Rung 29: storage per investment period — a storage unit and a store that cycle within each period, two that reopen on their initial level, and a ramp that restarts at a period start¶

description: A plain `n.optimize()`, and its multi-period and stochastic classes, in one file. Every second-stage
  quantity spans a `scenario` (a future dispatch is chosen in) and every asset stands in the investment
  `period`s its build year and lifetime span. A parameter spans `scenario` exactly when PyPSA reads it
  per scenario. Capacity is chosen once, before the future is known, and paid once per active period at
  its cost in expectation over the scenarios; operation is the expectation over the scenarios' weights,
  with a share priced at the tail through the CVaR rows, which stand only where a risk preference is set.
  A plain run feeds one scenario, one period, all-active masks and unit weights, and the model collapses
  to the standard one. A security-constrained run copies each branch flow limit once per outage in an
  `outage` set that a plain run leaves empty. Which snapshots an asset is active in, a scenario's weight,
  and the outage factors are data prep.
dimensions:
  scenario: {description: 'the futures dispatch is chosen in, each with a weight'}
  snapshot: {description: dispatch periods, dtype: datetime, ordered: true}
  bus: {description: network nodes}
  generator: {description: 'generating units, each on one bus'}
  link: {description: 'controllable connections, each from one bus to the buses it delivers to'}
  link_output: {description: 'a link''s output ports, one label per port a link declares — PyPSA''s `bus1`,
      `bus2`, … columns read long, so a link of any number of output ports is one term in the balance,
      data prep'}
  process: {description: 'generalized multi-port converters, each with an internal power that every port
      draws or delivers at its own rate'}
  process_output: {description: 'a process''s ports, one label per port a process declares — PyPSA''s
      `bus0`, `bus1`, … each carry a signed `rate`, so a process of any number of ports is one term in
      the balance, data prep'}
  load: {description: 'demands, each on one bus'}
  storage_unit: {description: 'storage units, dispatch and store behind one bus connection'}
  store: {description: 'pure energy stores, each on one bus'}
  period: {description: investment periods — PyPSA's `investment_periods`, dtype: int, ordered: true}
relations:
  snapshot_period: {description: the investment period a snapshot falls in, key: snapshot, values: period}
  Generator_bus: {description: the bus a generator sits on, key: generator, values: bus}
  Link_output_link: {description: the link an output port belongs to, key: link_output, values: link}
  Link_output_bus: {description: 'the bus an output port delivers to — PyPSA''s `bus1`, `bus2`, … columns.
      A link of three output ports is three labels here rather than a third relation, so the file states
      any number of them', key: link_output, values: bus}
  Process_output_process: {description: the process a port belongs to, key: process_output, values: process}
  Process_output_bus: {description: 'the bus a port draws from or delivers to — PyPSA''s `bus0`, `bus1`,
      … columns. A process of three ports is three labels here rather than a third relation, so the file
      states any number of them', key: process_output, values: bus}
  Load_bus: {description: the bus a load sits on, key: load, values: bus}
  StorageUnit_bus: {description: the bus a storage unit sits on, key: storage_unit, values: bus}
  Store_bus: {description: the bus a store sits on, key: store, values: bus}
parameters:
  snapshot_weightings_objective:
    description: PyPSA's `snapshot_weightings.objective` — hours a snapshot stands for in the cost
    dims: [snapshot]
  Generator_p_nom:
    description: nominal power
    dims: [scenario, generator]
  Generator_p_nom_extendable:
    description: whether the nominal power is a decision
    dims: [generator]
    dtype: bool
  Generator_p_min_pu:
    description: least output, per unit of nominal power
    dims: [scenario, snapshot, generator]
  Generator_p_max_pu:
    description: most output, per unit of nominal power — an availability profile
    dims: [scenario, snapshot, generator]
  Generator_marginal_cost:
    description: cost of one unit of output
    dims: [scenario, snapshot, generator]
  Generator_marginal_cost_quadratic:
    description: cost of the square of one unit of output
    dims: [scenario, snapshot, generator]
  Generator_sign:
    description: the sign output enters its bus's balance with — PyPSA's `sign`, `1` unless given, `-1`
      for a unit that draws power. PyPSA refuses one that differs by scenario (`constants.py:43`)
    dims: [generator]
  Generator_committable:
    description: whether output is gated by an on/off status decision
    dims: [generator]
    dtype: bool
  Generator_ramp_limit_up:
    description: most a generator may raise its output between snapshots, per unit of nominal power; no
      value means no limit — read at the later of the two snapshots, so the limit may change over time
    dims: [scenario, snapshot, generator]
    missing: neutral
  Generator_ramp_limit_down:
    description: most a generator may lower its output between snapshots, per unit of nominal power; no
      value means no limit — read at the later of the two snapshots, so the limit may change over time
    dims: [scenario, snapshot, generator]
    missing: neutral
  Generator_ramp_limit_start_up:
    description: most output in the snapshot a unit starts, per unit of nominal power; no value means
      no limit
    dims: [scenario, generator]
    missing: neutral
  Generator_ramp_limit_shut_down:
    description: most output in the snapshot before a unit stops, per unit of nominal power; no value
      means no limit
    dims: [scenario, generator]
    missing: neutral
  Generator_status_initial:
    description: one where the unit was on before the first snapshot, zero where off — PyPSA's `up_time_before
      > 0`, data prep
    dims: [scenario, generator]
    dtype: int
  Generator_p_init:
