Simulation of the energy efficiency auction prices in Brazil

11/09/2018
by   Javier L. L. Gonzales, et al.
0

The electricity consumption behavior in Brazil has been extensively investigated over the years due to financial and social problems. In this context, it is important to simulate the energy prices of the energy efficiency auctions in the Brazilian regulated environment. This paper presents an approach to generate samples of auction energy prices in energy efficiency market, using Markov chain Monte Carlo method, through the Metropolis-Hastings algorithm. The obtained results show that this approach can be used to generate energy price samples.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/27/2023

A flow-based ascending auction to compute buyer-optimal Walrasian prices

We consider a market where a set of objects is sold to a set of buyers, ...
research
04/23/2019

Power Consumption and Energy-Efficiency for In-Band Full-Duplex Wireless Systems

This paper presents an analytical model of power consumption for In-Band...
research
05/05/2022

Utility-Based Context-Aware Multi-Agent Recommendation System for Energy Efficiency in Residential Buildings

A significant part of CO2 emissions is due to high electricity consumpti...
research
03/13/2023

The Evaluation of a New Daylighting System's Energy Performance: Reversible Daylighting System (RDS)

This paper evaluates the energy performance of a new daylighting system,...
research
07/07/2020

An Entropy Equation for Energy

This paper describes an entropy equation, but one that should be used fo...
research
06/29/2011

Use of Markov Chains to Design an Agent Bidding Strategy for Continuous Double Auctions

As computational agents are developed for increasingly complicated e-com...
research
02/19/2023

Energy Efficient Homes: The Social and Spatial Patterns of Residential Energy Efficiency in England

Poor energy efficiency of homes is a major problem with urgent environme...

Please sign up or login with your details

Forgot password? Click here to reset