Optimum control strategies for short term load forecasting in smart grids

M Ali, M Adnan, M Tariq - International journal of electrical power & Energy …, 2019 - Elsevier
International journal of electrical power & Energy systems, 2019Elsevier
Nonlinearity in load profile and variations in demand due to error margin in short term load
forecasting cause power network overloading. The state of a power system is more severe
when a fault occurs in the power system network that leads to overloading. Analyzing the
effect due to these disturbances on power system network is an important feature of this
work. This paper proposes a control algorithm that focuses on sophisticated fuzzy logic
approach. Advanced fuzzy control takes overloading and variation in demand profile as …
Abstract
Nonlinearity in load profile and variations in demand due to error margin in short term load forecasting cause power network overloading. The state of a power system is more severe when a fault occurs in the power system network that leads to overloading. Analyzing the effect due to these disturbances on power system network is an important feature of this work. This paper proposes a control algorithm that focuses on sophisticated fuzzy logic approach. Advanced fuzzy control takes overloading and variation in demand profile as input, which mitigate these disturbances by incorporating optimal power dispatch of renewable energy resources (RERs). To show the effectiveness and validity of the proposed model and fuzzy control design, 9 Bus test system of the transmission network is adopted. Not only normal mode but fault and overloading modes are used to verify the proposed approach. Competitiveness of the proposed control design in terms of reliability and optimal utilization of RERs are verified through simulation results.
Elsevier
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