LOGO Experience of development and application of the optimization models for strategic planning in the power sector under the recent technological, economic.

LOGO

Experience of development and application of the optimization models for strategic planning in the power sector under the recent technological, economic and environmental challenges

Fedor VeselovAlla MakarovaAndery Khorshev

Seminar «Project for Kazakhstan energy system modeling: results and plans»

Kiev, May 16, 2012

Energy Research InstituteRussian Academy of Sciences

LOGOERI RAS – experience in system energy studies

Energy Research Institute RAS

Energy Research Institute of the Russian Academy of Sciences (ERI RAS) was established in 1985 for the fundamental studies in the area of national energy policy development and implementation:

state level - methodological, modeling and analytical support for the energy policy priorities and implementation mechanisms (incl. macroeconomic, technological, pricing, environmental and other aspects), quantitative elaboration of the economy and energy sector scenarios in the context of Energy Strategy

Ministry of Energy, Ministry of economic development, Ministry of natural resources, Federal Antimonopoly Service

corporate level – capacity building, modeling and information support of the strategic planning system of leading energy companies, justification of investment and market policy under the energy markets transformation processes

Gazprom, Gazexport, NovaTEK, Mezhregiongas, Wintershall, Roneft, TNK-ВР, SUEK, RAO EES Rossii, Rosenergoatom, Fortum

LOGOSCANER – multi-functional system of models for the investigation of the global and Russian energy sector development


«SCANER» is a tool for the system analysis of the Russian energy sector development for the mid- and long-term prospects (to 2030-50) as an important part of national economy and global energy markets. Integrating the powerful modeling and informational resources, SCANER provides:

Unique informational support to the analysis and forecasts (regularly updated databases on the national and regional economy, energy sector, energy balances and markets)

Multi-level co-ordination system of energy forecasts focused on the formulation of rational variants of the economy, energy sector and energy companies’ development

Huge flexibility and fast adaptation of the models and their calculation modes under the separate forecasting requirements

LOGO

Forecast of the financial feasibility by energy industries and companies

Forecast of the financial feasibility by energy industries and companies

Parameters of the global economy and energy sector development scenarios

Parameters of the global economy and energy sector development scenarios

Parameters of the Russian economy and energy sector development scenarios

Parameters of the Russian economy and energy sector development scenarios

Forecast of global energy markets development and

regulation environment

Forecast of global energy markets development and

regulation environment

Formulation of integrated target parameters for the

economy and energy sector development

Formulation of integrated target parameters for the

economy and energy sector development

National and regional forecast of the economic and technological development

National and regional forecast of the economic and technological development

National and regional fuel and energy demand forecast

with estimation of energy saving and efficiency

improvements

National and regional fuel and energy demand forecast

with estimation of energy saving and efficiency

improvements

Estimation of resources and

reserves for fuel supply industries

Estimation of resources and

reserves for fuel supply industries

Forecast of energy demand and prices by

countries

Forecast of energy demand and prices by

countries

Power sectorPower sector Oil and gas sector

Oil and gas sector Coal sectorCoal sector

Forecast of production and financial programs by energy industries

Forecast of production and financial programs by energy industries

Forecasted investment programs by energy

industries and companies

Forecasted investment programs by energy

industries and companies

Domestic fuel and energy prices’ forecast

Domestic fuel and energy prices’ forecast

National and regional energy balances

National and regional energy balances

Estimation of priorities for

new technologies

Estimation of priorities for

new technologies

Estimation of the impact of pricing and investment policy in energy

sector on the economy

Estimation of the impact of pricing and investment policy in energy

sector on the economy

Recommendations for the national energy policy improvements

Recommendations for the national energy policy improvements


SCANER – multi-functional system of models for the investigation of the global and Russian energy sector development

LOGO


Joint optimization of power sector structure with the gas and coal production and transportation system development provides opportunities:

• To form the core of the national and regional energy balances, incl. electricity, heat, gas and coal supply and demand.• To obtain the system of equilibrium wholesale prices by the regions of Russia on the basis of long-term fuel and electricity supply costs• To assess the long-term elasticity of fuel demand in electricity and heat production affected by the prices, cost and environmental factors

Power sector structure optimization as a part of national energy sector development

