Name
Title | ||
|---|---|---|
Intelligent decision making for energy management in microgrids with air pollution reduction policy |
Abstract | ||
|---|---|---|
Fuzzy Logic-based decision-making framework is implemented for energy management in microgrid systems in order to meet targets such as providing local consumers with required energy demand and making good revenue for the microgrid owner under a time-varying electricity cost policy while helping reduce negative environmental effects due to air polluting sources of electrical energy such as coal fire plants which operate in the main grid in order to provide local microgrid loads. Typically, a microgrid system has two modes of operation. It either works synchronously with the main grid or operates independently from the utility grid in an isolated mode. Distributed renewable energy generators including solar, wind in association with batteries and main grid supply power to the consumer in the microgrid network. One day period is divided to a finite number of time slots. The Fuzzy intelligent approach implemented in this article determines the rate at which power has to be delivered to/taken from the storage unit during the next time slot depending on the electricity price per kWh of energy, local load demand, electricity generation rate through renewable resources, and air pollution factor which are sampled at predetermined rates. Cost function is defined as the sum of balance/revenue due to electricity trade between microgrid and the main grid, which includes the power provided to local load and distribution losses. Five different scenarios are considered for local load and microgrid assembly operation. Measures of balance/revenue will be extracted to represent benefits of using Fuzzy logic for energy management in microgrids with air pollution reduction policy. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/SYSoSE.2012.6384132 | System of Systems Engineering |
Keywords | Field | DocType |
air pollution control,decision making,distributed power generation,energy measurement,environmental factors,fuzzy logic,power system management,renewable energy sources,air polluting sources,air pollution factor,air pollution reduction policy,coal fire plants,distributed renewable energy generators,distribution losses,electrical energy,electricity generation,energy demand,energy management,fuzzy intelligent,fuzzy logic-based decision-making framework,intelligent decision making,local consumers,local load demand,local microgrid loads,main grid,microgrid systems,microgrids,renewable resources,storage unit,time-varying electricity cost policy,utility grid,Intelligent Fuzzy Decision-Making,Microgrid Network,Power Flow Analysis,Time-Varying Electricity cost | Stand-alone power system,Energy management,Renewable energy,Grid parity,Control engineering,Distributed generation,Engineering,Microgrid,Electricity generation,Wind power | Conference |
ISBN | Citations | PageRank |
978-1-4673-2974-3 | 0 | 0.34 |
References | Authors | |
1 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Manjili, Y.S. | 1 | 1 | 1.05 |
| Amir Rajaee | 2 | 0 | 0.34 |
| Mo M. Jamshidi | 3 | 0 | 0.34 |
| Brian Todd Kelley | 4 | 0 | 0.34 |