Parallel PI/CDM Frequency Controller to Support V2G Plan for Microgrid

Qudaih, Yaser; Moukhtar, Ibrahim; Mohamed, Tarek Hassan; Elbaset, Adel A.; Dein, Adel Z. El; Mitani, Yasunori

doi:10.1016/j.egypro.2016.10.187

Cited by 9 publications

(7 citation statements)

References 11 publications

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“…microgrids or islands (defined as a small grid network that can operate independently of a larger national grid), and cost reduction via renewable energy storage and arbitrage [37]. For example, several sources found that introducing V2G to a microgrid would decrease the cost of operation, reduce reliance on the outside grid and increase utilization of wind and solar [38,39]. A study of the Canary Islands found that assuming a certain threshold of V2G usage in tandem with pumped hydro storage reduced energy dependence while also increasing renewable share of load and reducing carbon emissions [40].…”

Section: Renewable Energy Storage and Integrationmentioning

confidence: 99%

The neglected social dimensions to a vehicle-to-grid (V2G) transition: a critical and systematic review

Sovacool

Noel

Axsen

et al. 2018

Environ. Res. Lett.

183

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Vehicle-to-grid (V2G) refers to efforts to bi-directionally link the electric power system and the transportation system in ways that can improve the sustainability and security of both. A transition to V2G could enable vehicles to simultaneously improve the efficiency (and profitability) of electricity grids, reduce greenhouse gas emissions for transport, accommodate low-carbon sources of energy, and reap cost savings for owners, drivers, and other users. To understand the recent state of this field of research, here we conduct a systematic review of 197 peer-reviewed articles published on V2G from 2015 to early 2017. We find that the majority of V2G studies in that time period focus on technical aspects of V2G, notably renewable energy storage, batteries, or load balancing to minimize electricity costs, in some cases including environmental goals as constraints. A much lower proportion of studies focus on the importance of assessing environmental and climate attributes of a V2G transition, or on the role of consumer acceptance and knowledge of V2G systems. Further, there is need for exploratory work on natural resource use and externalities, discourses and narratives as well as social justice, gender, and urban resilience considerations. These research gaps need to be addressed if V2G is to achieve the societal transition its advocates seek.

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Section: Renewable Energy Storage and Integrationmentioning

confidence: 99%

The neglected social dimensions to a vehicle-to-grid (V2G) transition: a critical and systematic review

Sovacool

Noel

Axsen

et al. 2018

Environ. Res. Lett.

183

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show abstract

“…In this phase, learners improve their knowledge by interacting among themselves. Select two learners in the (10) describes how the learners transfer their knowledge between each other. Where X 0 total A ;i is the total fitness value of the learner in all subjects.…”

Section: Learners Phasementioning

confidence: 99%

“…During the last decade, the PHEVs are being considered by several authors for their proposed load frequency control (LFC) studies with various controllers [7][8][9][10][11][12][13][14][15][16][17][18][19]. In [7] authors suggested a conventional PI/ PID controller, in [8] an adaptive control method, in [9] authors proposed a robust PI controller, in [10] a coefficient diagram method, in [11] a generalized model predictive controller (MPC), in [12] with H ∞ controller, etc. In [13][14][15][16][17] the authors proposed various optimization techniques for secondary LFC with PHEVs.…”

Section: Introductionmentioning

confidence: 99%

Robust frequency control in a renewable penetrated power system: an adaptive fractional order-fuzzy approach

Annamraju

Nandiraju

2019

Prot Control Mod Power Syst

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Purpose: Load frequency control (LFC) in today's modern power system is getting complex, due to intermittency in the output power of renewable energy sources along with substantial changes in the system parameters and loads. To address this problem, this paper proposes an adaptive fractional order (FO)-fuzzy-PID controller for LFC of a renewable penetrated power system. Design/methodology/approach: To examine the performance of the proposed adaptive FO-fuzzy-PID controller, four different types of controllers that includes optimal proportional-integral-derivative (PID) controller, optimal fractional order (FO)-PID controller, optimal fuzzy PID controller, optimal FO-fuzzy PID controller are compared with the proposed approach. The dynamic response of the system relies upon the parameters of these controllers, which are optimized by using teaching-learning based optimization (TLBO) algorithm. The simulations are carried out using MATLAB/SIMULINK software. Findings: The simulation outcomes reveal the supremacy of the proposed approach in dynamic performance improvement (in terms of settling time, overshoot and error reduction) over other controllers in the literature under different scenarios. Originality/value: In this paper, an adaptive FO-fuzzy-PID controller is proposed for LFC of a renewable penetrated power system. The main contribution of this work is, a maiden application has been made to tune all the possible parameters of fuzzy controller and FO-PID controller simultaneously to handle the uncertainties caused by renewable sources, load and parametric variations.

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“…The governors of the thermal and hydro turbine are no longer sufficient to compensate these fluctuations of power and frequency due to their slow response. The smart charging of PHEV presents many challenges to overcome this problem [5][6][7][8][9][10]. When a sudden power change due to load variation and fluctuations of RES is occurred, the action of traditional power system control is slow.…”

Section: Power System Overviewmentioning

confidence: 99%

“…Furthermore, the PHEVs will be used extensively in consumer side for driving because of low-cost charging, reduced petroleum usages, and reduced greenhouse emissions [4]. PHEV is equipped with various control methods of load frequency control (LFC) such as a conventional proportionalintegral (PI) controller [5,6], a robust PI controller [7], an adaptive control [8], a fuzzy control [9], a coefficient diagram method [10], and a model predictive control (MPC) [11][12][13][14]. In [11], the weights of MPC for PHEV controller are found by a particle swarm optimisation (PSO).…”

Section: Introductionmentioning

confidence: 99%

Model predictive control of plug‐in hybrid electric vehicles for frequency regulation in a smart grid

Elsisi

Soliman

Aboelela

et al. 2017

IET Generation, Transmission & Distribution

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Parallel PI/CDM Frequency Controller to Support V2G Plan for Microgrid

Cited by 9 publications

References 11 publications

The neglected social dimensions to a vehicle-to-grid (V2G) transition: a critical and systematic review

The neglected social dimensions to a vehicle-to-grid (V2G) transition: a critical and systematic review

Robust frequency control in a renewable penetrated power system: an adaptive fractional order-fuzzy approach

Model predictive control of plug‐in hybrid electric vehicles for frequency regulation in a smart grid

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