TY - JOUR
T1 - MAS-Based Modeling of Active Distribution Network
T2 - The Simulation of Emerging Behaviors
AU - Degefa, Merkebu Z.
AU - Alahäivälä, Antti
AU - Kilkki, Olli
AU - Humayun, Muhammad
AU - Seilonen, Ilkka
AU - Vyatkin, Valeriy
AU - Lehtonen, Matti
PY - 2016/11/1
Y1 - 2016/11/1
N2 - Agent-based modeling of active distribution network helps to understand the dynamics and to design the control strategies for overall system efficiency. There is, however, a lack of generic and multipurpose agent definitions in existing studies. In this paper, a multi-agent system-based modeling of an active distribution network is presented using cooperative agents. A method to solve a network-wise objective of state estimation is explained with the proposed model. The network component agents are defined to be cooperative to meet the overall objectives and greedy to fulfil individual objectives such as energy cost minimization. A token-ring protocol is deployed for the agent communication among themselves, as well as with market and network operator agents. Furthermore, a MATLAB/Simulink model of active distribution network is used to simulate the emerging stochastic loading scenario, while the autonomous prosumer agents optimize their total energy cost responding to market price variations.
AB - Agent-based modeling of active distribution network helps to understand the dynamics and to design the control strategies for overall system efficiency. There is, however, a lack of generic and multipurpose agent definitions in existing studies. In this paper, a multi-agent system-based modeling of an active distribution network is presented using cooperative agents. A method to solve a network-wise objective of state estimation is explained with the proposed model. The network component agents are defined to be cooperative to meet the overall objectives and greedy to fulfil individual objectives such as energy cost minimization. A token-ring protocol is deployed for the agent communication among themselves, as well as with market and network operator agents. Furthermore, a MATLAB/Simulink model of active distribution network is used to simulate the emerging stochastic loading scenario, while the autonomous prosumer agents optimize their total energy cost responding to market price variations.
KW - Demand response
KW - distributed power generation
KW - IEC 61968
KW - multi-agent systems
KW - power distribution
KW - state estimation
UR - http://www.scopus.com/inward/record.url?scp=84956865387&partnerID=8YFLogxK
U2 - 10.1109/TSG.2015.2510547
DO - 10.1109/TSG.2015.2510547
M3 - Article
AN - SCOPUS:84956865387
SN - 1949-3053
VL - 7
SP - 2615
EP - 2623
JO - IEEE TRANSACTIONS ON SMART GRID
JF - IEEE TRANSACTIONS ON SMART GRID
IS - 6
M1 - 7394195
ER -