    description: the output a unit brought into the horizon — PyPSA's `p_init`, read only where the unit
      came in running; no value means it is unknown, so the unit carries no ramp row at the first snapshot
    dims: [scenario, generator]
    missing: neutral
  Generator_p_nom_mod:
    description: the module size a build comes in whole numbers of; no value means the build is continuous
    dims: [generator]
    missing: neutral
  Link_efficiency:
    description: share of the flow that arrives at an output port, PyPSA's `efficiency`, `efficiency2`,
      … read long — negative where that port consumes rather than delivers. Read at the snapshot the flow
      arrives, so a delayed port delivers at its arrival snapshot's efficiency (`constraints.py:1498`)
    dims: [scenario, snapshot, link_output]
  Link_output_delay:
    description: snapshots a port's delivery lags its link's flow — PyPSA's `delay`, `delay2`, … read
      long, divided by the `snapshot_weightings.generators` value and rounded up in data prep; zero for
      a port that delivers at once. A port has the same delay in every scenario, because PyPSA refuses
      a delay that differs by scenario (`constants.py:52`)
    dims: [link_output]
    dtype: int
  Link_output_cyclic_delay:
    description: whether a delayed port's flow wraps from the end of its investment period — PyPSA's `cyclic_delay`,
      `cyclic_delay2`, …; where it does not, the flow still in transit at each period's first snapshots
      is lost. The flag is the same in every scenario, as the delay is
    dims: [link_output]
    dtype: bool
  Process_rate:
    description: the energy a port draws or delivers per unit of internal power, PyPSA's `rate0`, `rate1`,
      … read long — negative where the port withdraws, positive where it injects; a link is a process
      whose `bus0` rate is minus one and whose output rates are its efficiencies. Read at the snapshot
      the transfer arrives, so a delayed port transfers at its arrival snapshot's rate (`constraints.py:1498`)
    dims: [scenario, snapshot, process_output]
  Process_output_delay:
    description: snapshots a port's transfer lags its process's internal power — PyPSA's `delay0`, `delay1`,
      … read long, divided by the `snapshot_weightings.generators` value and rounded up in data prep;
      zero for a port that transfers at once. A port has the same delay in every scenario, as a link's
      port has
    dims: [process_output]
    dtype: int
  Process_output_cyclic_delay:
    description: whether a delayed port's transfer wraps from the end of its investment period — PyPSA's
      `cyclic_delay0`, `cyclic_delay1`, …; where it does not, the energy still in transit at each period's
      first snapshots is lost. The flag is the same in every scenario, as the delay is
    dims: [process_output]
    dtype: bool
  Load_p_set:
    description: demand
    dims: [scenario, snapshot, load]
  Load_sign:
    description: the sign a load's demand enters its bus's balance with — PyPSA's `sign`, `-1` unless
      given, `1` for a load that feeds its bus. PyPSA refuses one that differs by scenario (`constants.py:43`)
    dims: [load]
  Load_active:
    description: whether a load stands in the model — PyPSA's `active`. A load has no build year and no
      lifetime, so the flag holds in every snapshot. PyPSA refuses one that differs by scenario (`constants.py:51`)
    dims: [load]
    dtype: bool
  scenario_weight:
    description: PyPSA's `scenario_weightings.weight` — the probability of a future
    dims: [scenario]
  period_weight_objective:
    description: PyPSA's `investment_period_weightings.objective` — what a period's cost weighs; PyPSA
      reads it only under `multi_investment_periods`, so data prep feeds one otherwise, whatever the column
      holds (`optimize.py:205-207`, `:264-266`)
    dims: [period]
  Generator_active:
    description: whether a generator stands in a snapshot's period — PyPSA's `active`, from build year
      and lifetime, data prep
    dims: [snapshot, generator]
    dtype: bool
  Link_active:
    description: whether a link stands in a snapshot's period — PyPSA's `active`, data prep
    dims: [snapshot, link]
    dtype: bool
  StorageUnit_active:
    description: whether a storage unit stands in a snapshot's period — PyPSA's `active`, data prep
    dims: [snapshot, storage_unit]
    dtype: bool
  Store_active:
    description: whether a store stands in a snapshot's period — PyPSA's `active`, data prep
    dims: [snapshot, store]
    dtype: bool
  Process_active:
    description: whether a process stands in a snapshot's period — PyPSA's `active`, data prep
    dims: [snapshot, process]
    dtype: bool
  Generator_active_asset:
    description: whether a generator is one of PyPSA's `active_assets` — its `active` flag alone, without
      build year and lifetime, so a unit that stands in no snapshot of the horizon still counts. PyPSA
      refuses one that differs by scenario (`constants.py:51`)
    dims: [generator]
    dtype: bool
  snapshot_weightings_stores:
    description: PyPSA's `snapshot_weightings.stores` — hours a snapshot stands for in a storage balance
    dims: [snapshot]
  StorageUnit_p_nom:
    description: nominal power
    dims: [scenario, storage_unit]
  StorageUnit_p_nom_extendable:
    description: whether the nominal power is a decision
    dims: [storage_unit]
    dtype: bool
  StorageUnit_p_min_pu:
    description: most storing, per unit of nominal power and negated
    dims: [scenario, snapshot, storage_unit]
  StorageUnit_p_max_pu:
    description: most dispatch, per unit of nominal power
    dims: [scenario, snapshot, storage_unit]
  StorageUnit_max_hours:
    description: energy capacity, as hours of dispatch at nominal power
    dims: [scenario, storage_unit]
  StorageUnit_efficiency_store:
    description: share of the power drawn from the bus that becomes charge
    dims: [scenario, snapshot, storage_unit]
  StorageUnit_efficiency_dispatch:
    description: share of the charge drawn down that reaches the bus
    dims: [scenario, snapshot, storage_unit]
  StorageUnit_sign:
    description: the sign net dispatch enters its bus's balance with — PyPSA's `sign`, `1` unless given.
