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generation and interconnection capacity expansion planning model

Objective                                                                      Input and
                                                                               ? output files in CSV format, making possible the
                                                                                   edition with Excel
OPTGEN is a computational tool that determines the least-cost                  Data import from either Super Olade’s MODPIN or SDDP
expansion plan for an electricity-natural gas multi-region system.
The system operation is represented in detail, including, for
example, inflow uncertainties, greenhouse gases emissions and                  Integration with SDDP
minimum capacity constraints, among others.
                                                                               OPTGEN can be integrated with the detailed transmission-
                                                                               constrained stochastic hydrothermal dispatch model SDDP.
OPTGEN can be used by either planners (in centralized decision
environments) or electricity regulators and investors (in compe-
titive environments).

Modeling Aspects
OPTGEN is an integrated expansion model formulated as a large-
scale mixed integer-linear optimization problem, with the following

? of investment and operation time steps (year,
     semester, quarter and month)
Both continuous and integer decision variables
? or compulsory projects
? associated and mutually exclusive projects
Sets of                                                                        Recent Applications
Precedence of construction constraints
? installed capacity constraints for different groups of
Minimum                                                                        SEETEC
                                                                               ? project to study the development and benefits of the
     technologies and for different time intervals, allowing the                  Balkan regional energy market, with 8 interconnected
     representation of governmental energy policies                               countries, 30 GW demand (5 GW of forecasted increase by
Calculation of reference costs for candidate projects
?                                                                                 2010)
Greenhouse gas emissions modeling
                                                                               ? studies for the Brazilian system, with 100 GW
Fuel availability constraints
                                                                                   installed capacity, 85% of which is hydroelectric (117 hydro
? scenario analysis
                                                                                   plants),108 thermal plants and 9 interconnected regions
? and reinforcement of user provided expansion plans

                                                                               Venezuela’s 2020 generation and transmission expansion plan
The solution is obtained by advanced techniques of mixed-integer
                                                                                  with 13 interconnected regions
programming and Benders decomposition.
                                                                               ? integrated generation-transmission ten-year
                                                                                  expansion plan
System Characteristics
                                                                               Study of
                                                                               ? interconnections between Egypt, Sudan and Ethiopia,
? compatible user interface
Windows                                                                           with the evaluation of large-size hydro plants
? model for visualization of results and generation of graphs

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physical-financial asset optimization and risk management

 General Features                                                              The optimal solution is obtained through mixed linear-integer
                                                                               programming techniques.
 OPTFOLIO is an analytical tool for the management of energy
 portfolios composed of both physical assets (power plants) and                Another important feature of OPTFOLIO is a financial simulator, in
 financial (bilateral contracts and other derivatives, such as options)        which the user specifies a portfolio of short, mid and long term
 assets.                                                                       contracts and simulates their performance for different scenarios.
                                                                               The following types of instruments are contemplated:
 The spectrum of decisions to be optimized covers short, medium
 and long term horizons, including investment in new equipment,                Bilateral
                                                                               ? contracts and options
 selection of contract portfolios, and purchase of hedge instruments.
 The objective is to maximize the revenues of an agent (generator,             Contracts
                                                                               ? with optionality clauses associated to energy
 distribution company or trader) subject to risk constraints, e.g.                  modulation (e.g. peak, off-peak) and seasonal allocation
 minimum profitability per period and/or during several time periods,
 considering different types of criteria such as utility functions,            Swaps
 value at risk (VaR) and conditional value at risk (CVaR).
                                                                               ? contracts
 Represented Features
                                                                               ? for risk sharing with respect to spot prices
 The model has the following input data:
                                                                               Take-or-pay contracts
 ? spot prices scenarios

 ? generation assets and sale/purchase contracts
                                                                               Computational Environment
 Set of candidate plants – to be either built or purchased, and
      of new financial instruments (contracts and options)                     Windows-based user friendly interface

 Risk constraints
 ?                                                                             Input and
                                                                               ? output files in CSV format managed by Excel
 OPTFOLIO provides the following results:
                                                                               ? with SDDP and SCE models (also of PSR), with
 ? decisions, such as the sequence of plants to be built
 Optimal                                                                           external simulation models (Newave) and simple Excel
      and financial instruments (contracts / options) to be signed                 spreadsheets

 Probability distribution of revenue stream and of project’s
      internal rate of return (IRR)
                                                                               Recent Applications
 Risk statistics (monetary value, VaR, downside risk etc.)
                                                                               OPTFOLIO has been used to determine the optimal hydrothermal
      associated to the cash flow analysis
                                                                               mix for generation utilities; to establish short, medium and long
                                                                               term contracting strategies for energy generators and traders and to
 ? of the company, considering tributary aspects and
                                                                               evaluate the risk profile of generation assets in various countries.
      sector regulations (e.g. charges)
                                                                               Other recent use has been the determination of attractiveness of
                                                                               firm energy options for distribution companies and large loads that
 ? prices and option contract premiums
                                                                               would promote capacity expansion in the Colombian market.

