21 Result(s)
within
Simona-Vasilica Oprea
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Article
From the East-European Regional Day-Ahead Markets to a Global Electricity Market
The so-called black swans, COVID-19 and the invasion in Ukraine, have led to an unprecedented increase in electricity prices. Since 2021, after lockdowns, the electricity price has started to increase due to e...
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Article
Open AccessAnomaly Detection in Weather Phenomena: News and Numerical Data-Driven Insights into the Climate Change in Romania’s Historical Regions
The extreme phenomena have been increased recently in frequency and intensity causing numerous damage that cannot be neglected by residents, local authorities and social media. More European countries are expe...
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Article
Electricity price forecast on day-ahead market for mid- and short terms: capturing spikes in data sequences using recurrent neural network techniques
This paper aims to forecast the electricity prices in the day-ahead market (DAM) with complex recurrent neural networks (RNNs), which are powerful in predicting the sequential prices with lags of unknown durat...
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Article
Open AccessMachine Learning Algorithms for Power System Sign Classification and a Multivariate Stacked LSTM Model for Predicting the Electricity Imbalance Volume
The energy transition to a cleaner environment has been a concern for many researchers and policy makers, as well as communities and non-governmental organizations. The effects of climate change are evident, t...
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Article
Open AccessInsights into Bitcoin and energy nexus. A Bitcoin price prediction in bull and bear markets using a complex meta model and SQL analytical functions
Cryptocurrencies are in the center of attention of investors, public authorities and researchers, but the interest has shifted from purely financial aspects regarding the way of trading, lack of regulation and...
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Article
On-grid and off-grid photovoltaic systems forecasting using a hybrid meta-learning method
In this paper, we investigate two types of photovoltaic (PV) systems (on-grid and off-grid) of different sizes and propose a reliable PV forecasting method. The novelty of our research consists in a weather da...
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Article
Open AccessExploring excitement counterbalanced by concerns towards AI technology using a descriptive-prescriptive data processing method
Given the current pace of technological advancement and its pervasive impact on society, understanding public sentiment is essential. The usage of AI in social media, facial recognition, and driverless cars ha...
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Article
Is Bitcoin ready to be a widespread payment method? Using price volatility and setting strategies for merchants
Bitcoin has gradually gained acceptance as a payment method that, unlike electronic payments in dollars or euros, passes through the international trading system with zero or lower fees. Moreover, Bitcoin and ...
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Article
Open AccessPredicting Day-Ahead Electricity Market Prices through the Integration of Macroeconomic Factors and Machine Learning Techniques
Several events in the last years changed to some extent the common understanding of the electricity day-ahead market (DAM). The shape of the electricity price curve has been altered as some factors that underp...
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Chapter and Conference Paper
Impact of Electronic Cash Registers on Tax Collection
This paper explores the impact of Electronic Cash Registers (ECRs) on tax collection and aims to provide an overview of the implementation of Electronic Fiscal Devices (EFDs) in Romania, describing the legal f...
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Article
Intelligent system to optimally trade at the interference of multiple crises
In this paper, we aim to create an intelligent system to predict the wholesale market prices and provide the input variables for producers to optimally approach the electricity Day-Ahead Market (DAM) and Balan...
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Article
Open AccessForecasting the Spot Market Electricity Price with a Long Short-Term Memory Model Architecture in a Disruptive Economic and Geopolitical Context
In this paper, we perform a short-run Electricity Price Forecast (EPF) with a Recurrent Neural Network (RNN), namely Long Short-Term Memory (LSTM), using an algorithm that selects the variables and optimizes t...
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Article
An Edge-Fog-Cloud computing architecture for IoT and smart metering data
Smart Metering (SM) systems allow frequent and accurate consumption readings that can be the source of multiple applications, generating new business in the future. However, it imposes interesting challenges f...
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Chapter and Conference Paper
Sustainable Communities with Smart Meters. A Statistical Measurement Model to Cope with Electricity Consumers’ Behavior
The mentality of electricity consumers is one of the most important entities that needs to be addressed when co** with balancing issues in operating the power systems. Consumers are used to being completely ...
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Article
Open AccessFeature engineering solution with structured query language analytic functions in detecting electricity frauds using machine learning
Detecting fraud related to electricity consumption is usually a difficult challenge as the input datasets are sometimes unreliable due to missing and inconsistent records, faults, misinterpretation of meter re...
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Chapter and Conference Paper
Alerts and Fraud Detection in Electricity Consumption Recorded by Smart Metering Systems
The fraud detection in electricity consumption represents a challenge as they produce significant financial losses for utility companies. The detection strategy could be also costly because the classification ...
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Chapter and Conference Paper
Multi-Processing Data Analysis for the Residential Load Flexibility in Smart Cities
Residential consumption is gaining an increasing focus regarding assessing their flexibility and load control. Flexibility potential of smart cities becomes significant as the uncertainties of the power system...
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Article
Optimizing the Electricity Consumption with a High Degree of Flexibility Using a Dynamic Tariff and Stackelberg Game
Recent advancements in the sensor industry, smart metering systems and communication technology have led to interesting electricity consumption optimization opportunities that contribute to both peak reduction...
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Chapter and Conference Paper
Edge Computing in Real-Time Electricity Consumption Optimization Algorithm for Smart Grids
Nowadays the electricity consumption optimization represents a big improvement point for the electricity supplier, but also for the consumers. Both sides can benefit from the progress of sensors and ICT techno...
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Article
Open AccessA three-stage approach for resilience-constrained scheduling of networked microgrids
This paper deals with optimal scheduling of networked microgrids (NMGs) considering resilience constraints. The proposed scheme attempts to mitigate the damaging impacts of electricity interruptions by effecti...
