Power-System Reliability Impact of Energy-Storage Integration with Intelligent-Operation Strategy

Xu, Yixing

doi:10.1016/b978-0-12-410491-4.00008-7

Cited by 16 publications

(26 citation statements)

References 19 publications

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“…The algorithm also takes into account the storage devices efficiency and standby losses, η and µ, respectively [10], as the change in energy of the storage device between time steps has been combined into one variable; when δ S is negative, the storage devices efficiency is 1 η , as shown in Equation (4). It is customary to define the SOC quantity as a value between zero and one; however, in Equation (1), as in [41], the state of charge at the end of each period is determined by the previous period's SOC level and the increase or decrease of energy in or out of the storage device (δ S ) at the current period.…”

Section: The Energy Storage System and LV Network Demand Modelmentioning

confidence: 99%

The Real-Time Optimisation of DNO Owned Storage Devices on the LV Network for Peak Reduction

et al. 2014

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Energy storage is a potential alternative to conventional network reinforcement of the low voltage (LV) distribution network to ensure the grid's infrastructure remains within its operating constraints. This paper presents a study on the control of such storage devices, owned by distribution network operators. A deterministic model predictive control (MPC) controller and a stochastic receding horizon controller (SRHC) are presented, where the objective is to achieve the greatest peak reduction in demand, for a given storage device specification, taking into account the high level of uncertainty in the prediction of LV demand. The algorithms presented in this paper are compared to a standard set-point controller and bench marked against a control algorithm with a perfect forecast. A specific case study, using storage on the LV network, is presented, and the results of each algorithm are compared. A comprehensive analysis is then carried out simulating a large number of LV networks of varying numbers of households. The results show that the performance of each algorithm is dependent on the number of aggregated households. However, on a typical aggregation, the novel SRHC algorithm presented in this paper is shown to outperform each of the comparable storage control techniques.

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Section: The Energy Storage System and LV Network Demand Modelmentioning

confidence: 99%

The Real-Time Optimisation of DNO Owned Storage Devices on the LV Network for Peak Reduction

et al. 2014

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“…Energy sources such as solar and wind usually are used with a mandatory energy storage system, just to meet the demand in times where wind or sunlight are not ofering the required energy [22]. Such systems have associated environmental impact since they use lead-acid batery banks [23].…”

Section: Energy Storage In Smart Gridsmentioning

confidence: 99%

Emerging Technologies for Renewable Energy Systems

Spatti¹,

Liboni²

2016

Smart Cities Technologies

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Considering all aspects involving smart grid deployment, several subjects extrapolate the electrical sector. In the Brazilian scenario, it can be clear that power companies cannot support, by themselves, all steps for establishing renewable energy sources in smart grid systems. The technology demands are greater than what the electric sector can deliver. Such discussions about regulations of renewable energy sources are largely discussed in the society. The search for deploying eolic and solar generation with big energy farms are opposite to the smart grid and smart city renewable energy concept, which require decentralized actions. This chapter will show the concepts of eolic and solar energy sources speciically in the context of Smart Grids.

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“…Most of these studies have focused on the operation and control strategy of the BESS for the integration with renewable energy, energy management, power quality, and etc. [1][2][3][4][5][6][7][8][9][10][11][12][13]. However, few protection studies in power systems with BESSs have been performed.…”

Section: Introductionmentioning

confidence: 99%

Reclosing scheme using synchronism checking for utilization of BESS in distribution system

Seo¹,

Rhee

2017

J. Mod. Power Syst. Clean Energy

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This paper proposes a reclosing scheme using synchronism checking for utilization of battery energy storage system (BESS) in a distribution system. The algorithm disconnects the faulty phase and keeps the power supply from the BESS to the healthy phase. Synchronism checking between the main source side and the load side is applied to minimize the transients at the reclosing instant. The BESS at the faulty phase is reconnected after checking the successful reclosing. The distribution system including BESS and proposed reclosing scheme are modeled by the electromagnetic transients program (EMTP)/ATPDraw. The various simulations by varing the fault clearing time are conducted and the simulation results are discussed. Also, the relation between proposed reclosing scheme and reliability is discussed.

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Power-System Reliability Impact of Energy-Storage Integration with Intelligent-Operation Strategy

Cited by 16 publications

References 19 publications

The Real-Time Optimisation of DNO Owned Storage Devices on the LV Network for Peak Reduction

The Real-Time Optimisation of DNO Owned Storage Devices on the LV Network for Peak Reduction

Emerging Technologies for Renewable Energy Systems

Reclosing scheme using synchronism checking for utilization of BESS in distribution system

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