Optimization for a Smarter Energy World !

Sortie officielle de la cartographie SmartGrid

Namur, April 11 2016

The best of advanced analytics for optimal decision-making

Mathematical sciences

Business engineering

Computer science

Our professionals provide you with combined expertise in:

State-of-the-art mathematics and algorithms are at the heart of N-SIDE’s innovation

Providing tailored software solutions & services to optimize decision making

Maximize profitsBe agile Manage risks

2

3

DescriptiveDetailed mathematical models to describe complexity and

opportunities

PredictiveAdvanced forecast to be ahead of risk/opportunity

PrescriptiveEfficient algorithm to generate optimal

decisions

N-S

IDE

APPR

OAC

H The best of advanced analytics for optimal decision-making

Market coupling Optimization

Energy Flexibility Optimization

MicroGridOptimization

Optimization for a smarter Energy World

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Market Coupling Optimization

EUPHEMIA by N-SIDE

Day-ahead electricity prices in Europe are calculated everyday thanks to N-Side algorithms

Extension to

Whole

Europe

underway

> “EUPHEMIA”: market coupling algorithm for European Power exchange, implemented and developed in-house by N-SIDE, from theory to operations

> Used daily by Power Exchanges to fix pan-EU day-ahead electricity prices in 19 EU countries

> Computing market prices & volumes by: coupling national markets maximizing total economical welfare optimizing network capacity utilization modeling complex constraints

Modeling and Optimization of Electricity Markets

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Energy Flexibility Optimization

ENERTOP by N-SIDE

Energy Flexibility Optimization with the best of advanced analytics

Flexible Load Models

CHP Models

RES Models

Storage Models

EVs Models

Efficient Mathematical Modellings

Planning Optimization

Real-time Optim.

Investment Optimization

Aggregation Optim.

Bidding Optimization

Advanced Optimization Algorithms

+

DA Market Forecast

Balancing Opporunities

Reserve Markets

Demand Forecast

Contracts Model

Accurate Forecasts

+ =CustomizedFlexibilityOptimization Solutions

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Mathematical models to describe plant complexity…A mathematical model is key for considering all factors in an integrated way…

Grid and market interaction• Different electricity

contracts (OTC, spot based)

• Capacity constraints

Storage facilities• Min-max capacities• Storage target

Industrial processes• All input and output flows• Maximal Stop/Day

• Minimal time OFF• ON-Off procedure• Operating rates

Economics• RM, electricity costs• Opportunity costs• Fix and variable

operating costs• Incentive from DR

programs 9

1

Example : Mathematical Model of Cement Plants

Product Demand• Quantities and delivery dates• Must / May serve

… and the differents energy flexibilities

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Produce electricity at optimal moment

ElectricityGeneration

Electricity Consumption

Consume electricity at optimal moment

Load Shifting

Load Scheduling

Load SheddingElectricity Storage

B

A

C F

CHP ModulationE

Fuel SwitchingD

Advanced forecasts to be ahead of risk/opportunities

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Statistics and Machine learning techniques

Spot Price Forecast

2

12

Probalistic Approach

Statistics and Machine learning techniques

Spot Price Forecast

1° Reserve composition: Quantity reserved / Marginal cost for each reserve

2° Imbalance volume on previous Quarter

3° External unpredicted change

Imbalance orientation:

Level of Imbalance:

Balancing Opportunity Forecast

Advanced forecasts to be ahead of risk/opportunities2

13

Probalistic Approach

Spot Price Forecast

1° Reserve composition: Quantity reserved / Marginal cost for each reserve

2° Imbalance volume on previous Quarter

3° External unpredicted changes

Imbalance orientation:

Level of Imbalance:

Stochastic tree to generate what-if

scenarios

1° Demand : Order book

2° Process: Maintenance and machine failure

3° External factors

Combined What-if scenarios

Balancing Opportunity Forecast

Statistics and Machine learning techniques

Advanced forecasts to be ahead of risk/opportunities2

14

Spot Price Forecast

1° Reserve composition: Quantity reserved / Marginal cost for each reserve

2° Imbalance volume on previous Quarter

3° External unpredicted changes

Stochastic tree to generate what-if scenarios

1° Demand : Order book

2° Process: Maintenance and machine failure

3° External factors

Combined What-if Scenarios

Probalistic ApproachImbalance orientation:

Level of Imbalance:

Balancing Opportunity Forecast

Statistics and Machine learning techniques

Advanced forecasts to be ahead of risk/opportunities2

Efficient algorithms to generate optimal planning….

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Advanced Algorithm

Accurate resultsFast running

Robust SolutionIntuitive

Planning

Electricity price forecast

Risk Factors forecast

Mathematical modeling

Optimized planning

3

… leveraging the different flexibility levers in a integrated way…

16

Produce electricity at optimal moment

ElectricityGeneration

Electricity Consumption

Consume electricity at optimal moment

Load Shifting

Load Scheduling

Load SheddingElectricity Storage

B

A

C F

CHP ModulationE

Fuel SwitchingD Inte

grat

ed O

ptim

izatio

n

Strategic Optimization

Reserve Optimization

Scheduling Optimization

Real-time Optimization

… and maximize savings on the different key timeframes

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• Optimal electricity contract

• Optimal investment in flexibility assets

• Optimal choice of flexibility products and volumes

• Optimal power and energy price

• Optimal scheduling of electricity load

• Optimal planning of CHP unit

• Optimal imbalance minimization

• Optimal activation management

InduStore• Objective: Quantify and Optimize Demand

Response potential in industrial sector in Wallonia

• 4 years project funded by walloon region (started in Oct. 2014)

• Partners: N-SIDE, UCL, ULg and ICEDD

• Objective: Optimize interaction between TSO and DSO to leverage flexibilities at local level

• 3 years H2020 projects starting in 2016• Partners: 22 including RSE, Siemens,

Vodafone, Energinet.dk, Terna, Sintef, VTT, VITO.

Innovative Projects on Energy Flexibility Optimization

MicroGrid Optimization

How to design and optimize my micro-grid in an optimal way ?

E-Cloud: Project for an Open Microgrid Solution

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• Optimized microgrids for industrial parks (eco-zoning):

Optimal investment in RES Optimal sharing of locally produced

electricity Optimal storage of electricity Optimal billing process managed by

DSO in charge of eco-zoning Optimal interaction with network

Two pilots projects in Wallonia

Partnership

Interested to know more ? Please contact us

Olivier DevolderEnergy Project ManagerTel: +32 472 46 83 44Email: ode@n-side.com

N-SIDEWatson & Crick Hill Park – Bldg. H Rue Granbonpré, 11B- 1348 Louvain-la-Neuve