Operation and Configuration of a Storage Portfolio via Convex Optimization

Kraning, Matt; Wang, Yan; Akuiyibo, Ekine; Boyd, Stephen

doi:10.3182/20110828-6-it-1002.02697

Cited by 41 publications

(40 citation statements)

References 24 publications

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“…RHC has been successfully applied in many areas, including chemical process control [50], supply chain management [11], stochastic control in economics and finance [24,58], and energy storage system op-eration [37]. While RHC is in general not an optimal controller, it has been shown to achieve good performance in many different domains.…”

Section: Closed-loop Controlmentioning

confidence: 99%

Dynamic Network Energy Management via Proximal Message Passing

Kraning

2014

FNT in Optimization

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209

228

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Section: Closed-loop Controlmentioning

confidence: 99%

Dynamic Network Energy Management via Proximal Message Passing

Kraning

2014

FNT in Optimization

Self Cite

209

228

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“…We apply an augmented formulation of what proposed in [39] to obtain a convex equivalent formulation of the original problem. We introduce:…”

Section: Appendix a Convex Formulation Of Day-ahead Problemmentioning

confidence: 99%

Achieving the Dispatchability of Distribution Feeders Through Prosumers Data Driven Forecasting and Model Predictive Control of Electrochemical Storage

Sossan

Namor

Cherkaoui

et al. 2016

IEEE Trans. Sustain. Energy

125

129

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Abstract-We propose and experimentally validate a process to dispatch the operation of a distribution feeder with heterogeneous prosumers according to a trajectory with 5 minutes resolution, called dispatch plan, established the day before the operation. The controllable element is a utility-scale grid-connected battery energy storage system (BESS) integrated with a minimally pervasive monitoring infrastructure. The process consists of two stages: day-ahead, where the dispatch plan is determined by using forecast of the aggregated consumption and local distributed generation (prosumption), and real-time operation, where the mismatch between the actual prosumption realization and dispatch plan is compensated for thanks to adjusting the real power injections of the BESS with model predictive control (MPC). MPC accounts for BESS operational constraints thanks to reduced order dynamic grey-box models identified from online measurements. The experimental validation is performed by using a grid-connected 720 kVA/500 kWh BESS to dispatch the operation of a 20 kV distribution feeder of the EPFL campus with both conventional consumption and distributed photo-voltaic generation.

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“…In [20] and [21], the authors consider this question from a purely economic point of view. Capacity provisioning of energy resources with network constraints of the physical system has been addressed, e.g., [12], [14].…”

Section: Introductionmentioning

confidence: 99%

Optimal large-scale storage placement in single generator single load networks

Thrampoulidis

Bose

Hassibi

2013

2013 IEEE Power &Amp; Energy Society General Meeting

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Abstract-Large-scale storage will play an increasingly important role in future power grids. As a result, how to optimally place storage in such networks, is an important investment problem. Furthermore, since the allocation of storage resources is static, i.e., it is not feasible to move storage around in a dynamic fashion, it is important to derive optimal such allocations that are robust to the values of the load profiles and other network parameters, such as the line flow constraints. For a single generator single load network, and for a cost of generation that is quadratic in the generation power, we show that, for any given amount of storage resources, placing storage at the demand node is always optimal. This result is true regardless of the demand profile and flow constraints, and therefore is robust. As a byproduct of this result, for a fixed demand profile, we characterize the dependence of the optimal production cost on the flow constraints and on the available storage resources.

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Operation and Configuration of a Storage Portfolio via Convex Optimization

Cited by 41 publications

References 24 publications

Dynamic Network Energy Management via Proximal Message Passing

Dynamic Network Energy Management via Proximal Message Passing

Achieving the Dispatchability of Distribution Feeders Through Prosumers Data Driven Forecasting and Model Predictive Control of Electrochemical Storage

Optimal large-scale storage placement in single generator single load networks

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