An Enhanced Security-Constrained Unit Commitment Model with Reserve Response Set Policies

Li, Nan; Singhal, Nikita; Hedman, Kory W.

doi:10.24251/hicss.2017.371

Cited by 5 publications

(3 citation statements)

References 13 publications

(24 reference statements)

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“…F. Guo et al [65] explored the potential of a distributed ED model for a smart grid system with random wind power. The proposed model works on the projected gradient and Finitetime Average Consensus Algorithm (FACA) and supports the plug-and-play feature of new generation smart grids.…”

Section: Economic Dispatchmentioning

confidence: 99%

“…This makes ED a highly complex optimization problem which needs to consider the various factors like generator capacity, ramp-rate, failure rate, emission, load profile and generation from DER. Unit Commitment (UC) in a smart grid system is a highly complex optimization problem that schedules the startup and shutdown of generators to meet the demand while satisfying system constraints [31,32]. The committed generators are modeled in the ED for generator scheduling.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Agent Systems for Resource Allocation and Scheduling in a Smart Grid

Nair

Hossen

Campion

et al. 2018

Technol Econ Smart Grids Sustain Energy

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With the increasing integration of Distributed Energy Resources (DER) in the power grid, a decentralized approach becomes essential for scheduling and allocation of resources in a smart grid. Economic Dispatch (ED) and Unit Commitment (UC) are the two major resource allocation problems that play critical role in the safe and stable operation of a grid system. The uncertainty associated with renewable energy sources have made the resource allocation problems even more challenging for grid operators. The future grid will have a higher generation mix of renewable energy sources and a large load of Electrical vehicles, with the possibility of bi-directional power flow. This complex smart grid system necessitates the development of a decentralized approach to resource allocation problem, which allows inter-node communication and decision making. Multi-agent systems (MAS) is a promising platform to decentralize the traditional centralized resource allocation aspects of smart grid. This paper presents a comprehensive literature review on the application of MAS to Economic Dispatch (ED) and Unit Commitment (UC) in smart grids.

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Section: Economic Dispatchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-Agent Systems for Resource Allocation and Scheduling in a Smart Grid

Nair

Hossen

Campion

et al. 2018

Technol Econ Smart Grids Sustain Energy

View full text Add to dashboard Cite

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“…In addition to cost minimisation, the unit commitment problem has been oriented towards particular objectives, such as finding an operating scheme subject to security restrictions [8][9][10], incorporating risk restrictions [11], considering reserve schemes [12][13][14][15], and considering day-ahead power dispatching [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Day‐ahead unit commitment for hydro‐thermal coordination with high participation of wind power

Zuluaga

Murillo-Sanchez

Moreno‐Chuquen

et al. 2022

IET Energy Syst Integration

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The variability and uncertainty of renewable resources impose new challenges in the operational planning related to the unit commitment of generation units. The development of day-ahead multi-period optimal power flow, under integration of wind power, requires modelling of multiple scenarios in order to ensure an optimal power flow minimising the generation cost. A progressive hedging approach has been proposed and developed to solve efficiently the unit commitment problem as a two-stage stochastic programming problem to update each stage in parallel. The performance of progressive hedging is compared with a standard mixed-integer linear programming problem. The results indicate that the computation time is 50 times faster than standard mixed-integer linear programming. The test case system is based on a reduced version of the interconnected Colombian system. The comparative results indicate an important reduction in computational time.

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