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Glossary

Terminology used in the methodology chapters of this book, with Portuguese equivalents where they appear in Brazilian regulatory or operational documentation. Citations to source papers for the more technical entries live in Bibliography.


EnglishPortugueseDefinition
BlockPatamarAn intra-stage time period (e.g., peak, shoulder, off-peak) representing load-level variation within a stage. Cobre supports two block topologies: parallel (independent dispatches) and chronological (sequential, with carry-over storage).
BusBarramentoA node in the electrical network where generation, demand, and transmission lines connect.
LineLinha / CircuitoA transmission line or transformer connecting two buses, modelled with a directional capacity and an exchange cost.
SubsystemSubsistemaA region of the interconnected grid (in Brazil: SE/CO, S, NE, N).
ExchangeIntercâmbioPower transfer between buses across a transmission line.
LoadCarga / DemandaElectrical power consumption at a bus, possibly varying per block via a load-factor table.
DeficitDéficitUnmet demand — load that cannot be served by available generation. Modelled as a slack variable with a high penalty cost.

EnglishPortugueseDefinition
Hydro plantUsina hidrelétrica (UHE)A hydroelectric generating station.
ReservoirReservatórioWater storage volume behind a dam.
StorageArmazenamentoCurrent water volume in a reservoir, in hm³. The primary state variable in SDDP.
InflowAfluência / Vazão naturalNatural water flow arriving at a reservoir, modelled stochastically by a PAR(p) model (or 0-order seasonal sampling for the p=0p = 0 degenerate case).
Turbined outflowVazão turbinadaWater passing through turbines to generate electricity.
SpillageVertimentoWater released from a reservoir without generating electricity.
CascadeCascataSequence of hydro plants along the same river, where downstream reservoirs receive turbined plus spilled water from upstream plants.
DownstreamJusanteDirection of water flow; the plant that receives outflow from upstream.
UpstreamMontanteDirection against water flow; the plant whose outflow feeds a downstream plant.
ProductivityProdutibilidadeConversion factor from water flow (m³/s) to power (MW).
Run-of-riverFio d’águaHydro plant with no significant storage capacity; storage variable bounds collapse to a single point.
DiversionDesvioWater bypassed to a separate channel, not passing through turbines.
EvaporationEvaporaçãoWater loss from the reservoir surface; can be negative under monthly-net conventions, requiring a bidirectional slack.
Forebay levelNível de montanteWater level at the upstream face of the dam, a function of reservoir storage.
Tailrace levelNível de jusanteWater level at the downstream channel below the dam, a function of total outflow.
HeadQuedaHeight difference between forebay and tailrace levels, determining generation efficiency.
FPHAFunção de Produção Hidrelétrica AproximadaApproximate Hydroelectric Production Function — piecewise-linear model of hydro generation as a function of storage, turbined flow, and spillage. See Hydro Production Models.
Dead volumeVolume mortoThe portion of the reservoir below the minimum operating storage; reservoirs in commissioning are filled to dead volume before entering normal operation.

EnglishPortugueseDefinition
Thermal unitUsina termelétrica (UTE)A fossil-fuel or nuclear generating station.
Minimum generationGeração mínima / InflexibilidadeMinimum output when the unit is committed; modelled as a soft constraint with a penalty slack in Cobre.
Operating costCusto variável unitário (CVU)Variable cost per MWh of generation.
Marginal cost (CMO)Custo Marginal de OperaçãoShadow price of the bus load-balance constraint — the cost of one additional MWh of demand at that bus.
Anticipated dispatchAntecipação de despachoA per-plant flag that splits the thermal decision into a commitment placed at stage tt and a delivered generation forced to match the commitment at stage t+Kt + K, where K=K = lead_stages 1\geq 1. Originally motivated by LNG (GNL) fuel-ordering lead times. See System Elements §4.
Lead stages (KK)Antecedência (estágios)Number of stages between commitment and delivery for an anticipated thermal. The commitment column at stage tt delivers physical generation at stage t+Kt + K.
Past anticipated commitmentsCompromissos anticipados pré-horizonteThe KiK_i pre-horizon commitments seeded into the ring buffer for plant ii. Stored on initial_conditions.past_anticipated_commitments[].values_mw, with values_mw[k] delivering at study stage kk.