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transmission constrained stochastic hydrothermal dispatch model

 Objective                                                                     Results
 SDDP is a stochastic hydrothermal dispatch model, with the                    SDDP results produced by SDDP are in CSV-format files. These files
 representation of the transmission network and gas pipelines, used            are managed by a graphical interface (GRAPH program) which
 in long, medium and short term operation studies. The model                   processes the desired results, graphing them in Excel files. SDDP’s
 calculates the least-cost operation policy of a hydrothermal power            main results are:
 generation system, taking into account the following aspects:
                                                                               ? operation statistics: hydro and thermal
 ? details of hydroelectric plants: hydraulic balance,                         generation, thermal production costs, energy
 storage and flow rate limits through turbines, spillways, head                interchanges, circuits flows, fuel consumption, risk of
 effect and others                                                             deficit and unserved energy
 ? model of thermoelectric plants: unit commitment, take                       Locational marginal costs (for each region or bus)
 or pay contracts, fuel availability constraints, efficiency curves,           Capacity
                                                                               ? marginal costs: measures the benefit of
 multi-fuel plants and others                                                  reinforcing a resource, such as the installed capacity of a
 Representation of spot and energy contracts markets
 ?                                                                             thermal plant, the turbine capacity of a hydro plant, the
 Hydrological uncertainty: stochastic inflow model representing
 ?                                                                             storage capacity of a reservoir or the capacity of a circuit.
 hydrological system characteristics such as seasonality, time                 These indices are used to signal effective reinforcements
 and spatial inflow correlations and droughts                                  for the system
 ? transmission network: Kirchhoff laws, power flow
 limits in each circuit, losses, security constraints, limits on
 export and import among electric areas, sum of flow
 constraints and others
                                                                               SDDP applications
 Load duration curve represented by blocks either at the system
 ?                                                                             SDDP has been used for operations planning and production
 level or in each bus (if transmission is considered), using                   costing studies in more than 30 countries, such as:
 monthly or weekly time steps
 ? of the natural gas pipeline network with gas                                All countries in South and Central America
 production and transportation constraints, production capacity
 in the fields, capacity, pipeline flow limits and losses. Natural             United States and Canada
 gas demands in each node are given by the thermal plants’
 production and “non-thermal” consumption (industrial,                         Austria,
                                                                               ? Spain, Turkey, Norway (Nordic region) and Balkan
 residential, etc.)                                                                region (ten countries)

 In addition to the least-cost policy, SDDP calculates economic                New Zealand and several provinces in China, including
 indices, such as load marginal costs in each region in case of a                  Sichuan, Shanghai, Guangdong and Shandong
 simplified energy interchanges model or in each bus in case of a
 transmission network wheeling rates, transmission congestion                  SDDP is also used:
 costs, water values in each hydroelectric plant, marginal cost of
 fuel constraints, etc.                                                        By the dispatch centers of Bolivia, Colombia, Chile, Guatemala,
                                                                                   El Salvador, Ecuador, Nicaragua, Panama, Peru and Venezuela
 Because the solution methodology is based on decomposing the
 orginal problem into smaller-size sub-problems, computational                 For valuation studies for new hydro and thermal power plants,
 efficiency may be increased if the parallel version of SDDP is used.              assessment of regional markets and international
 In this version, the sub-problems are solved simultaneously by                    interconnections in various Latin American, European and
 several computers connected by a local network or in a multi-task                 Asian countries

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short term energy scheduling

