Model of monthly electricity consumption of healthcare buildings based on climatological variables using PCA and linear regression

Pérez-Montalvo, Ernesto; Zapata-Velásquez, Manuel-Eduardo; Benítez-Vázquez, Laura-María; Cermeño-González, Juan-Manuel; Alejandro-Miranda, Jose; Martínez-Cabero, Miguel-Ángel; Puente-Gil, Álvaro de la

doi:10.1016/j.egyr.2022.06.117

Cited by 20 publications

(5 citation statements)

References 19 publications

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“…. ] (b) collected for specified, explicit and legitimate purposes and not further processed in a manner that is incompatible with those purposes; further processing for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes shall, in accordance with Article 89 (1), not be considered to be incompatible with the initial purposes ('purpose limitation'); (c) adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed ('data minimization') [ . .…”

Section: Principles Rights and Obligationsmentioning

confidence: 99%

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Blockchain, Data Protection and P2P Energy Trading: A Review on Legal and Economic Challenges

Chiarini¹,

Compagnucci

2022

Sustainability

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Blockchain technology (BCT) enables the automated execution of smart contracts in peer-to-peer (P2P) energy trading. BCT-based P2P platforms allow the sharing, exchange and trade of energy among consumers or prosumers as peers, fostering the decarbonization, decentralization and digitalization of the energy industry. On the other hand, BCT-based P2P energy trading relies on the collection, storage and processing of a large amount of user data, posing interdisciplinary challenges, including user anonymity, privacy, the governance of BCT systems and the role of energy market players. First, this paper seeks to review the state of the art of European data protection law and regulations by focusing on BCT compliance with the General Data Protection Regulation (GDPR) of 2018. Second, it explores both the potentials and the challenges of BCT-based P2P energy trading from a legal–economic perspective. To do so, the paper adopts an interdisciplinary approach which intertwines both law and economics, by reviewing the recent literature on BCT and P2P energy trading. Findings have revealed that the deployment of BCT-based P2P energy trading is still in its pilot stage because of technology immaturity, data protection uncertainty, incomplete disintermediation and the lack of both user awareness and collaboration among market players. Drawing on the review, the paper also proposes a selection of solutions to foster the implementation of BCT-based P2P energy trading.

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Section: Principles Rights and Obligationsmentioning

confidence: 99%

“…The Member States (MSs) of the European Union (EU) are committed to fostering a sustainable and decarbonized energy system. The EU aims at reducing greenhouse gas emissions by at least 55% by 2030, compared to 1990 [1]. Within this framework, buildings account for 43% of final energy consumption [2].…”

Section: Introductionmentioning

confidence: 99%

Blockchain, Data Protection and P2P Energy Trading: A Review on Legal and Economic Challenges

Chiarini¹,

Compagnucci

2022

Sustainability

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“…In [104], the importance of smart meters is clarified regarding the possibility of the early detection of electricity consumption abnormalities. Additionally, cost calculation and assess the viability of centralized energy procurement and inspection.…”

Section: Imentioning

confidence: 99%

A Review of Electricity Tariffs and Enabling Solutions for Optimal Energy Management

Zaki

Hamdy

2022

Energies

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Today, electricity tariffs play an essential role in the electricity retail market as they are the key factor for the decision-making of end-users. Additionally, tariffs are necessary for increasing competition in the electricity market. They have a great impact on load energy management. Moreover, tariffs are not taken as a fixed approach to expense calculations only but are influenced by many other factors, such as electricity generation, transmission, distribution costs, and governmental taxation. Thus, electricity pricing differs significantly between countries or between regions within a country. Improper tariff calculation methodologies in some areas have led to high-power losses, unnecessary investments, increased operational expenses, and environmental pollution due to the non-use of available sustainable energy resources. Due to the importance of electricity tariffs, the authors of this paper have been inspired to review all electricity tariff designs used worldwide. In this paper, 103 references from the last ten years are reviewed, showing a detailed comparison between different tariff designs and demonstrating their main advantages and drawbacks. Additionally, this paper reviews the utilized electricity tariffs in different countries, focusing on one of the most important countries in the Middle East and North Africa regions (Egypt). Finally, some recommended solutions based upon the carried-out research are discussed and applied to the case study for electricity tariff improvement in this region. This review paper can help researchers become aware of all the electricity tariff designs used in various countries, which can lead to their design improvements by using suitable software technologies. Additionally, it will increase end-users’ awareness in terms of deciding on the best electricity retail markets as well as optimizing their energy usage.

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“…For example, Feng et al [6] combined the PCA dimension reduction method and logistic regression method to predict pneumonia data in medicine, while Xu et al [7] used PCA and deep forest regression [8] to predict dioxin emission concentration. Montalvo et al [9] used PCA and linear regression to predict the monthly electricity consumption of healthcare buildings, and Perera et al [10] used PCA and partial least square regression (PLS-R) combined with ATR-FTIR spectroscopy to study the concentration-dependent curcumin interaction with serum biomolecules. However, this kind of method regards each observation time point as a one-dimensional variable and does not take into account the intrinsic function characteristic information of time series data.…”

Section: Introductionmentioning

confidence: 99%

A time series data regression based on a B-spline and stacking framework

Li,

Cui,

2024

J. Phys.: Conf. Ser.

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This paper proposes a new time series regression method based on the combination of B-spline basis expansion and distance covariance weighted model. This paper considers the case that the predictor variable is a time series and the response variable is a continuous scalar. In order to solve these problems of high dimension and high noise of time series, this proposed method uses a B-spline basis to reduce the dimension and extract the function information of the original sequence. Considering that there is still some noise in the reduced dimension random variables, this proposed method considers using the stacking framework to enhance the data. Since the importance of each basis model is unknown, this paper uses the distance covariance to measure the importance of the basis model and develop a weighted stacking framework, which can adaptively weigh the bias and variance of the predictor model. In addition, each basis estimator in ensemble learning is model-free. The real data analysis shows that the proposed method is competitive with some existing methods. Finally, the proposed method can be directly applied to other fields such as environmental science, medical science and speech recognition et al.

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Model of monthly electricity consumption of healthcare buildings based on climatological variables using PCA and linear regression

Cited by 20 publications

References 19 publications

Blockchain, Data Protection and P2P Energy Trading: A Review on Legal and Economic Challenges

Blockchain, Data Protection and P2P Energy Trading: A Review on Legal and Economic Challenges

A Review of Electricity Tariffs and Enabling Solutions for Optimal Energy Management

A time series data regression based on a B-spline and stacking framework

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