Fuel consumption at power plants and

boilers

Cond. Therm

alCHP

Boilers

Hydro, Nuclear,

RES

Other domestic

fuel consump-tion and export

Electricity demand

Heat demand

Gas balances

Fuel oil balances

Electricity and electric capacity balances

Centralized heat supply balances

Final energy demand

simulation models

Fuel demand models

Electricity demand model

Heat demand model

Steam coal balances

Gas production and

transportation

Fuel oil production and transportation

Coal production and

transportation

Oil sector development optimization

system

Coal sector development

simulation system

Gas sector development optimization

system

Fuel demand models


Heat demand model

Fuel demand models


LOGO

Capacity, electricity and heat production structure is formed under the optimization of capital and operational costs (or revenue requirement) of different types of investment alternatives (excl. distributed generation): life extension and rehabilitation of the existing capacities new CHP and/or boilers intersystem grid reinforcement new gas, coal and nuclear technologies renewable technologies

System assessment of the investment decisions is preformed under the uncertainities of: electricity and centralized heat demand fuel supply infrastructure development fuel pricing mechanisms (coat plus, netback of inter-fuel competition) GHG emission limitations and carbon prices Capital expenditure limitations

In the optimization model investment and production decisions are defined by the system of balances: electricity centralized heat (by types of towns and cities) installed capacity requirements (for peak and off-peak hour) fuel supply and demand

Production unit(regional electricity and

capacity balances

Investment unit(investment alternatives for the

existing and new plants)

Fuel supply unit(fuel demand, supply and

prices/ fuel balances)

Balance requirements and capacity additions

Variable fuel demand in the sector (incl. fuel substitution)

Power plant capacities

Distributed capital expenses for future additions

Fuel production and transportation capacities

Year T Year T+1Year T-1

Production unit(regional electricity and

capacity balances

Investment unit(investment alternatives for the

existing and new plants)

Fuel supply unit(fuel demand, supply and

prices/ fuel balances)

Balance requirements and capacity additions

Variable fuel demand in the sector (incl. fuel substitution)

Power plant capacities

Distributed capital expenses for future additions

Fuel production and transportation capacities

Year T Year T+1Year T-1


Dynamic aspect and area of optimization (EPOS)

Dynamic links ensure to assess the efficiency of these decisions on the whole planning horizon (taking into account the 10-15 years end-effect in costs)

LOGO

Optimization and simulation models can operate with different regional detailing level of the Russian Unified Electricity System: 7 Integrated Power System 42 balancing zones based on the main grid congestions 29 Free Capacity Flow zones assigned by the System Operator for the competitive capacity market results are additionally detailed by the simulation model (ELIS) to the level of administrative units and converted in the form of regional electricity and centralized heat balances

Generating capacities are modeled with the different detailing: aggregated technologies: 10-15 types of existing and 15-30 types of new technologies power plants: over 400 existing plants and over 150 investment projects of repowering, brown- and green-field unit construction