 Objective                                                                      Hydro unit
                                                                                ? optimization, considering the variation of the turbine-
                                                                                    generator efficiency versus turbined outflow, tailwater elevation,
 NCP determines the transmission-constrained least cost hydro-
                                                                                    head versus storage relationship in the reservoir, hydraulic head
 thermal dispatch for a horizon of up to two weeks using hourly time
                                                                                loss in the penstock and generation units
 steps. NCP can also be used to determine the revenue maximization
                                                                                ? zones of production for hydro plants
 strategy for companies in competitive markets, such as the NordPool.
                                                                                The optimum solution is obtained through advanced techniques of
 NCP minimizes thermal production costs (variable costs and start-up            mixed-integer programming.
 costs) and penalties associated to the violation of operational constraints,
 such as minimum outflows or energy rationings. NCP can be integrated
 with mid-long term models such as SDDP by importing the future cost (or
                                                                                System Characteristics
 benefit) function for the end of the first week or month. This function can    Windows
                                                                                ? based user friendly interface
 be “plugged” at the end of NCP planning horizon and is associated to the       Module
                                                                                ?for graphing output results, which include: hydro and
 reservoirs end storage vector. NCP’s revenue maximization mode works               thermal power, marginal costs in each bus, circuits power
 similarly to the least cost mode. The only difference is that exogenous            flows and losses, start-ups and decisions, operating costs, load
 spot price scenarios must be provided.                                             rationing, stored volumes, turbine and spillway outflows, and
                                                                                    many others. Results are given in hourly steps

Modeling Aspects
                                                                                Integration with Other Models
 NCP is formulated as a mixed-integer optimization problem, with
 the following characteristics:                                                 As mentioned, NCP can import future cost functions (water values)
                                                                                from SDDP and other models.
 Active hourly power balance in each bus bar of the
     transmission system, including Kirchoff laws, transmission                 NCP results, based on an active power flow model, may be used by
     capacity constraints and circuit losses resulting from the                 OptFlow - optimal AC power flow model also developed by PSR.
                                                                                OptFlow verifies additional network constraints (e.g. voltage levels)
     optimum power flow
                                                                                and indicates requirements for reactive support.
 ? balance for hydro plants in cascade, including travel
     times from upstream to downstream stations and wave
                                                                                NCP is integrated to ePSR – the Oracle-based application developed
 propagation effect
                                                                                by PSR. ePSR has a common interface, database and file sharing
 ? and maximum production for hydro and thermal plants
                                                                                system and is responsible for the management of energy planning
 Commitment-type decisions, ramp constraints, minimum up-
                                                                                studies made with both SDDP and NCP. ePSR also integrates NCP’s
     time and down-time constraints, maximum up-time constraint,                daily or weekly dispatches to external SCADA platforms.
     maximum number of start-ups for the study horizon or in each
     day, initial conditions (if plants are on/off in the beginning of the
 study and for how long they have been in that state)                           Recent Applications
 ? and maximum reservoir storage, alert and flood
                                                                                NCP is the
                                                                                ? official dispatch model in Bolivia and Ecuador and is
     control storage, irrigation, minimum and maximum total
                                                                                in the process of becoming the official model in Peru, Costa
 outflows, minimum and maximum turbine outflows
                                                                                Rica, Nicaragua, Dominican Republic and Guatemala
 Target generation constraints (at least, at most and exactly
                                                                                Used by
                                                                                ? generation utilities in Turkey
     types) for a user-provided timeframe within the study (horizon)            Used in
                                                                                ? Albania, Bosnia & Herzegovina, Bulgaria, Macedonia,
     and for a set of selected hydro and/or thermal power plants                Romania, Slovenia, Serbia and Montenegro in the activities
 Target (end of horizon) reservoir storage constraints
 ?                                                                              related to the SEETEC Project
 ? constraints (different types of reserve criteria)                            Used in
                                                                                ? Norway for maximizing revenues in the Nordpool

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simulator of the Brazilian electric power commercialization chamber – CCEE