      PyPSA refuses one that differs by scenario (`constants.py:43`)
    dims: [storage_unit]
  StorageUnit_retention:
    description: share of charge kept over a snapshot — PyPSA's `(1 - standing_loss) ** elapsed hours`,
      data prep
    dims: [scenario, snapshot, storage_unit]
  StorageUnit_inflow:
    description: energy arriving per hour, a river into a reservoir
    dims: [scenario, snapshot, storage_unit]
  StorageUnit_state_of_charge_initial:
    description: charge held before the first snapshot
    dims: [scenario, storage_unit]
  StorageUnit_cyclic_state_of_charge:
    description: whether the horizon closes on itself instead of opening on the initial charge
    dims: [scenario, storage_unit]
    dtype: bool
  StorageUnit_cyclic_state_of_charge_per_period:
    description: whether each investment period closes on itself instead of carrying its charge on to
      the next; it overrides `cyclic_state_of_charge` and `state_of_charge_initial_per_period`. PyPSA
      reads it only under `multi_investment_periods`, so data prep feeds false otherwise
    dims: [scenario, storage_unit]
    dtype: bool
  StorageUnit_state_of_charge_initial_per_period:
    description: whether each investment period opens on the initial charge instead of carrying the previous
      period's; PyPSA reads it only under `multi_investment_periods`, so data prep feeds false otherwise
    dims: [scenario, storage_unit]
    dtype: bool
  StorageUnit_opens_late:
    description: whether a snapshot is the first a storage unit stands in, where that is not the first
      of the horizon — PyPSA's `active.cumsum() == 1` over the snapshots it stands in, past the first
      snapshot, data prep; false in a run where every unit stands throughout
    dims: [snapshot, storage_unit]
    dtype: bool
  StorageUnit_inactive_snapshots:
    description: how many snapshots a storage unit does not stand in — PyPSA's `(~active).sum()`, data
      prep. A cyclic unit reaches back this many snapshots further, so it closes on the last snapshot
      it stands in
    dims: [storage_unit]
    dtype: int
  StorageUnit_marginal_cost:
    description: cost of one unit of dispatch
    dims: [scenario, snapshot, storage_unit]
  StorageUnit_marginal_cost_quadratic:
    description: cost of the square of one unit of dispatch; storing is not charged
    dims: [scenario, snapshot, storage_unit]
  StorageUnit_marginal_cost_storage:
    description: cost of one unit of charge held over one snapshot
    dims: [scenario, snapshot, storage_unit]
  Store_e_nom:
    description: nominal energy capacity
    dims: [scenario, store]
  Store_e_nom_extendable:
    description: whether the nominal energy capacity is a decision
    dims: [store]
    dtype: bool
  Store_e_min_pu:
    description: least energy held, per unit of nominal capacity — negative for a store that may go short
    dims: [scenario, snapshot, store]
  Store_e_max_pu:
    description: most energy held, per unit of nominal capacity
    dims: [scenario, snapshot, store]
  Store_sign:
    description: the sign the power a store delivers enters its bus's balance with — PyPSA's `sign`, `1`
      unless given. PyPSA refuses one that differs by scenario (`constants.py:43`)
    dims: [store]
  Store_retention:
    description: share of energy kept over a snapshot — PyPSA's `(1 - standing_loss) ** elapsed hours`,
      data prep
    dims: [scenario, snapshot, store]
  Store_e_initial:
    description: energy held before the first snapshot
    dims: [scenario, store]
  Store_e_cyclic:
    description: whether the horizon closes on itself instead of opening on the initial energy
    dims: [scenario, store]
    dtype: bool
  Store_e_cyclic_per_period:
    description: whether each investment period closes on itself instead of carrying its energy on to
      the next; it overrides `e_cyclic` and `e_initial_per_period`. PyPSA reads it only under `multi_investment_periods`,
      so data prep feeds false otherwise
    dims: [scenario, store]
    dtype: bool
  Store_e_initial_per_period:
    description: whether each investment period opens on the initial energy instead of carrying the previous
      period's; PyPSA reads it only under `multi_investment_periods`, so data prep feeds false otherwise
    dims: [scenario, store]
    dtype: bool
  Store_opens_late:
    description: whether a snapshot is the first a store stands in, where that is not the first of the
      horizon — PyPSA's `active.cumsum() == 1` over the snapshots it stands in, past the first snapshot,
      data prep; false in a run where every store stands throughout
    dims: [snapshot, store]
    dtype: bool
  Store_inactive_snapshots:
    description: how many snapshots a store does not stand in — PyPSA's `(~active).sum()`, data prep.
