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Smart Management for the Smart Grid A. Kazakov January 2018

Smart Grid Mgmt

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Page 1: Smart Grid Mgmt

Smart Management

for the Smart Grid

A. Kazakov

January 2018

𝑭 𝑿 → 𝒎𝒊𝒏𝑹 𝑿 ≥ 𝟎

Page 2: Smart Grid Mgmt

Unified energy system (UES)

𝐺 = 𝑁, 𝐸𝑁 − 𝑁𝑜𝑑𝑒𝑠𝐸 − 𝐿𝑖𝑛𝑒𝑠

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Notation UES

𝐺 = 𝑁, 𝐸 − 𝐺𝑟𝑎𝑝ℎ𝑁 = 𝑛𝑖 − 𝑁𝑜𝑑𝑒𝑠

𝐸 = 𝑒𝑖𝑗 − 𝐿𝑖𝑛𝑒𝑠

𝑒𝑖𝑗= (𝑛𝑖, 𝑛𝑗)

𝑁 = 𝑁𝑆 ∪ 𝑁𝑇 ∪ 𝑁𝐷

𝑁𝑆 − 𝐺𝑒𝑛𝑒𝑟𝑎𝑡𝑖𝑜𝑛𝑁𝑇 − 𝑇𝑟𝑎𝑛𝑠𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑁𝐷 − Distribution

𝑆 𝑁𝑆, 𝑡 − 𝑆𝑢𝑝𝑝𝑙𝑦𝐷 𝑁𝐷𝑠, 𝑡 − 𝐷𝑒𝑚𝑎𝑛𝑑𝑡 = 𝑡𝑖 − 𝑇𝑖𝑚𝑒𝑡𝑖+1 − 𝑡𝑖 = 30 𝑚𝑖𝑛

Supply Chain Management (SCM)

SupplyTranspor-

tationDemand

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Logistics network G

𝑭 𝑿 → 𝒎𝒊𝒏𝑹 𝑿 ≥ 𝟎

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The theoretical basis for SCM solutions

• Pointing theorem

• Le Chatelier's Principle

• The Principle of Least Actionby Feynman

• The development of the variationmethod for solving utility tasks

• Mathematical Methodsof Operations Research

Innovation (Т)

Theoretical Physics

Applied Mathematics

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Options SCM for UES

Ultimate

ConsumersDistribution RetailTransmission

Generation &

TradeConsumption

Ultimate

ConsumersDistribution RetailTransmission

Generation &

TradeConsumption

Value Distributed Energy Resources – DER (Local generation, storage, electric vehicles)

The Legacy Chain of Production, Transmission and Consumption of electricity

The Target Chain of Production, Transmission and Consumption of electricity

Information

Exchange

Platforms

Information

Devices

Information

Services

Energy Stream

Information Stream

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The digital economy in a Smart Grid

• Generation, Transmission and Consumptionof electricity: plan & accounting

• Energy Stream: management & control

• Collection, Distribution and Useof information: the model forecast & consolidation

• Information Stream: management & control

Real Production

Digital Power

Innovation (E)

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Key Technologies for the Project

• MLP - mixed linear programming

• LR - Linear Regression

• BM - Benchmarking

• BI - Business intelligence

• MDM - Master data management

• BC - Block chain

Mathematical Methods in Economics Information Technologies

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Key Projects Portfolio

Material and cost balances energy streamfor each node of the Grid

Parametric calculation of energy stream (for model SCM)

Planning and forecasting of demands and supplies

Assembling and rating of parameters of adaptive models UES

Unified target ICT architecture

Formalization and automation of information legacy exchanges based on a common (ontological model) MDM

MLP

BI, MLP

BI, LR

BI, LR, BM

MDM, BC

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Page 10: Smart Grid Mgmt

Optimization Models for SCM is the core to Project

Futureplanning

Strategic

Long-termMedium-

termShort-term

Tactical planning Scheduling

Dispatch

T t

New Grid Assets Existing Grid Assets

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Created new opportunities• Optimal operational management of electric grid: full, partial

• Model the formation of material Balances of stream 𝐁(𝐗, 𝐍, 𝐭)for all nodes of the network: replenishment of missing data, detection and elimination of inconsistencies

• Automated making of consolidated material and cost balances

• Stream forecasting for different time horizons: strategic, tactical, operational-production

• The possibility of clustering and/or consolidation of the network in forecasting: by owners or according to production criteria

• OPEX estimation in the Asset management of the electric grid: use and/or preservation of existing assets, creation of new assets

Creating valueSmart Management for the Smart Grid 11

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The target Reference architecture model

IEC Recommendation

SGAM –SmartGridArchitectureModel

IEC 62559-4/TR/Ed12016-05-13

https://www.en-trust.at/NISTIR/

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Thank you for Your attention!

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