 Background                                                                    algebraic rules which eventually guided a large agreement
                                                                               between Generation and Distribution companies that prevented a
 The objective of the original development of SCE in 1998 was to               complete halt of the MAE activities
 implement the algebraic rules of the Wholesale Electricity Market             To study
                                                                               ? contracting and risk control strategies for investors,
 (MAE). After the “second generation” of the Brazilian Reform, the             generation concessionaires and energy traders
 original program was updated in order to simulate the rules of the            To study
                                                                               ? the generation utilities contracting strategy in the
 then newborn CCEE (electric power commercialization chamber) in               auctions for “new energy” and “existing energy”, such as the
 2004. Among the most important rules are the energy reallocation              3,100 MW Santo Antonio hydropower auction (in 2007) and the
 mechanism (MRE), the systems service charge (ESS), the surplus                3,500 MW Jirau hydropower auction (in 2008), both at the Rio
 allocation to mitigate the contracts exposure and the risk sharing            Madeira, an Amazon tributary
 mechanisms to mitigate price differentials derived from the contracts
 between generation and distribution companies in the regulated
                                                                               Present use of the model
 market (CCEAR). The result is a tool that simulates the Brazilian
 Market rules coupled with simulation models (such as NEWAVE or                SCE is integrated to the set of models developed by PSR, in
 SDDP), guiding the economic evaluation of generation, distribution            particular to SDDP, OPTFOLIO and OPTVALUE. The objective is to
 and trading companies. SCE results are often used as inputs for the           advise utilities on their energy contracting strategies in the auctions
 investment decisions, or for devising contracting strategies or for           and on their investment decisions. SCE is also fully compatible with
 helping bidders in the electricity auction in Brazil..                        the tools being used in the Sector, such as the NEWAVE model.

 Historically, SCE was developed for the following purposes:
                                                                                                       SDDP               NEWAVE

 To assist
 ? in the economic analysis of generation utilities
 privatized in the FHC Government. The first version of the                                                       SCE
 program was developed in the second semester of 1998 for the
 privatization of the 5918 MW Gerasul utility (now Tractebel).
                                                                                                      OptFolio            OptValue
 Later, it was utilized for the analysis of 2237 MW CESP
 Paranapanema utility (now Duke Energy Brasil) and the 7455
 MW CESP Parana, whose privatized halted                                       SCE Results
 SCE was
 ? also used as “laboratory” to simulate different
 alternatives for MAE rules. In this regard it should be emphasized            Results produced by SCE are in CSV-format files. These files are
 that PSR has been consultant to several institutions, such as: the            managed by a graphical interface (GRAPH program) which retrieves
 MME (Ministry of Mines and Energy), ANEEL (National Agency of                 or processes the desired results from the CSV files, graphing the
 Electric Power), ONS (National System Operator), BNDES                        results in Excel, where the data becomes available and can be easily
 (National Development Bank), former Wholesale Energy Market                   edited. SCE main results are:
 Service Administrator (former MAE, now CCEE). As an example,
 of this usage, there are the studies with SCE to analyze different            MRE energy credit, generation outside MRE and GSF (assured
 alternatives for the energy reallocation mechanism (MRE),                         modulated energy allocation factor)
 number of sub-markets (price regions), effects of the Annex 5                 Total net
                                                                               ? contracts and energy balance at CCEE
 clause of the initial contracts, allocation rules for the exposure of         Net Revenues in each sub-market and contracts revenues for
 the market participants due to price-differentials among the sub-                 CCEAR (regulated environment) PPAs
 markets and allocation of trans-mission surplus (congestion                   Financial
                                                                               ? exposure to the MRE, allocation of the ESS (energy
 revenues)                                                                         service charges)
 To assist
 ? the Energy Crisis Management Chamber (2001) during                          Transmission surplus (congestion revenues) and allocation
 and after the energy rationing in Brazil in the presentation of               Risk-sharing adjustments among distribution companies for the
 proposals to revitalize the electricity sector. On this occasion,                 regulated market contracts and final negative exposure of each
 SCE was used to investigate different alternatives for MAE                        distribution company

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economic-financial evaluation of generation projects under uncertainty

 General Features                                                              OptValue produces the following outputs:

 OptValue is a computational tool for the risk-constrained economic-           Indices applied to the Brazilian energy auctions, such as the
 financial analysis of generation projects. Some of the available                  project’s physical guarantee (GF), variable operation cost (COP),
 features are the pricing of different types of energy contracts, or               revenue in the spot market (CEC) and cost-benefit index (ICB)
 PPAs, that will guarantee an internal rate of return (IRR) with a
 given probability, the calculation of the IRR for a contract with a           Investor
                                                                               ? annuity (for capacity contracts), associated to an IRR
 given price and the calculation of the project’s expected                         and to a cost-benefit index (equivalent to a fixed revenue to be
 investment costs needed to guarantee the IRR, given PPAs prices.                  bidden at energy auctions)