      A cyclic store reaches back this many snapshots further, so it closes on the last snapshot it stands
      in
    dims: [store]
    dtype: int
  Store_marginal_cost:
    description: cost of one unit of power delivered
    dims: [scenario, snapshot, store]
  Store_marginal_cost_quadratic:
    description: cost of the square of the net power delivered, so charging costs as much as delivering
    dims: [scenario, snapshot, store]
  Store_marginal_cost_storage:
    description: cost of one unit of energy held over one snapshot
    dims: [scenario, snapshot, store]
variables:
  Generator_p:
    description: '`Generator-p` — output of a generator in a snapshot'
    dims: [scenario, snapshot, generator]
    where: Generator_active
  StorageUnit_p_dispatch:
    description: '`StorageUnit-p_dispatch` — power delivered to the bus'
    dims: [scenario, snapshot, storage_unit]
    where: StorageUnit_active
  StorageUnit_p_store:
    description: '`StorageUnit-p_store` — power drawn from the bus into charge'
    dims: [scenario, snapshot, storage_unit]
    where: StorageUnit_active
  StorageUnit_state_of_charge:
    description: '`StorageUnit-state_of_charge` — energy held at the end of a snapshot'
    dims: [scenario, snapshot, storage_unit]
    where: StorageUnit_active
  Store_e:
    description: '`Store-e` — energy held at the end of a snapshot'
    dims: [scenario, snapshot, store]
    where: Store_active
  Store_p:
    description: '`Store-p` — power delivered to the bus; charging is negative'
    dims: [scenario, snapshot, store]
    where: Store_active
  Generator_status:
    description: '`Generator-status` — how much of a committable unit is on: an integer the rows below
      cap at one, or at the module count where the build is modular'
    dims: [scenario, snapshot, generator]
    where: Generator_committed
    domain: integer
    bounds: {lower: 0}
  Generator_p_nom_ext:
    description: '`Generator-p_nom` — nominal power where it is a decision, for a generator that is active;
      the parameter of the same PyPSA name carries the fixed regime'
    dims: [generator]
    where: Generator_p_nom_extendable AND Generator_active_asset
  Link_p:
    description: '`Link-p` — PyPSA''s `p0`, the flow measured at the `Link_bus0` end: a positive value
      withdraws there and injects at every bus the link''s output ports deliver to'
    dims: [scenario, snapshot, link]
    where: Link_active
  Process_p:
    description: '`Process-p` — PyPSA''s internal power `p`: a positive value drives every port at its
      own rate, withdrawing where the rate is negative and injecting where it is positive'
    dims: [scenario, snapshot, process]
    where: Process_active
constraints:
  Generator_fix_p_lower:
    description: '`Generator-fix-p-lower` — a fixed generator outputs at least its minimum'
    dims: [scenario, snapshot, generator]
    where: not Generator_p_nom_extendable AND not Generator_committable AND Generator_active
    expression: Generator_p >= Generator_p_min_pu * Generator_p_nom
  Generator_fix_p_upper:
    description: '`Generator-fix-p-upper` — a fixed generator outputs at most what is available'
    dims: [scenario, snapshot, generator]
    where: not Generator_p_nom_extendable AND not Generator_committable AND Generator_active
    expression: Generator_p <= Generator_p_max_pu * Generator_p_nom
  StorageUnit_fix_p_dispatch_lower:
    description: '`StorageUnit-fix-p_dispatch-lower` — dispatch is non-negative'
    dims: [scenario, snapshot, storage_unit]
    where: StorageUnit_fix
    expression: StorageUnit_p_dispatch >= 0
  StorageUnit_fix_p_dispatch_upper:
    description: '`StorageUnit-fix-p_dispatch-upper` — a fixed unit dispatches at most its nominal power'
    dims: [scenario, snapshot, storage_unit]
    where: StorageUnit_fix
    expression: StorageUnit_p_dispatch <= StorageUnit_p_max_pu * StorageUnit_p_nom
  StorageUnit_fix_p_store_lower:
    description: '`StorageUnit-fix-p_store-lower` — storing is non-negative'
    dims: [scenario, snapshot, storage_unit]
    where: StorageUnit_fix
    expression: StorageUnit_p_store >= 0
  StorageUnit_fix_p_store_upper:
    description: '`StorageUnit-fix-p_store-upper` — a fixed unit stores at most its nominal power, the
      minimum-per-unit column carrying that cap negated'
    dims: [scenario, snapshot, storage_unit]
    where: StorageUnit_fix
    expression: StorageUnit_p_store <= -StorageUnit_p_min_pu * StorageUnit_p_nom
  StorageUnit_fix_state_of_charge_lower:
    description: '`StorageUnit-fix-state_of_charge-lower` — charge is non-negative'
    dims: [scenario, snapshot, storage_unit]
    where: StorageUnit_fix
    expression: StorageUnit_state_of_charge >= 0
  StorageUnit_fix_state_of_charge_upper:
    description: '`StorageUnit-fix-state_of_charge-upper` — a fixed unit holds at most its hours at nominal
      power'
    dims: [scenario, snapshot, storage_unit]
    where: StorageUnit_fix
    expression: StorageUnit_state_of_charge <= StorageUnit_max_hours * StorageUnit_p_nom
  Generator_p_ramp_limit_up:
    description: '`Generator-p-ramp_limit_up` — a generator raises output no faster than its ramp limit
      of the build, and a committed one no further than its start-up ramp in the snapshot it turns on.
