Real Time Operation of Smart Grids via FCN Networks and Optimal Power Flow

Siano, Pierluigi; Cecati, Carlo; Yu, Hao; Kolbusz, Janusz

doi:10.1109/tii.2012.2205391

Cited by 198 publications

(77 citation statements)

References 51 publications

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“…The validity of the reduced model was demonstrated in [8], where both the reduced and complete models were compared, showing similar responses, but with a considerable reduction of the computational time for the first one. Several control strategies for FC vehicles [2]- [5] were evaluated by using this reduced model.…”

Section: Hydrogen Subsystemmentioning

confidence: 93%

Energy Management System Control for a Hybrid Non-conventional Energy Sources using Hysteresis Switching Algorithm

Devi¹,

Saravanapriyan²

2015

IJAREEIE

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Renewable energy sources play an important role in electrical energy generation. The drawbacks of Renewable energy sources have been overcome by the use of hybrid power generating unit. A typical hybrid renewable energy system (HRES) combines several renewable energy sources such as wind turbine (WT) and photovoltaic (PV) panels as primary energy sources and an energy storage system (ESS) based on fuel cell and battery. All of the energy sources are connected together to a central dc bus by means of power converters. This paper includes a supervisory control called hysteresis switching algorithm which determines the power that must be generated by/stored in the fuel cell and battery, taking into account the control demand by the grid, the offered power, the hydrogen reservoir point and the state-of-charge (SOC) of the battery. The proposed EMS is compared with classical EMS composed of state based supervisory control system based on states and inverter control system based on PI controller. Dynamic simulation results of the proposed EMS demonstrate the better performance than the classical EMS.

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Section: Hydrogen Subsystemmentioning

confidence: 93%

Energy Management System Control for a Hybrid Non-conventional Energy Sources using Hysteresis Switching Algorithm

Devi¹,

Saravanapriyan²

2015

IJAREEIE

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“…The forecasted wind power profiles for one day are taken from [31] and shown as the red-dashed curves in Figure 7b,c. The actual wind power P w.A (n w , m) for the two WSs are generated at each 20 s using the Beta distribution with the shape parameters α(n w ) and β(n w ) corresponding to the forecasted wind power, where σ w (n w ) = 0.1 pu = 1 MW based on Equations (7) and (8). The resulting curves for the two WSs are shown in Figure 7b, The active d P and reactive d Q power demand are assumed to follow the hourly IEEE-RTS fall season's days [49].…”

Section: Test Casesmentioning

confidence: 99%

A Framework for Real-Time Optimal Power Flow under Wind Energy Penetration

Mohagheghi

Gabash

2017

Energies

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Developing a suitable framework for real-time optimal power flow (RT-OPF) is of utmost importance for ensuring both optimality and feasibility in the operation of energy distribution networks (DNs) under intermittent wind energy penetration. The most challenging issue thereby is that a large-scale complex optimization problem has to be solved in real-time. Online simultaneous optimization of the wind power curtailments of wind stations and the discrete reference values of the slack bus voltage which leads to a mixed-integer nonlinear programming (MINLP) problem, in addition to considering variable reverse power flow, make the optimization problem even much more complicated. To address these difficulties, a two-phase solution approach to RT-OPF is proposed in this paper. In the prediction phase, a number of MINLP OPF problems corresponding to the most probable scenarios of the wind energy penetration in the prediction horizon, by taking its forecasted value and stochastic distribution into account, are solved in parallel. The solution provides a lookup table for optional control strategies for the current prediction horizon which is further divided into a certain number of short time intervals. In the realization phase, one of the control strategies is selected from the lookup table based on the actual wind power and realized to the grid in the current time interval, which will proceed from one interval to the next, till the end of the current prediction horizon. Then, the prediction phase for the next prediction horizon will be activated. A 41-bus medium-voltage DN is taken as a case study to demonstrate the proposed RT-OPF approach.

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“…The Z-BGW performs meter reading collection 500 times and so the average ALLs have been recorded for each testing networks (1)(2)(3)(4)(5). Later, these experimental results were compared with the average ALL 500 simulation results for 3-4 in order to study the impact of the number of interfaces (k) on the BN performance of MIZBAN.…”

Section: B Backbone Network (Vertical Communication)mentioning

confidence: 99%

The Generic Design of a High-Traffic Advanced Metering Infrastructure Using ZigBee

Tung

Tsang

Chui

et al. 2014

IEEE Trans. Ind. Inf.

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Abstract-A multi-interface ZigBee building area network (MIZBAN) for a high-traffic advanced metering infrastructure (AMI) for high-rise buildings was developed. This supports meter management functions such as Demand Response for smart grid applications. To cater for the high-traffic communication in these building area networks (BANs), a multi-interface management framework was defined and designed to coordinate the operation between multiple interfaces based on a newly defined tree-based mesh (T-Mesh) ZigBee topology, which supports both mesh and tree routing in a single network. To evaluate MIZBAN, an experiment was set up in a five-floor building. Based on the measured data, simulations were performed to extend the analysis to a 23-floor building. These revealed that MIZBAN yields an improvement in application-layer latency of the backbone and the floor network by 75% and 67%, respectively. This paper provides the design engineer with seven recommendations for a generic MIZBAN design, which will fulfill the requirement for demand response by the U.S. government, i.e. a latency of less than 0.25 s.Index Terms-Advanced Metering Infrastructure (AMI), building area network (BAN), multi-interface, smart grid, ZigBee.

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Real Time Operation of Smart Grids via FCN Networks and Optimal Power Flow

Cited by 198 publications

References 51 publications

Energy Management System Control for a Hybrid Non-conventional Energy Sources using Hysteresis Switching Algorithm

Energy Management System Control for a Hybrid Non-conventional Energy Sources using Hysteresis Switching Algorithm

A Framework for Real-Time Optimal Power Flow under Wind Energy Penetration

The Generic Design of a High-Traffic Advanced Metering Infrastructure Using ZigBee

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