600

2500

0

Belarus

Kola

Karelia

LeningradPskov

Novgorod

Finland

Kaliningrad

ОЭС Балтии

Tver

Vologda

Arkhangelsk Komi

Yaroslavl

Smolensk

KalugaTulaRyazan

Moscow

BryanskOryolKursk

BelgorodVoronezhTambovLipetsk

Ukraine

UlyanovskPenza

Mordvinia

Nizhny novgorod

KostromaIvanovoVladimir

VolgogradAstrakhanKalmykia

RostovStavropol

Karachayevo-cherkessiya

Kuban

Georgia

Kabardino-balkariaOsetia

ChechnyaIngushetiaDagestan

Azerbaijan

SaratovSamara

Mari ElChuvashia

KirovUdmurtiya

Tatarstan

Bashkortostan

Orenburg

Perm

Kazakhstan

ChelyabinskKurgan

Sverdlovsk

Tyumen

KhakassiaTyva

Omsk

Tomsk

NovosibirskAltayKuzbas

Krasnoyarsk Irkutsk

BuryatiaChita

Chita Amur Khabarovsk Primorskykray

Yuzhno-yakutskiy

energoregionSouth IPS

North-West IPS

Center IPS

Volga IPS

Ural IPS

Siberia IPS

Far East IPS

600

2500

0

Belarus

Kola

Karelia

LeningradPskov

Novgorod

Finland

Kaliningrad

ОЭС Балтии

Tver

Vologda

Arkhangelsk Komi

Yaroslavl

Smolensk

KalugaTulaRyazan

Moscow

BryanskOryolKursk


Ukraine

UlyanovskPenza

Mordvinia

Nizhny novgorod



RostovStavropol


Kuban

Georgia



Azerbaijan

SaratovSamara

Mari ElChuvashia

KirovUdmurtiya

Tatarstan

Bashkortostan

Orenburg

Perm

Kazakhstan

ChelyabinskKurgan

Sverdlovsk

Tyumen

KhakassiaTyva

Omsk

Tomsk


Krasnoyarsk Irkutsk

BuryatiaChita


Yuzhno-yakutskiy

energoregion

600

2500

0

Belarus

Kola

Karelia

LeningradPskov

Novgorod

Finland

Kaliningrad

ОЭС Балтии

Tver

Vologda

Arkhangelsk Komi

Yaroslavl

Smolensk

KalugaTulaRyazan

Moscow

BryanskOryolKursk


Ukraine

UlyanovskPenza

Mordvinia

Nizhny novgorod



RostovStavropol


Kuban

Georgia



Azerbaijan

SaratovSamara

Mari ElChuvashia

KirovUdmurtiya

Tatarstan

Bashkortostan

Orenburg

Perm

Kazakhstan

ChelyabinskKurgan

Sverdlovsk

Tyumen

KhakassiaTyva

Omsk

Tomsk


Krasnoyarsk Irkutsk

BuryatiaChita


Yuzhno-yakutskiy

energoregionSouth IPS

North-West IPS

Center IPS

Volga IPS

Ural IPS

Siberia IPS

Far East IPS


Technological and regional representation of the power sector (EPOS)

Free capacity flow zones (ZSPM)

Representation of the Unified Power System (UPS) by integrated power systems (IPS) and balancing zones

LOGO


Representation of power plant (i) operation modes (j)

Xit

Xi1t Xi2t … XiJtOperation modes

Installed capacity

Electricity production

Total fuel consumption

Fuel 1 consumption

Fuel N consumption

. . .

h1

b1*h1

11*b1*h1

…

N1*b1*h1

h2

b2*h2

12*b2*h2

…

N2*b2*h2

hJ

bJ*hJ

1J*bJ*hJ

…

NJ*bJ*hJ

…

Installed capacity requirements

Electricity supply/demand balance

Fuel 1 supply/demand balance

…Fuel N supply/demand balance

n nj = 1 for each fuel mix

LOGO


Representation of capacity development

Xit+1 = Xit - Decommit,t+1

Existing capacities

Xit+1 = Xit + Additionit,t+1

New & rehabilitated capacities

Condition for total capacity of rehabilitated alternatives (k) for existing plant (i)

kAdditionkt,t+1 ≤ Decomm it,t+1

LOGO


Capacity constraints

Matrix representation of plants in the system of capacity constraints

Coal CCGT Nuclear CHP Hydro pump strorage

GT (peak)

Wind

Electricity supply/demand balance 4,0-6,5 3,0-6,5 7,3-7,6 4,0-6,0 -0,25 0,5-1,5 0,2

Installed capacity requirement 1.0 1.0 1.0 1.0 1,0 1,0 -

Rated peak capacity requirement 0.912 0.898 0.907 0.91 1,0 1,0 -

Rated off-peak capacity requirement 0.456 0.449 0.907 0.783 -1,2 0 -

New peaking capacity requirement - - - - 1,0 1,0 -

Pmax

Pmin

NreqReserve margin

Installed capacity requirement

Nreq = Pmax + ReserveMargin

Rated capacity requirement for a peaking hour (max load requirement)

Rated capacity requirement for an off-peak hour (min load requirement)

Existing hydro and other peaking capacities

New peaking capacity requirement

LOGO


Representation of heat supply

Matrix representation of CHP capacity in the system of heat balances

Existing CHP

Rehab. of exist.