      A unit that came into the horizon running carries a row at the first snapshot only where its `p_init`
      gives the output it brought in, and no unit carries one at the start of a later investment period
      — nor does any unit a big M releases instead'
    dims: [scenario, snapshot, generator]
    where: (Generator_ramp_limit_up OR Generator_ramp_limit_start_up) AND NOT (Generator_committable AND
      Generator_p_nom_extendable AND NOT (Generator_p_nom_mod > 0)) AND Generator_ramps_from_previous
      AND Generator_active
    expression: Generator_p - Generator_previous_p <= Generator_ramp_up_allowance
  Generator_p_ramp_limit_down:
    description: '`Generator-p-ramp_limit_down` — a generator lowers output no faster than its ramp limit
      of the build, and a committed one no further than its shut-down ramp in the snapshot it turns off.
      A unit that came into the horizon running carries a row at the first snapshot only where its `p_init`
      gives the output it brought in, and no unit carries one at the start of a later investment period
      — nor does any unit a big M releases instead'
    dims: [scenario, snapshot, generator]
    where: (Generator_ramp_limit_down OR Generator_ramp_limit_shut_down) AND NOT (Generator_committable
      AND Generator_p_nom_extendable AND NOT (Generator_p_nom_mod > 0)) AND Generator_ramps_from_previous
      AND Generator_active
    expression: Generator_previous_p - Generator_p <= Generator_ramp_down_allowance
  StorageUnit_energy_balance:
    description: '`StorageUnit-energy_balance` — the charge carried in, plus what is stored after its
      efficiency, less what dispatch draws down before its own, plus inflow not spilled'
    dims: [scenario, snapshot, storage_unit]
    where: StorageUnit_active
    expression: StorageUnit_state_of_charge == ((StorageUnit_charge_carried_in + ((StorageUnit_efficiency_store
      * StorageUnit_p_store) * snapshot_weightings_stores)) - ((StorageUnit_p_dispatch * snapshot_weightings_stores)
      / StorageUnit_efficiency_dispatch)) + (StorageUnit_inflow * snapshot_weightings_stores)
  Store_fix_e_lower:
    description: '`Store-fix-e-lower` — a fixed store holds at least its floor'
    dims: [scenario, snapshot, store]
    where: not Store_e_nom_extendable AND Store_active
    expression: Store_e >= Store_e_min_pu * Store_e_nom
  Store_fix_e_upper:
    description: '`Store-fix-e-upper` — a fixed store holds at most its nominal capacity'
    dims: [scenario, snapshot, store]
    where: not Store_e_nom_extendable AND Store_active
    expression: Store_e <= Store_e_max_pu * Store_e_nom
  Store_energy_balance:
    description: '`Store-energy_balance` — the energy carried in, less what is delivered to the bus'
    dims: [scenario, snapshot, store]
    where: Store_active
    expression: Store_e == Store_energy_carried_in - Store_p * snapshot_weightings_stores
  Bus_nodal_balance:
    description: '`Bus-nodal_balance` — what is generated at a bus, storage dispatch and stores included,
      less what the links take away, plus what arrives over them after losses and any delay at every port
      they deliver to, each process port drawing or delivering at its own rate and each passive branch
      carrying its flow, meets the load there, less half of every incident line''s and transformer''s
      loss — PyPSA dissipates a branch''s loss half at either end. Each generator, storage unit, store
      and load term enters with its component''s `sign` (`constraints.py:1404-1405`, `:1514`), and an
      inactive load not at all. A bus nothing is attached to has no row; PyPSA refuses one that carries
      load, and this file does not yet.'
    dims: [scenario, snapshot, bus]
    expression: Bus_injection == 0
expressions:
  Generator_previous_status:
    description: the commitment state a generator carries into a snapshot — off at the first snapshot
      it stands in past the first of the horizon, as PyPSA reads a status it did not build (`constraints.py:298`),
      and the state carried over otherwise
    dims: [scenario, snapshot, generator]
    cases:
      opening_late: {when: 'position(snapshot) > 0 AND NOT shift(Generator_active, along=snapshot, offset=1)',
        expression: 0}
    otherwise: Generator_status_carried_over
  Generator_status_carried_over:
    description: the state a generator carries over into a snapshot — the state it brought into the horizon
      at the first, the previous snapshot's after that
    dims: [scenario, snapshot, generator]
    cases:
      opening: {when: position(snapshot) == 0, expression: Generator_status_initial}
    otherwise: shift(Generator_status, along=snapshot, offset=1)
  Generator_previous_p:
    description: the output a generator carries into a snapshot — at the first, the `p_init` it brought
      in where it came in running and nothing where it came in off; the previous snapshot's after that
    dims: [scenario, snapshot, generator]
    cases:
      opening: {when: position(snapshot) == 0, expression: Generator_status_initial * Generator_p_init}
    otherwise: shift(Generator_p, along=snapshot, offset=1)
  Generator_p_nom_effective:
    description: the build a generator's limits are taken against — the chosen one where it is extendable,
      the given one otherwise
    dims: [scenario, generator]
    cases:
