Search results for "Energy market"

Regulating blockchain for sustainability? The critical relationship between digital innovation, regulation, and electricity governance

2021

Abstract Blockchain technology has found several innovative applications in the electricity industry. However, its potential has still to be discovered. This is partly due to the role that regulation plays in electricity markets. To be introduced, experimented with, and eventually adopted on a commercial scale, blockchain-supported innovations need to fit the existing regulatory framework or the rules to be reshaped or updated. We focus on energy regulators' possible responses to the blockchain-enhanced market operations (both from the incumbents and potential newcomers), suggesting a monitoring mechanism that can support innovation.

Humanities and Social Sciences Latvia. Vol. 25, N. 1 (Spring-Summer 2017)

2017

Efficiency optimization in bi-directional inductive power transfer systems

2015

Inductive Power Transfer (IPT) allows to wirelessly supply electronic devices. Thus, it is a very smart technique of battery charging for electric vehicles. In a parking area scenario, IPT is a proper method aiming at the energy transfer from the vehicle battery to the electric grid too. Bi-Directional Inductive Power Transfer (BDIPT) Systems are an attractive solution for the automotive market. Due to the great relevance of the energy saving problem, the goal of an efficiency maximization is researched by the energy market. In this paper, an in-depth investigation of the power efficiency in BDIPT systems is carried out, aiming at the optimum efficiency.

Challenges and directions for Blockchain technology applied to Demand Response and Vehicle-to-Grid scenarios

2021

Abstract Nowadays, Blockchain is considered a consolidated technology supporting many different applications that integrate well with Artificial Intelligence and the Internet of Things, and supports the creation of Decentralized Autonomous Organizations. Within this wider framework, the energy blockchain applications are now deserving more and more attention, since blockchain architectures, on one hand, provide transparency and solve the information asymmetry problem, on the other, provide disintermediation. In this way, the dream of an energy market closer to end-users becomes a reality, although, still, the regulatory framework is not clear, especially for what concerns the tokenization o…

Day-ahead forecasting for photovoltaic power using artificial neural networks ensembles

2016

Solar photovoltaic plants power output forecasting using machine learning techniques can be of a great advantage to energy producers when they are implemented with day-ahead energy market data. In this work a model was developed using a supervised learning algorithm of multilayer perceptron feedforward artificial neural network to predict the next twenty-four hours (day-ahead) power of a solar facility using fetched weather forecast of the following day. Each set of tested network configuration was trained by the historical power output of the plant as a target. For each configuration, one hundred networks ensembles was averaged to give the ability to generalize a better forecast. The train…

Energy market segmentation for distributed energy resources implementation purposes

2007

The new power market scene has made its actors aware of the importance of offering customers a set of products according to their specific needs. At the same time, a desirable massive deployment of distributed energy resources would require that the products be designed for specific purposes for each type of customer. For these reasons, it is essential to identify the energy behaviour of different customer segments existing in the electricity market. This paper presents a segmentation methodology that allows the identification of different types of customers in accordance with their energy use. This segmentation is conceptually different from the one that is currently performed by the utili…

Novel Energy Modelling and Forecasting Tools for Smart Energy Networks

2015

A novel Energy Modelling and Forecasting Tool (EMFT) has been adopted for use in the VIM SEN (Virtual Microgrids for Smart Energy Networks) project and this paper gives an insight of the techniques used to provide vital support to the energy market, in particular to energy aggregators. A brief description of one of the test sites where data has been collected for validation of the EMFT will be outlined and some examples shown. The information and predictions will then be used by a decision support system to dynamically adjust energy delivery and consumption, by giving advice to users and operators on actions they can take to obtain a better match between energy supply and demand that increa…

A New Platform for Automatic Bottom-Up Electric Load Aggregation

2017

In this paper, a new virtual framework for load aggregation in the context of the liberalized energy market is proposed. Since aggregation is managed automatically through a dedicated platform, the purchase of energy can be carried out without intermediation as it happens in peer-to-peer energy transaction models. Differently from what was done before, in this new framework, individual customers can join a load aggregation program through the proposed aggregation platform. Through the platform, their features are evaluated and they are clustered according to their reliability and to the width of range of regulation allowed. The simulations show the deployment of an effective clustering and …

Blockchain for power systems:Current trends and future applications

2020

Abstract Today, the blockchain is synonymous of technological innovation, being recognized among the 10 top strategy technologies in 2018 by the consulting company Gartner, it is more and more adopted in different sectors. However, the initial enthusiasm around this technology is going beyond the peak of inflated expectations, towards more stable applications in money transactions, cryptocurrencies and Digital Commodity Exchanges. Essentially, misguided efforts, the overuse of blockchain, and the Bitcoin's price drop have been the main reasons for this decay in expectations. Nevertheless, the exploitation of the blockchain technology in the power systems area appears largely underexplored, …

Time and frequency dynamics of connectedness between renewable energy stocks and crude oil prices

2018

Abstract This paper examines the time and frequency dynamics of connectedness among stock prices of U.S. clean energy companies, crude oil prices and a number of key financial variables using the methodology developed by Barunik and Krehlik (2018). This approach allows measuring the dynamics of return and volatility connectedness over time and across frequencies simultaneously. The empirical results show that most of return and volatility connectedness is generated in the very short-term, i.e. movements up to five days, while the long-term plays a minor role. Our analysis further reveals a greater degree of interconnectedness across crude oil and financial markets since the onset of the U.S…