Search results for "energy market"

A Reinforcement Learning Approach for User Preference-aware Energy Sharing Systems

2021

Energy Sharing Systems (ESS) are envisioned to be the future of power systems. In these systems, consumers equipped with renewable energy generation capabilities are able to participate in an energy market to sell their energy. This paper proposes an ESS that, differently from previous works, takes into account the consumers’ preference, engagement, and bounded rationality. The problem of maximizing the energy exchange while considering such user modeling is formulated and shown to be NP-Hard. To learn the user behavior, two heuristics are proposed: 1) a Reinforcement Learning-based algorithm, which provides a bounded regret and 2) a more computationally efficient heuristic, named BPT- ${K}…

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.

Real-time pricing for aggregates energy resources in the Italian energy market

2015

Abstract Over the last decade, the architecture of the energy market has radically changed. In many countries end-users are now able to directly access the market, which has given rise to the question of how they can actively participate in that market. End-users can comprise a critical mass through aggregation that is carried out by a third party – to wit the “loads aggregator.” This paper proposes a new framework for generating feasible real-time price curves for those end-users in a demand-response management process. The underlying algorithm generates output curves as the solution to a constrained optimization problem whose objective function is the aggregator's economic benefit. A case…

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…

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…

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

2017

The Energy Market Impact of Climate Change on Electricity Generation in Europe

2018

In this paper, the policy trend in Europe towards the emission reduction target in the energy sector, as planned from the Paris Agreement, is analyzed. Although renewable energy sources are improving their share, the large use of coal as primary fuel and the uncertainty about nuclear production makes the transition hard. It's well known that future emission patterns from energy generation influence the climate change trend, but as shown in the following, there is also a reverse interrelation, due to the different environmental conditions caused by climate change affecting all generation technologies. Furthermore, energy prices, which derive from this changed framework likewise will influenc…

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…

A new formulation of the optimal compensation and reconfiguration problem including minimum load nodes unavailability for automated distribution netw…

2004

This paper deals with a new formulation of the optimal operation of electrical distribution networks problem in regular working state. In the new deregulated energy market providing reliable and economical service to customers is a primary task. The multiobjective formulation of the reconfiguration and compensation problem used in this paper considers as a primary object also the minimisation of the load nodes unavailability (UA) expressed in probabilistic terms. Therefore, the objectives to be attained through the optimisation strategy are: minimal power losses operation, minimum UA of the load nodes, load balancing among the HV/MV transformers, and voltage profile regularisation. The appl…

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…