software tools and solutions for hpp operation optimization

12/19/2019 FOOTER GOES HERE 1

SOFTWARE TOOLS AND

SOLUTIONS FOR HPP

OPERATION OPTIMIZATION

TYPES OF TOOLS, APPROACH

AND EXAMPLES


• Types of tools

• Maximum welfare models as SDDP

• Profit maximization tools

Table of contents

12/19/2019 3

There are two main approaches for hydropower

operation planning

Profit maximization

• Used under market environments

• The goal is to maximize the profits of

the company against the power market

• Only needs detailed characterization

of own plants but needs an electricity

price and water inflow forecast which

are typically stochastic

• Utilities use portfolio optimization

models either tailored or commercial

Maximum welfare

• Used in systems with centralized

planning as in the case of state-owned

producers

• The goal is to maximize social welfare

using the system cost as a proxy

• Requires detailed characterization of

the whole system considered

• SDDP is the most widely used model

(M. Pereira, PSR)

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Table of contents

• Types of tools




Table of contents

• Types of tools


• Introduction

• Methodological approach

• Examples of application

• Overview of available software

solutions


12/19/2019 6

SDDP presents a sophisticated and powerful approach to

hydrothermal scheduling

6

SDDP: provides optimal (least-cost) hydrothermal

dispatch (delivered quantities by plant and nodal

prices) for a given demand forecast and generation

expansion plan, with stochastic consideration of

water inflows (hydrologies) and medium/long term

optimization of reservoirs.

SDDP allows including in the optimization process

the constrains arising from other used of water like

irrigation, flood control, navigation and

environmental requirements

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12/19/2019 7

The tool allows detailed representation of hydroelectric plants

considering hydrological uncertainty and the transmission grid

• Individual representation of hydroelectric plants:

– On cascade hydric balance.

– Spillage, filtration and evaporation.

– Variable production factor.

– Alert volume, minimum security storage and flood control storage

– Maximum and minimum total outflow constrains.

• Integrated analysis of hydrothermal systems together with the transmission

system.

• Hydrology uncertainty calculated through a stochastic model that takes into

account the temporal and spatial dependence.

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12/19/2019 8

It requires parametrization of the power system including

demand, generation and transmission

• Reservoir operation planning requires to know:

– Demand side:

• Load Forecast

– Generation side:

• Expected new generation entries

• Hydro forecast (inflows to the reservoirs)

• Restrictions on water storage and release

• Expected maintenance outages

• Fuel prices forecast

– Power transmission:

• Available transfer capacities

• Operation and transmission constraints and reliability

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Table of contents

• Types of tools


• Introduction




solutions


# of plants # of states

1 202= 400

2 204=160 thousand

3 206= 64 million

4 208≈ 25 billion

5 2010≈ 10 trillion!!!!

12/19/2019 10

The traditional approach for hydropower optimization

becomes unsolvable with large numbers of reservoirs

• The computational effort increases

exponentially with the number of

reservoirs

• If both reservoir storage and inflows are

discretized into 20 levels:

• The traditional approach, the Stochastic

Dynamic Programming (SDP) recursion,

requires enumerating all combinations of

initial storage values and previous inflows

Initial

State

1 2

M

m

T-1 T

1

System states

(initial storage

level) for

stage T

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12/19/2019 11

The introduction of the Future Cost Function avoids the need

for discretization and for assessment of all combinations

• With Dual Dynamic Programming

(DDP) the Future Cost Function (FCF)

is represented as a piecewise linear

function

• Hence there is no need to discretize

system states

• The slope of the FCF around a given

point can be obtained from the one-

stage dispatch problem

1 2 T-1 T Cost

Expected operation cost

Slope = derivation

of op. cost with

respect to storage

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12/19/2019 12

Determining the optimal hydrothermal dispatch implies

considering both current and future costs

• Solving the hydrothermal

dispatch problem is complex

due to the time-coupling

characteristics

• Optimal use of stored water

should minimize total system

operation costs

• Operators need to evaluate the

tradeoff of using the water

today or saving it for the future

0

1

2

3

4

5

6

7

Operational Cost at

Current Stage

(Immediate Cost)

Future

Operational Cost

Total Cost

MINIMUM

Storage Level at the end

of current stage

Cost

[$]