      extendable: {when: Generator_p_nom_extendable, expression: Generator_p_nom_ext}
    otherwise: Generator_p_nom
  Generator_ramp_up_rate:
    description: the ramp limit a unit's up row reads — PyPSA's `ramp_limit_up`, or the full build where
      it has none, since a start-up ramp alone builds the row
    dims: [scenario, snapshot, generator]
    cases:
      given: {when: Generator_ramp_limit_up, expression: Generator_ramp_limit_up}
    otherwise: 1
  Generator_ramp_down_rate:
    description: the ramp limit a unit's down row reads — PyPSA's `ramp_limit_down`, or the full build
      where it has none, since a shut-down ramp alone builds the row
    dims: [scenario, snapshot, generator]
    cases:
      given: {when: Generator_ramp_limit_down, expression: Generator_ramp_limit_down}
    otherwise: 1
  Generator_start_up_rate:
    description: the start-up ramp a unit's up row reads — PyPSA's `ramp_limit_start_up`, or the full
      build where it has none
    dims: [scenario, generator]
    cases:
      given: {when: Generator_ramp_limit_start_up, expression: Generator_ramp_limit_start_up}
    otherwise: 1
  Generator_shut_down_rate:
    description: the shut-down ramp a unit's down row reads — PyPSA's `ramp_limit_shut_down`, or the full
      build where it has none
    dims: [scenario, generator]
    cases:
      given: {when: Generator_ramp_limit_shut_down, expression: Generator_ramp_limit_shut_down}
    otherwise: 1
  Generator_p_nom_committed:
    description: the build a committed unit's ramp rows are taken against — one module where the build
      is extendable and modular, the given build otherwise
    dims: [scenario, generator]
    cases:
      modular_build: {when: Generator_p_nom_extendable AND Generator_p_nom_mod > 0, expression: Generator_p_nom_mod}
    otherwise: Generator_p_nom
  Generator_ramp_up_allowance:
    description: how far a generator may raise output between two snapshots — its ramp limit of the build
      while it stays on, plus its start-up ramp in the snapshot it turns on
    dims: [scenario, snapshot, generator]
    cases:
      committed: {when: Generator_committable, expression: Generator_ramp_up_rate * Generator_p_nom_committed
          * Generator_previous_status + Generator_start_up_rate * Generator_p_nom_committed * (Generator_status
          - Generator_previous_status)}
    otherwise: Generator_ramp_up_rate * Generator_p_nom_effective
  Generator_ramp_down_allowance:
    description: how far a generator may lower output between two snapshots — its ramp limit of the build
      while it stays on, plus its shut-down ramp in the snapshot it turns off
    dims: [scenario, snapshot, generator]
    cases:
      committed: {when: Generator_committable, expression: Generator_ramp_down_rate * Generator_p_nom_committed
          * Generator_status + Generator_shut_down_rate * Generator_p_nom_committed * (Generator_previous_status
          - Generator_status)}
    otherwise: Generator_ramp_down_rate * Generator_p_nom_effective
  StorageUnit_charge_carried_in:
    description: the charge a unit opens a snapshot with — at the first snapshot it stands in, its last
      such snapshot's less standing loss where it is cyclic and the given initial charge, which no standing
      loss has touched yet, where it is not; the previous snapshot's less standing loss otherwise. A unit
      built in a later period opens in that period, and a cyclic one that retires closes on its own last
      snapshot. Per period, the same holds with each investment period as the horizon
    dims: [scenario, snapshot, storage_unit]
    cases:
      cyclic: {when: StorageUnit_cyclic_state_of_charge AND NOT StorageUnit_cyclic_state_of_charge_per_period
          AND NOT StorageUnit_state_of_charge_initial_per_period AND (position(snapshot) == 0 OR StorageUnit_opens_late),
        expression: 'StorageUnit_retention * shift(shift(StorageUnit_state_of_charge, along=snapshot,
          offset=1, edge=''wrap''), along=snapshot, offset=StorageUnit_inactive_snapshots, edge=''wrap'')'}
      opening: {when: NOT StorageUnit_cyclic_state_of_charge AND NOT StorageUnit_cyclic_state_of_charge_per_period
          AND NOT StorageUnit_state_of_charge_initial_per_period AND (position(snapshot) == 0 OR StorageUnit_opens_late),
        expression: StorageUnit_state_of_charge_initial}
      period_cyclic: {when: StorageUnit_cyclic_state_of_charge_per_period, expression: 'StorageUnit_retention
          * shift(StorageUnit_state_of_charge, along=snapshot, offset=1, edge=''wrap'', within=snapshot_period[period])'}
      period_opening: {when: 'StorageUnit_state_of_charge_initial_per_period AND NOT StorageUnit_cyclic_state_of_charge_per_period
          AND position(snapshot, within=snapshot_period[period]) == 0', expression: StorageUnit_state_of_charge_initial}
    otherwise: StorageUnit_retention * shift(StorageUnit_state_of_charge, along=snapshot, offset=1)
  Store_energy_carried_in:
    description: the energy a store opens a snapshot with — at the first snapshot it stands in, its last
      such snapshot's less standing loss where it is cyclic and the given initial energy, which no standing
      loss has touched yet, where it is not; the previous snapshot's less standing loss otherwise. A store
      built in a later period opens in that period, and a cyclic one that retires closes on its own last
