TY - JOUR
T1 - A multiagent modeling and investigation of smart homes with power generation, storage, and trading features
AU - Kahrobaee, Salman
AU - Rajabzadeh, Rasheed A.
AU - Soh, Leen Kiat
AU - Asgarpoor, Sohrab
PY - 2013
Y1 - 2013
N2 - Smart homes, as active participants in a smart grid, may no longer be modeled by passive load curves; because their interactive communication and bidirectional power flow within the smart grid affects demand, generation, and electricity rates. To consider such dynamic environmental properties, we use a multiagent-system-based approach in which individual homes are autonomous agents making rational decisions to buy, sell, or store electricity based on their present and expected future amount of load, generation, and storage, accounting for the benefits each decision can offer. In the proposed scheme, home agents prioritize their decisions based on the expected utilities they provide. Smart homes' intention to minimize their electricity bills is in line with the grid's aim to flatten the total demand curve. With a set of case studies and sensitivity analyses, we show how the overall performance of the home agents converges-as an emergent behavior-to an equilibrium benefiting both the entities in different operational conditions and determines the situations in which conventional homes would benefit from purchasing their own local generation-storage systems.
AB - Smart homes, as active participants in a smart grid, may no longer be modeled by passive load curves; because their interactive communication and bidirectional power flow within the smart grid affects demand, generation, and electricity rates. To consider such dynamic environmental properties, we use a multiagent-system-based approach in which individual homes are autonomous agents making rational decisions to buy, sell, or store electricity based on their present and expected future amount of load, generation, and storage, accounting for the benefits each decision can offer. In the proposed scheme, home agents prioritize their decisions based on the expected utilities they provide. Smart homes' intention to minimize their electricity bills is in line with the grid's aim to flatten the total demand curve. With a set of case studies and sensitivity analyses, we show how the overall performance of the home agents converges-as an emergent behavior-to an equilibrium benefiting both the entities in different operational conditions and determines the situations in which conventional homes would benefit from purchasing their own local generation-storage systems.
KW - Energy storage
KW - load management
KW - multiagent systems
KW - smart grids
KW - wind power generation
UR - http://www.scopus.com/inward/record.url?scp=84878269380&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84878269380&partnerID=8YFLogxK
U2 - 10.1109/TSG.2012.2215349
DO - 10.1109/TSG.2012.2215349
M3 - Article
AN - SCOPUS:84878269380
SN - 1949-3053
VL - 4
SP - 659
EP - 668
JO - IEEE Transactions on Smart Grid
JF - IEEE Transactions on Smart Grid
IS - 2
M1 - 6338331
ER -