EnglishPortugueseDefinition
ScenarioCenárioOne realisation of uncertain quantities (inflows, load, non-controllable sources) along the planning horizon.
StageEstágioA time period in the planning horizon — typically a month, week, or hour.
State variableVariável de estadoVariables that link one stage to the next: storage volumes (always) and AR-lag state (only for PAR(p) with p1p \geq 1).
PAR(p)PAR(p)Periodic Autoregressive model of order pp for inflow generation. The order pmp_m can vary by season mm; pm=0p_m = 0 corresponds to white-noise (0-order) seasonal sampling.
0-order inflow-The degenerate p=0p = 0 case of the PAR(p) model: at=μt+σtεta_t = \mu_t + \sigma_t \varepsilon_t with εtN(0,1)\varepsilon_t \sim \mathcal{N}(0,1) iid. No AR-lag state, no AR coefficients in the data file.
InnovationInovaçãoThe independent standardised noise term εtN(0,1)\varepsilon_t \sim \mathcal{N}(0,1) in the PAR(p) model, representing the unpredictable component after removing autoregressive structure.
AR lagDefasagemPast inflow values ah,ta_{h, t-\ell} that enter the PAR(p) recursion for p1p \geq 1. Stored as state variables in the LP and pinned to the previous stage’s realised inflow via column bounds.
Yule-Walker equationsEquações de Yule-WalkerSystem of linear equations relating autoregressive coefficients to sample autocorrelations. Cobre uses the periodic Yule-Walker variant where the reference season shifts per row to handle multi-season covariance structure.
Spatial correlationCorrelação espacialCross-hydro covariance structure between innovations εh\varepsilon_h. Applied via spectral factorisation ε=Lz\varepsilon = L\, z with LL=ΣL L^{\top} = \Sigma, where zN(0,I)z \sim \mathcal{N}(0, I).
Seasonal mean / stdMédia / desvio sazonalPer-season parameters μm,σm\mu_m, \sigma_m stored in inflow_seasonal_stats.parquet and used both for sampling 0-order inflows and for converting standardised PAR coefficients to original units.
OpeningAberturaA pre-generated noise vector ε\varepsilon used to evaluate the backward pass at one branch of the scenario tree.
Opening treeÁrvore de aberturasThe fixed set of pre-generated noise vectors used in the backward pass; generated once before training begins and reused across all iterations. Each stage carries num_scenarios openings. See Scenario Generation.
In-sample samplingAmostragem in-sampleForward-pass scheme that draws trajectories from the same opening tree the backward pass uses. Default in Cobre.
Out-of-sample samplingAmostragem out-of-sampleForward-pass scheme that draws trajectories from a separate, independent set of openings. Used for unbiased upper-bound estimation.