 Different generation technologies can be evaluated, which makes it            IRR and
                                                                               ? NPV cumulative probability distributions derived from
 possible to price several uncertainties, such as those related to                 the simulated scenarios
 investment costs, delays in operation start-up, exchange rate risk
 and hydrological risk.                                                        Optimum
                                                                               ? contracting amount for hydraulic projects,
                                                                                   considering the relevant risks, e.g. hydrological risk, risk of
 The evaluation is made through probabilistic simulation. As a result,             delays in operation start, and others
 OptValue builds the distribution probability of the IRR, which allows
 one to analyze the risks of each specified technology and scenario.           Contract
                                                                               ? price break-down in: Investment, Taxes, Charges,
                                                                                   O&M, Fuel, TUST (transmission system tariff)

                                                                               ? Statements: Company Cash Flow, Shareholder Cash
 Modeling Aspects
                                                                                   Flow, Income Statement, Balance Sheet and Dividend Flow
 The model has the following input data:
                                                                               Charts of
                                                                               ? time series associated to the plant dispatch,
 ? number of generating units and their respective
 Plant type,                                                                       allocated energy, surplus, energy reallocation mechanism
     operation start-up schedule                                                   (MRE) revenues, purchases and sales at CCEE (electric energy
                                                                                   trading chamber), shareholder’s cash flow
 Project life
 ? span, contract type and duration

 ? variable O&M costs, fuel contract characteristics
 Fixed and                                                                     Computational Environment
     (e.g. cost, flexibility and take-or-pay clauses)
                                                                               The model
                                                                               ? input and results are managed by an Excel interface

 ? of future energy spot prices

 Investment schedule, aggregated or independent, for each
 ?                                                                             Recent Applications
     account comprising the budget and the maintenance CAPEX
                                                                               OptValue has been applied to calculate energy prices of new
 ? loan payment schemes, such as constant
 Different                                                                     generation projects, assisting investors on making decisions at
     amortization, IFC loans, PRICE and BNDES (Brazilian                       energy auctions and on their capital allocation decisions. Other
     development bank)                                                         applications of OptValue include the analysis of risk factors and risk
                                                                               premiums for each technology, such as bioelectricity,
 ? sector-related charges
 Taxes and                                                                     hydroelectricity, wind power or thermal power (nuclear, gas, coal,
                                                                               oil and diesel-fired plants).

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corporate management system for energy planning applications

 Objective                                                                     Constraints: operational rules which constrain the power dis-
                                                                               patch, such as reservoir operation constraints, individual or
ePSR is an integrated computational environment for the collabo-               combined generation limits for the power plants, spinning
rative development of energy studies. Using a comprehensive                    reserves, unit commitment constraints, transmission security
central database, ePSR architecture integrates PSR applications                constraints, and many others
and is designed to facilitate integration with third party                     Study Management: a case study is defined by selecting infor-
components, such as ERP systems.                                               mation from available configurations, historical data, scenarios,
                                                                               and constraints, previously defined from the database.
 ePSR is a workbench in which information for the applications and             Additional parameters which depend on the application are
 the output results are available to the users through a common                required, such as the study horizon. Users benefit from
 database. The resources are accessed through a friendly interface             information already available in the common ePSR database,
 working under a security control framework. Corporate-wide features           sometimes defined by others
 increase productivity and assist the management of the studies.

 Modeling Aspects                                                              System Characteristics
 General Framework Architecture: ePSR is built under a multi-tier              Windows-based User Interface

 architecture comprising of a graphical user interface, business               Software
                                                                               ? Code: Microsoft .NET (object-oriented code, based on

 rules, database management systems, energy applications and                       state of the art design patterns)
 data format converters.                                                       Database:
                                                                               ? Oracle RDBMS
                                                                               Data Interchange Format: Web Services and XML