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12/19/2019 13

Assessing the trade-off between current and future costs is

challenging due to the variability of water inflows

The immediate cost function

• Is given by the thermal generation

costs required to complement hydro

production

• If more hydropower is generated in

one stage fewer fossil fuels are needed

and the immediate cost decreases but

the final storage level is lower

The future cost function

• Is associated with the expected future

thermal generation expenses

• This cost increases the lower the

storage level as less water becomes

available for future use

Due to the variability of inflows this simulation is carried out on a

probabilistic basis using several hydrological scenarios

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Cost

Stor. level

Cost

Stor. level

Cost

Stor. level

Cost

Stor. level

Cost

Stor. level

Cost

Stor. level

Month 2Month 1 Month N

Backward

recursion

Forward

iteration

SDDP leverages FCFs to enable the consideration of multiple

hydrological scenarios solvable with an iterative process

Recalculate

initial storage

levels

Iteration step Goal of the iteration

Check Repeat until target tolerance is reached

Refine FCF by

adding new

piecewise linear

functions

1412/19/2019 FOOTER GOES HERE

12/19/2019 15

The Water Value reflects the opportunity cost of the stored

water to produce electricity now or in the future

• The least cost of operation is reached when reservoirs are

at a level where the marginal immediate cost of power

generation equals the marginal future cost

• Both derivatives are known as Water Value and reflect the

opportunity cost of the stored water for considered initial

reservoir level

𝜕(𝑇𝑜𝑡𝑎𝑙𝐶𝑜𝑠𝑡)

𝜕𝑉=

𝜕(Im𝑚𝑒𝑑𝑖𝑎𝑡𝑒𝐶𝑜𝑠𝑡)

𝜕𝑉+𝜕(𝐹𝑢𝑡𝑢𝑟𝑒𝐶𝑜𝑠𝑡)

𝜕𝑉= 0

𝜕(𝐼𝑚𝑚𝑒𝑑𝑖𝑑𝑎𝑡𝑒𝐶𝑜𝑠𝑡)

𝜕𝑉= –

𝜕(𝐹𝑢𝑡𝑢𝑟𝑒𝐶𝑜𝑠𝑡)

𝜕𝑉=

$

𝑚3

ICF

FCF

Final Storage

ICF + FCF

Optimal

decision

Immediate

Cost

Function

Future

Cost

Function

Water

value

V = Stored Volume of Water in the reservoir

FOOTER GOES HERE


Table of contents

• Types of tools


• Introduction




solutions


12/19/2019 17

SDDP produces a comprehensive set of outputs characterizing

the economics of the hydrothermal power system

• For each load block and hydrological scenario:

– Spot prices, including cost of losses and congestion

– Energy dispatch (production) of each generating unit modelled

– Load flow through each modelled element of the transmission grid

– Settlement surplus by each modelled element of the transmission grid

– All “marginal costs” associated to activated constraints (dual variables)

– Fuel consumption by generating unit and fuel type

– Unserved energy (curtailments) by node if transmission grid considered

– Carbon emissions

• For each stage and hydrological scenario:

– Water value (opportunity cost of stored water)

– Reservoirs’ level at the end of each stage

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12/19/2019 18

SDDP can be used for medium term hydrothermal

dispatch optimization

• Installed capacity: 125 GW

• 160 hydro plants (85 with storage), 140 thermal plants

(gas, coal, oil and nuclear),

• 8 GW wind, 5 GW biomass, 1 GW solar

• Transmission network: 5 thousand buses

• 7 thousand circuits

• State variables: 85 (storage) + 160 x 2 = 405

• 120 monthly stages with 3 load blocks

• Number of SDDP iterations: 10

• Total execution time: 90 minutes

• 25 servers with 16 processors each

FOOTER GOES HERE

12/19/2019 19

It has been used in Central Asia on regional

integration studies

Tajikistan isolated Enhanced trade

-

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

2010 Jan

2010 M

ar

2010 M

ay

2010 Jul

2010 S

ep

2010 N

ov

2011 Jan

2011 M

ar

2011 M

ay

2011 Jul

2011 S

ep

2011 N

ov

2012 Jan

2012 M

ar

2012 M

ay

2012 Jul

2012 S

ep

2012 N

ov

2013 Jan

2013 M

ar

2013 M

ay

2013 Jul

2013 S

ep

2013 N

ov

2014 Jan

2014 M

ar

2014 M

ay

2014 Jul

2014 S

ep

2014 N

ov

[GWh]

