediterranean Sea

2016

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“…Ciabattoni et al [39] and Ciabattoni et al [40] presented a high-resolution model of domestic electricity use. The model is based on a fuzzy logic inference system.…”

Section: Fuzzy Benefit-cost Analysismentioning

confidence: 99%

A Comparison of Wind Energy Investment Alternatives Using Interval-Valued Intuitionistic Fuzzy Benefit/Cost Analysis

2016

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Abstract:One of the tools for maintaining environmental sustainability is transformation from fossil-based energy sources to renewable energy sources in energy consumption. Among renewable energy alternatives, wind energy is the most prominent and reliable energy source for fulfilling energy demand. Traditional investment evaluation techniques based on discounted cash flows are not capable of capturing the uncertainty and vagueness in the data related to the wind energy investment parameters. Fuzzy capital budgeting techniques can capture this vagueness and model the imprecise estimations of parameter values. In this paper, we develop interval-valued intuitionistic fuzzy benefit-cost analysis for the evaluation of wind energy technology investments. The fuzzy benefit-cost analyses are based on both present worth and annual worth analyses. The developed analyses can handle the assessments of multiple experts through aggregation operators. In the proposed economic model, the components of each wind energy investment parameter are incorporated into the equations in detail. A real case study is also presented in this paper.

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“…Although households energy management is widely recognized 7 as a priority to reach an overall cost-saving by PV generation systems, nowadays consumers'load during the day is still particularly high in the evening 8 , while the quota of energy consumed in the morning and/or in the afternoon is still quite low. Then, having normalized the energy demand to one, by …xing the production quota used for selfconsumption is endogenously determined once the plant size 1 is chosen 9 . Active households energy management may increase , this in turn may induce investors to install greater size plants.…”

Section: Assumptionmentioning

confidence: 99%

“…8 According to the analysis performed by the Italian National Authority for Electricity, Gas and Water Services (AEEGSI) in 2009, the higher peak load demanded by residential users occurs in the evening, between 8:00 p.m. and 10:00 p.m. (AEEGSI, 2009). 9 Many technical reports and contributions in the literature show that this quota ranges between 30% and 50%. See as an example Ciabattoni et al (2014), Kastel and Gilroy-Scott (2015).…”

Section: Assumptionmentioning

confidence: 99%

Investing in Photovoltaics: Timing, Plant Sizing and Smart Grids Flexibility

2016

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In Italy and in many EU countries, the last decade was characterized by a large development of distributed generation power plants. Their presence determined new critical issues for the design and management of the overall energy system and the electric grid due to the presence of discontinuous production sources. It is commonly agreed that contingent problems that a¤ect local grids (e.g. ine¢ ciency, congestion rents, power outages, etc.) may be solved by the implementation of a "smarter" electric grid.The main feature of smarts grid is the great increase in production and consumption ‡exi-bility. Smart grids give producers and consumers, the opportunity to be active in the market and strategically decide their optimal production/consumption scheme. The paper provides a theoretical framework to model the prosumer's decision to invest in a photovoltaic power plant, assuming it is integrated in a smart grid. To capture the value of managerial ‡exibility, a real option approach is implemented. We calibrate and test the model by using data from the Italian energy market. JEL: Q42; C61; D81

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Fuzzy logic home energy consumption modeling for residential photovoltaic plant sizing in the new Italian scenario

Cited by 58 publications

References 20 publications

Energetic Sustainability Using Renewable Energies in the Mediterranean Sea

Energetic Sustainability Using Renewable Energies in the Mediterranean Sea

A Comparison of Wind Energy Investment Alternatives Using Interval-Valued Intuitionistic Fuzzy Benefit/Cost Analysis

Investing in Photovoltaics: Timing, Plant Sizing and Smart Grids Flexibility

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