Article citationsMore>>
Bintoudi, A., Zyglakis, L., Tsolakis, A., Ioannidis, D., Hadjidemetriou, L., Zacharia, L., Mutlaq, N., Hashem, M., Al-Agtash, S., Kyriakides, E., Demoulias, C. and Tzovaras, C. (2020) Hybrid Multi-Agent-Based Adaptive Control Scheme for AC Microgrids with Increased Fault-Tolerance Needs. IET Renewable Power Generation, 14, 1-6.
https://doi.org/10.1049/iet-rpg.2019.0468
has been cited by the following article:
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TITLE:
Agents for Smart Power Grids
AUTHORS:
Salem Al-Agtash, Hossam Abdel Hafez
KEYWORDS:
Agents, Electric Power System, Smart Power Grid
JOURNAL NAME:
Energy and Power Engineering,
Vol.12 No.8,
August
13,
2020
ABSTRACT: The
future of electricity systems will compose of small-scale generation and
distribution where end-users will be active participants with localized energy
management systems that are able to interact on a free energy market. Software
agents will most likely control power assets and interact together to decide
the best and safest configuration of the power grid system. This paper presents
a design of agents that can be deployed in real-time with capabilities that
include optimization of resources, intensive computation, and appropriate
decision-making. Jordan 51-bus system has been used for simulation with a total
generation capacity of 4050 MW of which 230 MW represents renewable energy. The
economic analyses demonstrated the use of smart grid technologies with 2016
generation—load profiles for nominal liquified gas (NLG)
prices and ±20% sensitivity
analysis. The results have shown variations in the range of 1% in the price of
MWh with smart grid technologies. These variations are mainly driven by the
fact that agents shift power generation to renewable power plants to produce
maximum power at peak hours. As a result, there is a positive economic impact
in both NLG ± 20% sensitivity analysis, due to the fact that
agents coordinate to better displace expensive thermal generation with
renewable generation. It is evident that renewable resources compensate for
power at peak times and provide economic benefits and savings.
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