EnglishPortugueseDefinition
Stage subproblem (stage LP)Subproblema de estágioThe linear programme solved at one stage given an incoming state and a scenario realisation. Carries the cuts accumulated for that stage as constraints on the future-cost variable θ\theta.
Bellman recursionRecursão de BellmanRecursive equation Vt(xt1)=minxtct(xt)+dE[Vt+1(xt)]V_t(x_{t-1}) = \min_{x_t}\, c_t(x_t) + d \cdot \mathbb{E}[V_{t+1}(x_t)] that defines the cost-to-go functions and underlies the SDDP backward pass.
Cost-to-go functionFunção de custo futuro (FCF)Expected cost from the current stage to the end of the horizon, as a function of the incoming state. Convex and piecewise-linear under LP subproblems.
Cut (Benders cut)Corte (de Benders)A linear inequality θα+πx\theta \geq \alpha + \pi^{\top} x providing a lower bound on the future-cost function. Generated in the backward pass from the LP reduced costs of the pinned incoming-state columns at trial states.
Cut interceptInterceptoThe scalar α\alpha in a cut, anchoring the hyperplane vertically.
Cut slope (cut coefficient)Coeficiente do corteThe vector π\pi in a cut, giving the partial derivative of the future-cost function with respect to each state variable. Negative for storage (more storage means lower cost) under the methodology’s sign convention.
State pinning (column bounds)Fixação de estadoBinding an incoming-state coordinate to the trial value x^t1\hat{x}_{t-1} by setting equal lower/upper bounds on its dedicated LP column. The column’s reduced cost is the cut coefficient for that state directly, with no preprocessing. Replaces the earlier equality fixing-row mechanism (KKT-equivalent, fewer rows).
Trial pointPonto amostralThe state visited during a forward pass, used as the anchor where the backward pass evaluates per-opening LPs and aggregates a cut.
Forward passPassagem diretaPhase that simulates the policy by solving stage LPs sequentially under sampled scenarios, producing trial points and a statistical upper-bound estimate.
Backward passPassagem reversaPhase that walks stages in reverse, evaluates all openings at each trial point, extracts duals, and aggregates one cut per stage.
Single-cut formulationFormulação de corte únicoAggregation scheme that produces one cut per (stage, trial point) by averaging per-opening cuts with probability weights. Cobre’s default. Contrasted with the multi-cut formulation (one cut per opening), which Cobre does not currently use.
Outer approximationAproximação exteriorThe piecewise-linear lower bound on the future-cost function constructed from accumulated Benders cuts. The primary output of SDDP training.
Cut poolConjunto de cortesCollection of all cuts at a given stage. Append-only across iterations within one training run; cuts occupy stable, deterministic slot indices and are never deleted — only deactivated and later reactivated, which keeps the cut order reproducible.
Level-1 cut selection-Cut-selection strategy that, at every visited trial point, keeps each cut within tie_tolerance of the per-state maximum cut value (evaluated over all populated cuts, active and inactive) and deactivates cuts that fall short at every visited state. Least aggressive of a value-based family that also includes LML1 (keeps only the oldest near-maximum cut per state) and Dominated (uses a domination_tolerance band); all three share one kernel and reactivate cuts symmetrically. See Cut Management §7.
Dynamic cut selection (DCS)Seleção dinâmica de cortesCut-management mode (selection.method = "dynamic") that retains the full cut pool but loads only a small resident subset into each stage LP, growing it lazily until no omitted cut is violated — so the per-solve LP stays bounded as the pool grows while the solution remains exact (the resident-subset optimum equals the full-pool optimum). Mutually exclusive with the value-based pruning family (Level-1 / LML1 / Dominated). See Cut Management.
Lower boundLimite inferiorEstimate from solving the stage-1 LP with all cuts active; non-decreasing as cuts accumulate.
Upper boundLimite superiorStatistical estimate of policy cost from forward-pass simulations (in-sample or out-of-sample), or a deterministic estimate from an inner approximation.
Optimality gapGap de otimalidadeRelative difference between upper and lower bounds, the primary convergence diagnostic.
Bound stalling-Stopping criterion that fires when the lower bound stops increasing across a configurable window of iterations.
Dual variableVariável dual / MultiplicadorShadow price from an LP solution; indicates the marginal value of a constraint right-hand side. The companion sensitivity for a variable is its reduced cost — for a column pinned at equal bounds, the reduced cost is the marginal value of that bound, which is how Cobre extracts state cut coefficients.
Epigraph variable-The auxiliary LP variable θ\theta that lower-bounds the true cost-to-go function Vt+1(xt)V_{t+1}(x_t); named after the epigraph of a convex function.
Relatively complete recourseRecurso relativamente completoProperty that every stage LP is feasible for any incoming state and scenario realisation. Cobre ensures this via penalty slack variables on every constraint that could otherwise be violated.
Trajectory recordTrajetóriaData structure capturing one stage’s forward-pass result: primal solution, dual solution, stage cost, and end-of-stage state. Used for cut-coefficient extraction in the backward pass and for simulation output.