CHP

New CHP-1 New CHP-2

For class 1

For class 2

For class 3

For class 2

For class 3

Steam turbine

Comb cycle

Comb cycle

Comb cycle

Comb cycle

Gas turbine

Gas turbine

Heat balance for load class 1 0,2*8 0,2*5 5

Heat balance for load class 2 0,5*8 0,5*5 5 9

Heat balance for load class 3 0,3*8 0,3*5 5 9

Heat production in the area of existing CHP

8 6

• different heal load classes (separate balances)

• different set of heat supply alternatives (CHP and boiler technologies) for each heat load class

• heat supply alternatives can be used for different heat load classes, but with different heat distribution costs

• heat-driven rehabilitation for existing CHP – electricity is considered as by-product of the required heat production

LOGO


Analysis of dual solution

Primal LP task solutioncapacity and generation structure, supply/demand balances of all considered energy resources

Dual LP task solutionsystem of “shadow” prices of energy resources (electricity, capacity, heat, fuels)

Static LP task - short-term (spot) marginal pricingDynamic LP task - long-term (spot) marginal pricing

Post-optimization analysis of dual solution and “shadow” prices’ structure required the investigation of basic variables, their impact on matrix of LP task and cost function:

= cb B-1

LOGO


Modeling pricing rules at the energy markets

EPOS allows to investigate different pricing models for fuel industries and power sector based on the long-term marginal costs

Gas pricing model Source of marginal costs

Cost plus Gas fields and new pipelines

Netback Export routes and prices

Inter-fuel competition Gas substitution/saving in the power sector

Power plants operates at several markets with different pricing models

Product Pricing model EPOS representation of the market

Electricity Competitive + (Supply/demand balance)

Capacity Competitive + (Supply/demand balance)

Heat Regulated + (Supply/demand balance)Long-term efficiency of plant operation (revenues-costs) can be evaluated on the basis of variable reduced costs

LOGO

Knowledge baseLibrary of the formation methods

(modules) of the LP model matrix elements

LP taskMatrix and RHS coefficients of the

liner programming task

(# of equatuins – up to 150 000# of variables- up to 300 000

# of non-zero elements – up to 1 500 000)

Subject areaHierarchical stratified database

Operation and fuel supply modes

(~6500 variants of the capacity factor and fuel supply mix modes)

Equipment groups(~2500 groups of units with the

same equipment type and existing/new state)

Power plants (~600 existing and new

plants)

~ 80 regional systems

(RF administrative units)

Energy companies(22 GenCos, indep.

producers and utilities)

Generating technologies (~20 per region)

7 IPS (42 nodes, 29

free flow zones)

CountryIndustry

Linear Programming (LP) ModelDatabase of the mathematical

LP model coefficients(by LP matrix fragments and variants)

System of automatic formulation and information support of the optimization models and multi-case runs (EPOS family)


Automatization of interaction between post-relatinal and relational databases and an interface openess ensure the high flexibility and efficiency of new models and solution reports creation

LOGOTechnology of prompt matrix generation / transformation for EPOS family


Types of LP matrix transformation

• recalculation of coefficients (RHS) for existing variables (constraints) without changes of dimension

• simple changes of dimension without changes of the matrix structure - addition of variables (constraints) of existing types

• complex changes of dimension with the changes of the matrix structure - addition of variables (constraints) of new types

EPOS modeling system

Alternative algorithms for separate matrix coeffs, bounds and RHS calculation from initial input data

Free fragmentation of LP matrix elements in the database

Automatic assembling of the whole LP matrix from its fragments in the database

Opened for used and time saving technology will not require regular general

recalculations of input data

LOGOConclusion. Financial aspects of power sector optimization


Market structure and pricing rules

Technological structure

and fuel mix

Profitability of investments and

capitalization growth in the sector

Joint (iterative) analysis of EPOS results and financial models of energy companies

Agent-based approach to simulation of the investment decisions and market evolution

At present

In the future

LOGO

Energy Research Institute of [email protected]

Veselov Fedor, PhD economics, Head of Department

[email protected], [email protected]

Makariva Alla, PhD economics, Head of Laboratory [email protected]

Khorshev Andrey, PhD economics, Head of Laboratory [email protected]

LOGO Experience of development and application of the optimization models for strategic planning in the power sector under the recent technological, economic.

Documents

energy industries

estimation of energy

energy balances

energy sector scenarios

energy demand forecast

energy policy priorities

russian economy

national economy