      snapshot. Per period, the same holds with each investment period as the horizon
    dims: [scenario, snapshot, store]
    cases:
      cyclic: {when: Store_e_cyclic AND NOT Store_e_cyclic_per_period AND NOT Store_e_initial_per_period
          AND (position(snapshot) == 0 OR Store_opens_late), expression: 'Store_retention * shift(shift(Store_e,
          along=snapshot, offset=1, edge=''wrap''), along=snapshot, offset=Store_inactive_snapshots, edge=''wrap'')'}
      opening: {when: NOT Store_e_cyclic AND NOT Store_e_cyclic_per_period AND NOT Store_e_initial_per_period
          AND (position(snapshot) == 0 OR Store_opens_late), expression: Store_e_initial}
      period_cyclic: {when: Store_e_cyclic_per_period, expression: 'Store_retention * shift(Store_e, along=snapshot,
          offset=1, edge=''wrap'', within=snapshot_period[period])'}
      period_opening: {when: 'Store_e_initial_per_period AND NOT Store_e_cyclic_per_period AND position(snapshot,
          within=snapshot_period[period]) == 0', expression: Store_e_initial}
    otherwise: Store_retention * shift(Store_e, along=snapshot, offset=1)
  Link_output_arrival:
    description: what a link delivers to an output port at a snapshot — its flow delayed by the port's
      `delay` within its investment period, times the port's efficiency at the snapshot the flow arrives;
      where the port is `cyclic_delay` the delayed flow wraps from the period's end, and where it is not
      the flow still in transit at the period's first snapshots is lost. A port that does not delay (`delay`
      zero) delivers its flow unshifted, cyclic or not
    dims: [scenario, snapshot, link_output]
    cases:
      wrapping: {when: Link_output_cyclic_delay, expression: 'shift(at(Link_p, by=Link_output_link[link]),
          along=snapshot, offset=Link_output_delay, edge=''wrap'', within=snapshot_period[period]) * Link_efficiency'}
    otherwise: shift(at(Link_p, by=Link_output_link[link]), along=snapshot, offset=Link_output_delay,
      edge=0, within=snapshot_period[period]) * Link_efficiency
  Process_output_arrival:
    description: what a process transfers at a port at a snapshot — its internal power delayed by the
      port's `delay` within its investment period, times the port's rate at the snapshot the transfer
      arrives; where the port is `cyclic_delay` the delayed transfer wraps from the period's end, and
      where it is not the energy still in transit at the period's first snapshots is lost. A port that
      does not delay (`delay` zero) transfers at once, cyclic or not
    dims: [scenario, snapshot, process_output]
    cases:
      wrapping: {when: Process_output_cyclic_delay, expression: 'shift(at(Process_p, by=Process_output_process[process]),
          along=snapshot, offset=Process_output_delay, edge=''wrap'', within=snapshot_period[period])
          * Process_rate'}
    otherwise: shift(at(Process_p, by=Process_output_process[process]), along=snapshot, offset=Process_output_delay,
      edge=0, within=snapshot_period[period]) * Process_rate
  Generator_opex: {expression: 'sum(sum(((Generator_p * Generator_marginal_cost) * snapshot_weightings_objective)
      * at(period_weight_objective, by=snapshot_period[period]), over=generator), over=snapshot) + sum(sum((((Generator_p
      * Generator_p) * Generator_marginal_cost_quadratic) * snapshot_weightings_objective) * at(period_weight_objective,
      by=snapshot_period[period]), over=generator), over=snapshot)'}
  StorageUnit_opex: {expression: '(sum(sum(((StorageUnit_p_dispatch * StorageUnit_marginal_cost) * snapshot_weightings_objective)
      * at(period_weight_objective, by=snapshot_period[period]), over=storage_unit), over=snapshot) +
      sum(sum((((StorageUnit_p_dispatch * StorageUnit_p_dispatch) * StorageUnit_marginal_cost_quadratic)
      * snapshot_weightings_objective) * at(period_weight_objective, by=snapshot_period[period]), over=storage_unit),
      over=snapshot)) + sum(sum(((StorageUnit_state_of_charge * StorageUnit_marginal_cost_storage) * snapshot_weightings_objective)
      * at(period_weight_objective, by=snapshot_period[period]), over=storage_unit), over=snapshot)'}
  Store_opex: {expression: 'sum(sum(((Store_p * Store_marginal_cost) * snapshot_weightings_objective)
      * at(period_weight_objective, by=snapshot_period[period]), over=store), over=snapshot) + sum(sum((((Store_p
      * Store_p) * Store_marginal_cost_quadratic) * snapshot_weightings_objective) * at(period_weight_objective,
      by=snapshot_period[period]), over=store), over=snapshot) + sum(sum(((Store_e * Store_marginal_cost_storage)
      * snapshot_weightings_objective) * at(period_weight_objective, by=snapshot_period[period]), over=store),
      over=snapshot)'}
  scenario_opex:
    dims: [scenario]
    expression: (Generator_opex + StorageUnit_opex) + Store_opex
    description: what a future costs to run — every operating term, weighted by the snapshot's hours and
      its period, before the scenario's own weight; a start and a stop cost what they cost, unweighted,
      as PyPSA adds them (`optimize.py:415-432`)
  risk_weighted_opex: {expression: 'sum(scenario_weight * scenario_opex, over=scenario)'}
  total_cost:
    dims: []
    expression: risk_weighted_opex
    description: what the system costs — capacity once per active period at its expected cost over the
