iPlug: Decentralised dispatch of distributed generation

Rongali, Subendhu; Ganuy, Tanuja; Padmanabhan, M.K.; Arya, Vijay; Kalyanaraman, Shivkumar; Petra, Mohammad Iskandar

doi:10.1109/comsnets.2016.7440003

Cited by 8 publications

(2 citation statements)

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“…Numerous studies on solar regulation through curtailment exist Rongali et al (2016); Lo and Ansari (2012); Tonkoski et al (2011); Bandyopadhyay et al (2016). Tonkoski et al (2011) presents an active power curtailment technique to increase the overall distributed solar capacity at the low-voltage feeder Rongali et al (2016) describes a voltage-based curtailment where the solar rate is reduced if the sensed voltage is higher than normal. Lo and Ansari (2012) presents a discrete curtailment approach by completely disconnecting the solar units through control signals from the utility's command center.…”

Section: Related Workmentioning

confidence: 99%

Distributed rate control of smart solar arrays with batteries

Bovornkeeratiroj

Iyengar

Irwin

et al. 2023

Front. Internet Things

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Continued advances in technology have led to falling costs and a dramatic increase in the aggregate amount of solar capacity installed across the world. A drawback of increased solar penetration is the potential for supply-demand mismatches in the grid due to the intermittent nature of solar generation. While energy storage can be used to mask such problems, we argue that there is also a need to explicitly control the rate of solar generation of each solar array in order to achieve high penetration while also handling supply-demand mismatches. To address this issue, we present the notion of smart solar arrays that can actively modulate their solar output based on the notion of proportional fairness. We present a decentralized algorithm based on Lagrangian optimization that enables each smart solar array to make local decisions on its fair share of solar power it can inject into the grid and then present a sense-broadcast-respond protocol to implement our decentralized algorithm into smart solar arrays. We also study the benefits of using energy storage when we rate control solar. To do so, we present a decentralized algorithm to charge and discharge batteries for each smart solar. Our evaluation on a city-scale dataset shows that our approach enables 2.6× more solar penetration while causing smart arrays to reduce their output by as little as 12.4%. By employing an adaptive gradient approach, our decentralized algorithm has 3 to 30× faster convergence. Finally, we demonstrate energy storage can help netmeter more solar energy while ensuring fairness and grid constraints are met.

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Section: Related Workmentioning

confidence: 99%

Distributed rate control of smart solar arrays with batteries

Bovornkeeratiroj

Iyengar

Irwin

et al. 2023

Front. Internet Things

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“…Several works perform reactive solar curtailment in response to rising voltage. VVO [26] increases reactive power to lower the voltage due to real power while iPlug curtails the solar energy input to the grid by redirecting it to charge storage or coordinate with local demand ramp-up resources [28]. e authors in [22,33,36] achieve continuous curtailment from solar PVs by running them at voltages other than the Maximum Power Point (MPP).…”

Section: Related Workmentioning

confidence: 99%

Optimal net-load balancing in smart grids with high PV penetration

Kuppannagari

Kannan

Prasanna

2017

Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments

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Mitigating Supply-Demand mismatch is critical for smooth power grid operation. Traditionally, load curtailment techniques such as Demand Response (DR) have been used for this purpose. However, these cannot be the only component of a net-load balancing framework for Smart Grids with high PV penetration. ese grids can sometimes exhibit supply surplus causing over-voltages. Supply curtailment techniques such as Volt-Var Optimizations are complex and computationally expensive. is increases the complexity of net-load balancing systems used by the grid operator and limits their scalability. Recently new technologies have been developed that enable the rapid and selective connection of PV modules of an installation to the grid. Taking advantage of these advancements, we develop a uni ed optimal net-load balancing framework which performs both load and solar curtailment. We show that when the available curtailment values are discrete, this problem is NP-hard and develop bounded approximation algorithms for minimizing the curtailment cost. Our algorithms produce fast solutions, given the tight timing constraints required for grid operation. We also incorporate the notion of fairness to ensure that curtailment is evenly distributed among all the nodes. Finally, we develop an online algorithm which performs net-load balancing using only data available for the current interval. Using both theoretical analysis and practical evaluations, we show that our net-load balancing algorithms provide solutions which are close to optimal in a small amount of time. RELATED WORKSSigni cant literature exists on performing net-load balancing using load curtailment techniques such as Demand Response (DR). e key idea is to 'shi ' the loads away from high demand periods. Load curtailment can be pricing based in which the customers are arXiv:1709.00644v3 [cs.DS]

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