دانلود رایگان ترجمه مقاله سیستم چند عاملی برای مدیریت انرژی مشارکتی در ریزشبکه ها (نشریه IEEE 2016)

سیستم چند عاملی برای مدیریت انرژی مشارکتی در ریزشبکه ها

Multi Agent System for cooperative energy management in microgrids

Abstract

In the last years the microgrid are emerged as the key component able to increase the efficiency, reliability, and sustainability of traditional electrical infrastructures. Micro distribution systems aggregate small, modular renewable power source, distributed storage and local loads as autonomous entities that can exchange power with the traditional electricity if operating in connected mode. A prime task in microgrid operation is the dynamic balance of local supply and power demand due to the intermittent nature of renewable energy resource and the variability of load demand during the day. However the power transfer among each microgrid and the main grid is always associated with a cost due to the loss of power over the distribution line. In this paper, a multi-agent systems (MAS) for the optimal coordination of multiple distributed energy resources is presented. The agents, associated with each microgrid, implement a cooperative strategy to minimise the power loss over the distribution lines and to maximise the economic income by sharing the surplus of the generated power between the microgrids belonging to the same coalition. The simulation results show the effectiveness of the proposed control strategy demonstrating that the MGs payoff increases up to 30% when microgrids cooperate to gain the power balance.

I. BACKGROUND

The smart grids are the evolution of the traditional power grid in a complex and more interconnected cyber-physical system, which optimizes asset utilization and improves power quality operating resiliently against system disturbances and faults [1]-[3]. These challenges need the development of:

– advanced monitoring and communication systems to collect data for timely decision making;

– renewable energy sources, located at a distribution level, to defer the construction of new plants and transmission lines;

– distributed artificial intelligence systems for demand management and control of energy bills.

With respect to these goals, microgrids are emerged as a potential way to supply customer and critical loads with the energy locally produced offering considerable control capabilities [4]. In fact, microgrids are defined as complex systems at LV or MV distribution network comprising small power generators, energy conversion devices, intelligent static control switches and confined cluster of loads. The microgrids generally work as controlled single entities within the traditional electricity grid and can operate as a small source of power or an aggregated load according to the required local power needs. Clearly, microgrids require smart control architectures to manage the uncertainty of renewable power generation and the hourly fluctuations of energy demand with high reliability and cost effectiveness.

This paper discusses the development of a Multi-Agent System (MAS) for the control and dispatch of the power flows within a district of the distribution network including N microgrids linked to the primary substation of a public utility grid. The microgrids (MG) agents interact each-other to find the optimal feeder reconfiguration that allows to redistribute locally the energy surplus of the microgrids, minimizing the burden on the main grid and the technical losses [5] in a cost effective way.

The logic control of the MG agents is designed to implement a TU-cooperative game enabling the formation of coalitions between microgrids to achieve the power balance. This approach allows the primary advantage to distribute decision making capabilities facilitating dynamic demand response. Moreover, the asynchronous operation of the agents and the distributed energy management allow microgrids to easily leave or enter each coalition as conditions permit. This leads to an improvement of the overall reliability of the distribution network, an increment of resiliency to faults and accelerate service restoration.

The proposed MAS for cooperative energy management is simulated using the middleware JADE (Java agent development Environment) by TILAB (Telecom Italy Lab) for the development of distributed multi-agent applications based on peer-to-peer communication architectures [6]. This middleware allows distributing the intelligence, the initiative and the control on different terminals in order to implement the parallel interactions between peers (called agents) with different behaviours in compliance with the FIPA (Foundation for Intelligent Physical Agents) standards [7] [8]. JADE enables the communications between the agents both in wireless or wireline networks allowing the exchange of asynchronous messages.

Results from simulation studies show the effectiveness of the approach followed in designing the proposed MAS for the cooperative distributed power management of the microgrids located in the same geographical area of a smart grid. The rest of the work is organized as follows. The second section briefly presents the model for the distribution network, the MAS components and the control strategy based on a TU game. The third section describes the study environment and the main experimental results. The fourth section is devoted to conclusions.