Coal Gas Hydro RES

-

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

2010 Jan

2010 M

ar

2010 M

ay

2010 Jul

2010 S

ep

2010 N

ov

2011 Jan

2011 M

ar

2011 M

ay

2011 Jul

2011 S

ep

2011 N

ov

2012 Jan

2012 M

ar

2012 M

ay

2012 Jul

2012 S

ep

2012 N

ov

2013 Jan

2013 M

ar

2013 M

ay

2013 Jul

2013 S

ep

2013 N

ov

2014 Jan

2014 M

ar

2014 M

ay

2014 Jul

2014 S

ep

2014 N

ov

[GWh]

Coal Gas Hydro RES

• Power generation from coal runs flat being a base load

technology with low operation costs

• Gas-fired power plants adapt to changes in the load and in

the generation from hydropower

• In times of high power generation from hydropower gas-

fired generation is interrupted and coal fired becomes the

marginal technology

FOOTER GOES HERE

12/19/2019 20

And can be applied to develop power market outlooks where

other tools fail

• SDDP has been used since 2008

by Thomson Reuters to carry out

electricity market forecast in

Northern Europe

• Northern Europe presents a very

high share of power generation

from hydropower with large

storage capacities

FOOTER GOES HERE

• Link to https://www.youtube.com/watch?v=K5s98kgQJ6Q

• Only until time 1:14


https://www.youtube.com/watch?v=K5s98kgQJ6Q


Table of contents

• Types of tools


• Introduction




solutions


12/19/2019 23

PLEXOS does not have a strong hydropower focus but allows

co-optimizing power, water supply and gas systems

• Replace different tools with one integrated hub

– Co-optimization across electric power, water and gas

systems

– Four integrated tools: long-term, PASA, medium-term

and short-term scheduling

– Pass data across phases from long-term through short-

term

• Provide transparency for how the models are solved

– PLEXOS shows you its calculations

– Credible sources for audits and documentation

• Run your scenarios in minutes instead of hours

– Leverages innovations in distributed computing and

parallelization

FOOTER GOES HERE

12/19/2019 24

Plexos is used all around the world

• Worldwide installations of PLEXOS exceed 1060 at more than 175 sites worldwide in 37 countries.

• Users: Power Generation Companies, Transmission System Operators (TSOs), Independent System

Operators (ISOs), Electricity and Gas Market Operators, Energy Commission and Regulators, Price

Forecasting Agencies, Power Plant Manufacturers, Consultants, Analysts, Academics & Research Institutions

FOOTER GOES HERE

• Link to https://www.youtube.com/watch?v=bfnAhrHHrIo

• Full video


https://www.youtube.com/watch?v=bfnAhrHHrIo


Table of contents

• Types of tools



12/19/2019 27

Profit maximization models optimize the operation of power

generators for an expected market price

0

50

100

150

200

250

300

350

400

1 5 9

13

17

21

25

29

33

37

41

45

49

53

57

61

65

69

73

77

81

85

89

93

97

101

105

109

113

117

121

125

129

133

137

141

145

149

153

157

161

165

0

10

20

30

40

50

60

70

80

90

Po

we

r G

en

era

tio

n /

Sto

rage

[M

W]

Syst

em

Pri

ce [

EUR

/MW

h]

Pump Generation Price

FOOTER GOES HERE

12/19/2019 28

Portfolio optimization tools leverage profit maximization

models to automate power market participation

Forecast

Inflow Demand Price Wind Weather

Long/Medium Term Decision

Support

Cross Market Short Term Decision Support

Outage and limitation scheduling

Availability

planning

Restriction

handling

Long term

reservoir

management

Fuel contract

handling

Resource

value

Bilateral contracts

Long term earning forecast

Establish

optimal bids

Day ahead

market

Bilateral

trading

Sending and

receiving

bids

Optimize

production plan

Hydro

Thermal

Send ancillary

service data

to TSO

Operation –

Monitoring and

replanning,

including intraday

markets

Optimize bids

for balancing

market

Sending

bids

FOOTER GOES HERE

The bids are presented prior sending them

to the electricity market


• Link to: https://www.youtube.com/watch?v=lXPe5EStlHI

• Full video


https://www.youtube.com/watch?v=lXPe5EStlHI

Thank you for your

attention

Any question?


32

Thanks for your

attention

software tools and solutions for hpp operation optimization

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