 Access Control: ePSR environment is security controlled through
 two mechanisms: access control and workgroup profile. Users
 have to “login” to the ePSR framework in order to gain access.                Recent Applications
 Personal logins are related to workgroups for which access profiles
                                                                               Some of the recent uses of ePSR include:
 are defined. A workgroup access profile establishes privileges to
 access a set of ePSR functions, restricting information and models
                                                                               ?EÜAª, largest generation company in the country, has
 to the members of the workgroup.
                                                                               been using ePSR since 2007 to coordinate studies related to
                                                                               long-term planning activities and firm-energy calculation
 Organization: ePSR organizes the information into five categories,
                                                                               (SDDP/ MAXREV models), dispatch of energy scheduled in the
 as follows:
                                                                               short term market resulting from the combined effect of self-
                                                                               dispatch and position in the balancing market (NCP model)
 Power System Components: describe the power system
                                                                               ? CENACE, the institution responsible for operating the
 components (power plants, reservoirs, circuits, substations and
                                                                               power system and the electricity market, has been using ePSR
 others). Data can be constant or dynamic (time-dependent). Data
                                                                               since 2006 to integrate PSR applications for optimizing the system
 are versioned which means that power system components from
                                                                               dispatch in studies ranging from a few hours (NCP model) to
 previous years may be used (important for auditing the results)
                                                                               several years ahead (SDDP model) and to determine ex-ante and
 Power System Configurations: abstract organizations of the
                                                                               ex-post prices according to regulations (MSP model). ePSR also
 power system components. Configurations are defined by
                                                                               integrates application results with SCADA and ERP systems
 clustering these components into sets of interrelated energy
                                                                               ? Agder Energi has been evaluating ePSR to manage its
 systems, geo-electrical areas and electrical control areas
                                                                               short term energy application (NCP model) for optimizing the
 Time series: historical data and forecasted scenarios, such as
                                                                               scheduled generation of its power plants in order to maximize
 hydrological inflows, reservoir storage level, fuel prices,
                                                                               revenues from power sales into the Nordpool
 macro-climatic variables and others

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transmission analysis and expansion planning tool

 Objective                                                                     Analysis
                                                                               ? of a user provided expansion plan and determination
                                                                                  of new investments required to comply with the transmission
 NETPLAN is a computational tool aimed at finding the least-cost                  planning criteria
 transmission expansion of a hydrothermal system. The expansion
 planning is done in two phases. In the first phase the OPTNET
 model chooses the best line and transformer reinforcements
                                                                               System Characteristics
 required to meet forecasted loads along the planning horizon, taking
 into account (i) the base case and contingency constraints, using             Windows
                                                                               ? compatible user interface for model execution
 either the “N-1” or the reliability worth criterion; (ii) dispatch               considering selected scenarios and network states
 scenarios related to different inflows to hydro plants and the
 generation expansion plan of the system. In the second phase, the             GUI provides visualization of results in spreadsheet or network
 OPTFLOW model determines the most economic reactive support                      diagram and generation of graphs
 required reinforcements along the planning horizon considering the
 first stage reinforcements. Both models use state-of-the-art                  Data import from either SDDP, PSS-E or ANARED files
 optimization tools capable of dealing with the dimension of regional
 or national networks while coping with the complexity of the                  Study manager that allows the user to produce alternative
 transmission planning criteria. Besides the expansion models,                    plans and deal with different assumptions and planning criteria
 contingency (power flow and OPF) and reliability analysis models
 provide a detailed assessment of the performance of a trial plan in
 terms of its capability in complying with the transmission criteria.
                                                                               Integration with SDDP, OPTGEN and NCP
 NETPLAN can be used by planners (in centralized decision                      NETPLAN can be integrated with the detailed transmission-
 environments), electricity regulators and investors (in competitive           constrained stochastic hydrothermal dispatch model SDDP and
 environments).                                                                with the generation and interconnection capacity expansion
                                                                               planning model OPTGEN.

 Modeling Aspects                                                              Recent Applications
 NETPLAN is an integrated analysis and expansion tool which
                                                                               Transmission expansion planning study of Costa Rica along a
 represents the following features:
                                                                                   five year horizon considering 100 dispatch scenarios and 90
                                                                                   circuit contingencies (2007-2011)
 ? of operation time steps (year, semester, quarter, and
     month)                                                                    Greece
                                                                               ?network contingency analysis based on network data
 Both continuous and integer decision variables (investment in
 ?                                                                                 imported from PSS-E (2007)
     lines, transformers, etc)
                                                                               Transmission expansion planning study of El Salvador for a five
 ? dispatch scenarios
                                                                                  year horizon considering 500 dispatch scenarios
 Contingency list for “N-1”or reliability worth criteria

 Transmission reliability worth and trade-off between annualized
                                                                               Power system database management, including georeferenced

     reliability and investment costs                                              information integrated with PSR models for the visualization of
                                                                                   dispatch and power flow results for many countries, such as
 Robustness of the expansion plan with regard to dispatch
                                                                                   Bolivia, Brazil, Colombia, Costa Rica, Dominican Republic,
     scenarios and network states                                                  Ecuador, Greece and Guatemala

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Description: Psr Contracts document sample