An Energy Storage Cost Comparison: Li-ion Batteries vs Distributed Load Control

Cammardella, Neil; Moye, Robert; Chen, Yue; Meyn, Sean

doi:10.1109/psc.2018.8664042

Cited by 18 publications

(10 citation statements)

References 11 publications

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“…A macro-model for a diverse population is comprised of a finite number of different type DER homogeneous populations that work together under the same VPP for demand dispatch. Hence, consider a population of DERs described by (1) with common underlying state space. To create a finite-state abstraction of the entire population evolution, the state space is discretized in a manner that the main features of the system are preserved.…”

Section: B Pem Macro-modelmentioning

confidence: 99%

“…For decades, the operating paradigm has been supply follows demand, which has been implemented via the hierarchical primary, secondary, and tertiary frequency regulation schemes. However, with increasing penetrations of variable renewable generation, such as solar PV and wind, and internet-enabled, connected, and controllable appliances (e.g., distributed energy resources or DERs), it is now technically and economically feasible for flexible demand to follow a variable supply (i.e., provide dynamic grid services) [1]- [3]. However, to control large fleets of DERs to provide grid services requires a distributed controller implementation, which has been known since the late 1970s [4], [5].…”

Section: Introductionmentioning

confidence: 99%

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Reference-Tracking Control Policies for Packetized Coordination of Heterogeneous DER Populations

Espinosa

Khurram

Almassalkhi

2021

IEEE Trans. Contr. Syst. Technol.

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Section: B Pem Macro-modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reference-Tracking Control Policies for Packetized Coordination of Heterogeneous DER Populations

Espinosa

Khurram

Almassalkhi

2021

IEEE Trans. Contr. Syst. Technol.

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“…In the scenario approach, the chance constraint is substituted with a finite, but large number of deterministic constraints corresponding to different realizations of the underlying uncertainty space [36]. By employing an adequate number of 1 A unimodal distribution is one with a clear peak and includes distributions, such as Gaussian, uniform, and chi-square distributions. For details, please see [34].…”

Section: A Chance Constrained Formulationmentioning

confidence: 99%

“…However, even though the cost of an ESS has declined significantly in the last decade, ESSs remain expensive options. In addition, less costly alternatives, such as energy services provided by aggregated DERs, are advancing rapidly [1].…”

Section: Introductionmentioning

confidence: 99%

Optimal Corrective Dispatch of Uncertain Virtual Energy Storage Systems

Amini

Almassalkhi

2020

IEEE Trans. Smart Grid

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High penetrations of intermittent renewable energy resources in the power system require large balancing reserves for reliable operations. Aggregated and coordinated behind-the-meter loads can provide these fast reserves, but represent energy-constrained and uncertain reserves (in their energy state and capacity). To optimally dispatch uncertain, energy-constrained reserves, optimization-based techniques allow one to develop an appropriate trade-off between closed-loop performance and robustness of the dispatch. Therefore, this paper investigates the uncertainty associated with energy-constrained aggregations of flexible, behind-the-meter distributed energy resources (DERs). The uncertainty studied herein is associated with estimating the state of charge and the capacity of an aggregation of DERs (i.e., a virtual energy storage system or VESS). To that effect, a risk-based chance constrained control strategy is developed that optimizes the operational risk of unexpectedly saturating the VESS against deviating generators from their scheduled set-points. The controller coordinates energy-constrained VESSs to minimize unscheduled participation of and overcome ramprate limited generators for balancing variability from renewable generation, while taking into account grid conditions. To illustrate the effectiveness of the proposed method, simulation-based analysis is carried out on an augmented IEEE RTS-96 network with uncertain energy resources and temperature-based dynamic line ratings.

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“…This batterylike behavior of flexible loads is often referred as Virtual Energy Storage (VES) [1]. VES from flexible loads can be less expensive than energy storage from batteries [2]. Some examples of flexible loads include residential air conditioners [3], water heaters [4], refrigerators, commercial HVAC systems [5], pumps for irrigation [6], pool cleaning [7] or heating [8].…”

Section: Introductionmentioning

confidence: 99%

Characterizing capacity of flexible loads for providing grid support

Coffman¹,

Zhang²,

Barooah³

2020

Preprint

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Flexible loads are a resource for the Balancing Authority (BA) of the future to aid in the balance of supply and demand in the power grid. Consequently, it is of interest for a BA to know how much flexibility a collection of loads has, so to successfully incorporate flexible loads into grid level resource allocation. Loads' flexibility is limited by all their Quality of Service (QoS) requirements. In this work we present a characterization of capacity for a collection of flexible loads. This characterization is in terms of the Power Spectral Density (PSD) of the reference signal. Two advantages of our characterization are: (i) it easily allows for a BA to use the characterization for resource allocation of flexible loads and (ii) it allows for precise definitions of the power and energy capacity for a collection of flexible loads.

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An Energy Storage Cost Comparison: Li-ion Batteries vs Distributed Load Control

Cited by 18 publications

References 11 publications

Reference-Tracking Control Policies for Packetized Coordination of Heterogeneous DER Populations

Reference-Tracking Control Policies for Packetized Coordination of Heterogeneous DER Populations

Optimal Corrective Dispatch of Uncertain Virtual Energy Storage Systems

Characterizing capacity of flexible loads for providing grid support

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