THE WIDE-AREA ENERGY STORAGE AND MANAGEMENT SYSTEM PHASE II Final Report - Flywheel Field Tests

Liu, Ning; Makarov, Yuri V.; Weimar, Mark R.; Rudolph, F. J.; Murthy, S.N Keshava; Arseneaux, J.A.; Loutan, Clyde; Chowdhury, Sirajul

doi:10.2172/991592

Cited by 10 publications

(6 citation statements)

References 9 publications

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“…Generation units are subject to hourly ramp-up and ramp-down constraints, as shown in Eqs. (5) and (6) respectively. The required Reg+ (R + (t)) and RegÀ (R À (t)) for the system at hour t is provided by units which are on, as given in Eqs.…”

Section: Minimizementioning

confidence: 99%

“…In the USA, ISOs and RTOs have taken an active role in following FERC order to identify and monetize all the benefits that storage may bring to the grid by improving the market policies [4,5]. Simultaneously there are on-going efforts from many researchers and industries to properly model these storage technologies in operating and planning studies [6][7][8], as system operators and planners feel the need for tools that can properly capture the various functionalities of storage, systematically assess its contributions towards grid operations and incentivize their multiple value streams [9].…”

Section: Introductionmentioning

confidence: 99%

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Assessing the benefits and economics of bulk energy storage technologies in the power grid

2015

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Section: Minimizementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessing the benefits and economics of bulk energy storage technologies in the power grid

2015

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“…With fast response and low operating costs, energy storage can be an attractive resource to compensate for variability between load demand and power production by renewable resources. However, research indicates that most energy storage technologies, at current cost levels, are not economically competitive in power markets compared to conventional generating resources [1][2][3]. Energy capacity and power capacity are the two major factors determining the capital investment of a storage device.…”

Section: Introductionmentioning

confidence: 99%

Cross-market optimization for hybrid energy storage systems

Jin

Liu

et al. 2011

2011 IEEE Power and Energy Society General Meeting

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A method is developed to generate optimal bid schedules for a hybrid energy storage system participating in both energy and regulation service markets. The hybrid energy storage system includes a fast-response component, such as a flywheel or battery, and a slow response component, such as a pumped-hydro or a conventional generator. This paper describes the objective function and constraints of the cross-market optimization problem. A genetic algorithm is used to solve the problem with a nonlinear penalty curve applied to the energy constraints. A single market optimization method based on priority search is used as a baseline. The results show that the cross-market optimization can improve revenue of the energy storage system by 6.9% over the baseline. Although the method was applied to a hybrid energy storage system, it can be generalized to any energy storage systems.

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“…However, ESDs are expensive. Comprehensive cost-benefit studies [3][4][5][6] have shown that the following strategies will make using ESDs more cost-effective: 1) providing multiple services to increase the utilization rate and revenue streams, 2) using demand-side management (DSM) to reduce the size of ESDs, and 3) sharing ESDs among a group of users to reduce the amount of ESD needed at the aggregated level.…”

mentioning

confidence: 99%

A Graphical Performance-Based Energy Storage Capacity Sizing Method for High Solar Penetration Residential Feeders

Zhu

Yan

Liu

2017

IEEE Trans. Smart Grid

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This paper presents a graphical, performancebased energy storage capacity sizing method for residential feeders with high solar penetration levels. The rated power and storage capacity of an energy storage device (ESD) are calculated to fulfill a specified operational requirement. Three locations for installing ESDs are investigated: 1) consumer-owned ESDs inside single-family households, 2) utility-owned distribution transformer-level ESDs, and 3) third-party owned ESDs in a community. First, historical solar radiation data, residential household load data, and residential load models are used for creating the net load (load minus solar generation) ensembles at the house level with resolution of 15 minutes. Then, a novel graphical capacity selection method using equal probability lines (EPLs) on compressed, composite cumulative distribution function (CC-CDF) curves is developed for sizing the energy storage needs at the house, distribution transformer, and community levels. Demand-side management (DSM) methods are investigated for further reducing the need of energy storage. Simulation results demonstrate that the proposed method avoids over-or under-sizing ESDs and allows the users to compare the marginal benefit of increasing the capacity of the ESD.Index Terms-performance-based methods, data-driven model, energy storage systems, PV, distribution planning, demand response, optimal sizing, renewable integration.

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THE WIDE-AREA ENERGY STORAGE AND MANAGEMENT SYSTEM PHASE II Final Report - Flywheel Field Tests

Cited by 10 publications

References 9 publications

Assessing the benefits and economics of bulk energy storage technologies in the power grid

Assessing the benefits and economics of bulk energy storage technologies in the power grid

Cross-market optimization for hybrid energy storage systems

A Graphical Performance-Based Energy Storage Capacity Sizing Method for High Solar Penetration Residential Feeders

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