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A stochastic power network calculus for integrating renewable energy sources into the

power grid

Presenter: qinghua shen

Wang, Kai, et al. "A stochastic power network calculus for integrating renewable energy sources into the power grid." Selected Areas in Communications, IEEE Journal on 30.6 (2012): 1037-1048.

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content

• Intro• Formulation• Power system modelling• Performance metrics • Case study • Conclusions

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1. Intro

• Motivationuse environmentally friendly sourcesadopt storage to match uncertain supply and demand (island)

improve reliability of the system

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1. Intro

• MotivationWhy network calculus

The ability of the stochastic network calculus to model broad classes of queueing scenarios and capture statistical multiplexing gain

Why extend Decoupled arrival and service processSpecific performance metrics:

Fraction of Time that energy is not-served (FTNS) waste of power supply (WPS) (drop rate)

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2. Formulation

• Problem descriptionIsland: only renewable sources for supplyStorage has limited capacity CNp: PV panels, Nw wind turbinesObjectives: reliability provisioning in terms of FTNS

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2. Formulation

• Network Calculus was designed to facilitate stochastic performance analysis

(tail performance analysis with multiplexing)Envelop process to characterize arrival processQueue characterization:

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3. Power system modelling

• Energy storage: discrete – Charged:

– Discharged:

– Differences from queue• Departure is not a function of the arrival and current

queue

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3. Power system modelling

• Energy demand and supply– Upper curve:

– Lower curve:

– Similar for supply– Upper curve: similar to queue– Lower curve: needed for energy storage– Tightness: tradeoff between shapes of curves and

bounding function

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4. Performance metrics

• Transform to non-recursive– recursive

– Non-recursive:

– Compare to previous work• Finite buffer length

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4. Performance metrics

• How to present metrics recursive form

Loss of power supply:Fraction Time of no service:Waste of power supply (WPS)

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4. Performance metrics

• How to present metrics non recursive form

Loss of power supply:

Fraction Time of no service:Waste of power supply (WPS):

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4. Performance metrics

• Bound expression Loss of power supply:

Intuition: upper of demand - lower of supply

Waste of power supply (WPS):Intuition: upper of supply – lower of demand

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4. Performance metrics

• More benefits to come!Multiplexing:

For N source with

Similar results for upper bound

• Something is missing! (hao)

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5. A case study • Santa Catalina Island

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5. A case study • Model fitting– Linear function with rate equal to long term mean rate– exponential functions for the bounding functions

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5. A case study • Model fitting– Linear function with rate equal to long term mean rate– exponential functions for the bounding functions

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5. A case study • Model fitting– Linear function with rate equal to long term mean rate– exponential functions for the bounding functions

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5. A case study • Numerical results– Impacts of PV panels, wind and season

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6. Conclusion• Issues: demand and supply for an island– Only renewable energy– Storage aided– Reliability

• Good point– New type of “queue”– Finite buffer analysis

• Insufficient– Does this really matter (finite queue, decoupled?)

• My view– Not average tail but instantaneous tail(New fitting)– How will renewable energy impacts the market?