EnglishPortugueseDefinition
Policy graphGrafo de políticaDirected graph defining the stage structure and transitions of an SDDP problem. Cobre supports finite (acyclic chain) and cyclic policy graphs.
Finite horizon (acyclic mode)Horizonte finitoPolicy graph with a single terminal stage and zero terminal cost-to-go. Susceptible to the end-of-world effect: reservoirs are systematically emptied near the terminal stage.
Cyclic modeModo cíclicoPolicy graph with a back-edge that returns from the last stage of a cycle to the first stage of the next repetition. Used for long-term studies where a finite terminal condition would distort the policy. Replaces what older Brazilian literature calls “infinite horizon”.
Season function τ(t)\tau(t)Função de estaçãoThe position of stage tt within one cycle of length PP: τ(t)=(t1)modP+1\tau(t) = (t-1) \bmod P + 1. In cyclic mode, cuts are pooled by season, not by absolute stage.
Cycle convergence inequality-The requirement dcycle=tcycledtt+1<1d_{\text{cycle}} = \prod_{t \in \text{cycle}} d_{t \to t+1} < 1 for the cumulative discount around one cycle, ensuring the value function remains finite across infinite repetitions.
Discount factorFator de descontoMultiplicative factor d(0,1]d \in (0, 1] applied to the future-cost variable θ\theta in the stage objective, reflecting the time value of future costs. Required (strictly less than 1) for cyclic-mode convergence.
Terminal boundary cut-A Benders cut on the terminal future-cost function imported from an upstream Cobre run, used to chain studies (e.g., a weekly run inheriting the monthly run’s terminal cuts).

EnglishPortugueseDefinition
Coherent risk measureMedida de risco coerenteA risk measure satisfying monotonicity, translation equivariance, positive homogeneity, and subadditivity. CVaR is the canonical example used in SDDP.
CVaRCVaRConditional Value at Risk at level α\alpha — the expected cost in the worst α%\alpha\% of scenarios. The basis for risk-averse aggregation weights in SDDP.
EAVaR-Expectation plus Average Value-at-Risk: the convex combination (1λ)E[Z]+λCVaRα[Z](1-\lambda)\,\mathbb{E}[Z] + \lambda \cdot \text{CVaR}_\alpha[Z] used as Cobre’s parameterised risk measure. λ=0\lambda = 0 recovers risk-neutral; λ=1\lambda = 1 gives pure CVaR.
Risk-neutralNeutro ao riscoOptimisation that minimises expected cost only. Probability weights at cut aggregation are uniform pω=1/Np_\omega = 1/N.
Risk-averseAverso ao riscoOptimisation that penalises high-cost tail scenarios. Cut aggregation reweights toward worse outcomes via the EAVaR formula.

EnglishPortugueseDefinition
LPPrograma LinearLinear Program — an optimisation problem with a linear objective and linear constraints.
Simplex methodMétodo SimplexAlgorithm for solving linear programs by traversing vertices of the feasible polytope. Cobre’s default warm-start strategy targets simplex bases.
BasisBaseThe set of basic variables defining a vertex of the LP feasible region; reused across iterations for warm-starting.
Warm-startPartida a quenteReusing a previous solution basis to accelerate the simplex method on a modified LP, including reconstructing a stored basis onto a churned cut pool by slot identity. See LP Warm-Start.
HiGHS-Open-source LP / MIP solver used as Cobre’s default backend.
CLP-Open-source LP solver from COIN-OR, available as an alternative compile-time backend.

TermDefinition
ONSOperador Nacional do Sistema Elétrico — the Brazilian grid operator.
CEPELCentro de Pesquisas de Energia Elétrica — R&D centre that develops the official NEWAVE / DECOMP / DESSEM dispatch programs.
SINSistema Interligado Nacional — the Brazilian interconnected power system.
NEWAVECEPEL’s long-term hydrothermal-dispatch model (monthly stages, multi-year horizon).
DECOMPCEPEL’s medium-term dispatch model (weekly resolution). The “DECOMP-style” scenario tree (deterministic trunk with branching at the last stage) takes its name from this model.
DESSEMCEPEL’s short-term dispatch model (hourly / half-hourly, day-ahead).
GEVAZPCEPEL’s synthetic scenario-generation tool for hydro inflows.
CCEECâmara de Comercialização de Energia Elétrica — Brazilian electricity-trading chamber.