35,112 research outputs found
A multi-agent model for assessing electricity tariffs
This paper describes the framework for modelling a multi-agent approach for assessing dynamic pricing of electricity and demand response. It combines and agent-based model with decision-making data, and a standard load-flow model. The multi-agent model described here represents a tool in investigating not only the relation between different dynamic tariffs and consumer load profiles, but also the change in behaviour and impact on low-voltage electricity distribution networks.The authors acknowledge the contribution of the EPSRC Transforming Energy Demand Through Digital Innovation Programme, grant agreement numbers EP/I000194/1 and EP/I000119/1, to the ADEPT project
Smart Grid Technologies in Europe: An Overview
The old electricity network infrastructure has proven to be inadequate, with respect to modern challenges such as alternative energy sources, electricity demand and energy saving policies. Moreover, Information and Communication Technologies (ICT) seem to have reached an adequate level of reliability and flexibility in order to support a new concept of electricity networkâthe smart grid. In this work, we will analyse the state-of-the-art of smart grids, in their technical, management, security, and optimization aspects. We will also provide a brief overview of the regulatory aspects involved in the development of a smart grid, mainly from the viewpoint of the European Unio
Agent based modeling of energy networks
Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows.
Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model.
But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required.
This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed
Recommended from our members
An Agent Based Simulation of Smart Metering Technology Adoption
Based on the classic behavioural theory âthe Theory of Planned Behaviourâ, we develop an agent-based model to simulate the diffusion of smart metering technology in the electricity market. We simulate the emergent adoption of smart metering technology under different management strategies and economic regulations. Our research results show that in terms of boosting the take-off of smart meters in the electricity market, choosing the initial users on a random and geographically dispersed basis and encouraging meter competition between energy suppliers can be two very effective strategies. We also observe an âS-curveâ diffusion of smart metering technology and a âlock-inâ effect in the model. The research results provide us with insights as to effective policies and strategies for the roll-out of smart metering technology in the electricity market
Consensus-based approach to peer-to-peer electricity markets with product differentiation
With the sustained deployment of distributed generation capacities and the
more proactive role of consumers, power systems and their operation are
drifting away from a conventional top-down hierarchical structure. Electricity
market structures, however, have not yet embraced that evolution. Respecting
the high-dimensional, distributed and dynamic nature of modern power systems
would translate to designing peer-to-peer markets or, at least, to using such
an underlying decentralized structure to enable a bottom-up approach to future
electricity markets. A peer-to-peer market structure based on a Multi-Bilateral
Economic Dispatch (MBED) formulation is introduced, allowing for
multi-bilateral trading with product differentiation, for instance based on
consumer preferences. A Relaxed Consensus+Innovation (RCI) approach is
described to solve the MBED in fully decentralized manner. A set of realistic
case studies and their analysis allow us showing that such peer-to-peer market
structures can effectively yield market outcomes that are different from
centralized market structures and optimal in terms of respecting consumers
preferences while maximizing social welfare. Additionally, the RCI solving
approach allows for a fully decentralized market clearing which converges with
a negligible optimality gap, with a limited amount of information being shared.Comment: Accepted for publication in IEEE Transactions on Power System
- âŠ