      scenarios, operation in expectation over the scenarios, and a share of it at the tail
  Load_demand:
    description: what a load draws from its bus's balance — its demand times its sign where it is active,
      nothing where it is not, since PyPSA drops an inactive load from the balance (`constraints.py:1513-1514`)
    dims: [scenario, snapshot, load]
    cases:
      active: {when: Load_active, expression: Load_sign * Load_p_set}
    otherwise: 0
  Generator_injection: {expression: 'sum(Generator_sign * Generator_p, over=generator, by=Generator_bus[bus])'}
  Link_injection: {expression: 'sum(Link_output_arrival, over=link_output, by=Link_output_bus[bus])'}
  Load_injection: {expression: 'sum(Load_demand, over=load, by=Load_bus[bus])'}
  Process_injection: {expression: 'sum(Process_output_arrival, over=process_output, by=Process_output_bus[bus])'}
  StorageUnit_injection: {expression: 'sum(StorageUnit_sign * (StorageUnit_p_dispatch - StorageUnit_p_store),
      over=storage_unit, by=StorageUnit_bus[bus])'}
  Store_injection: {expression: 'sum(Store_sign * Store_p, over=store, by=Store_bus[bus])'}
  Bus_injection:
    dims: [scenario, snapshot, bus]
    expression: ((((Generator_injection + Link_injection) + Load_injection) + Process_injection) + StorageUnit_injection)
      + Store_injection
    description: what every component puts into a bus, less what it takes out of it; PyPSA writes each
      term into the balance, and a load on its right-hand side
conditions:
  Generator_committed: {description: a committable generator that stands in the snapshot's period — every
      unit-commitment row's set, condition: Generator_committable AND Generator_active}
  Generator_ramps_from_previous: {description: 'a snapshot whose ramp reads a previous output — any snapshot
      but its period''s first, and the horizon''s first where the generator comes in off or carries an
      initial output', condition: 'position(snapshot, within=snapshot_period[period]) > 0 OR (position(snapshot)
      == 0 AND (Generator_status_initial == 0 OR Generator_p_init))'}
  StorageUnit_fix: {description: a storage unit with a fixed build that stands in the snapshot's period
      — PyPSA's `fix` rows, condition: NOT StorageUnit_p_nom_extendable AND StorageUnit_active}
objective: {sense: minimize, expression: total_cost}

from differential.pypsa.prep import relation, static, varying, weighting


n = build()  # the network from the PyPSA tab

sources = {
    'snapshot': pl.Series('snapshot', list(timesteps(n)), dtype=pl.Datetime('us')),
    'bus': pl.Series('bus', list(names(n.buses.index).astype(str)), dtype=pl.String),
        **{
            dim: pl.Series(dim, list(names(n.static(component).index).astype(str)), dtype=pl.String)
            for component, dim in DIM.items()
        },
        **scenarios(n),
        **periods(n, multi),
        **carriers(n, multi),
    'Generator_bus': relation(n, 'Generator', 'bus'),
    'Load_bus': relation(n, 'Load', 'bus'),
    'StorageUnit_bus': relation(n, 'StorageUnit', 'bus'),
    'Store_bus': relation(n, 'Store', 'bus'),
    'snapshot_weightings_objective': weighting(n, 'objective'),
    'Generator_sign': per_component('Generator', first_scenario(n.generators['sign'])),
    'Load_p_set': varying(n, 'Load', 'p_set'),
    'Load_sign': per_component('Load', first_scenario(loads['sign'])),
    'Load_active': per_component('Load', first_scenario(loads['active']), bool),
    'snapshot_weightings_stores': weighting(n, 'stores'),
}

with sps.solve('differential/pypsa/rungs/rung_29_storage_per_period.yaml', sources) as solution:
    solution.objective  # 7438.461538

# SPDX-FileCopyrightText: mathspec Contributors
#
# SPDX-License-Identifier: MIT

"""Rung 29: storage per investment period — a storage unit and a store that cycle within each period, two that reopen on their initial level, and a ramp that restarts at a period start."""

from __future__ import annotations

from datetime import datetime

import pandas as pd

OPTIMIZE = {'multi_investment_periods': True}


def build():
    """A whole network, not the spine: eight snapshots over two periods, four storages that each close or reopen per period, a ramp-limited coal unit."""
    import pypsa

    n = pypsa.Network()
    n.snapshots = pd.MultiIndex.from_tuples(
        [(2020, datetime(2020, 1, 1, t)) for t in range(4)] + [(2030, datetime(2030, 1, 1, t)) for t in range(4)]
    )
    n.investment_periods = [2020, 2030]
    n.investment_period_weightings['objective'] = [1.0, 0.5]
    n.investment_period_weightings['years'] = [10.0, 10.0]
    n.snapshot_weightings['objective'] = [2.0, 1.5, 2.5, 2.0, 2.0, 1.5, 2.5, 2.0]
    n.snapshot_weightings['stores'] = [0.5, 2.0, 1.5, 2.5, 0.5, 2.0, 1.5, 2.5]
    n.add('Bus', 'hub')
    n.add('Generator', 'coal29', bus='hub', p_nom=100, marginal_cost=10, ramp_limit_up=0.1, ramp_limit_down=0.1)
    n.add('Generator', 'peak29', bus='hub', p_nom=200, marginal_cost=[80, 20, 90, 30, 80, 20, 90, 30])
    n.add('StorageUnit', 'su_cycle', bus='hub', p_nom=15, max_hours=4, cyclic_state_of_charge_per_period=True)
    n.add(
        'StorageUnit',
        'su_reset',
        bus='hub',
        p_nom=15,
        max_hours=4,
        state_of_charge_initial=20,
        state_of_charge_initial_per_period=True,
    )
    n.add('Store', 'e_cycle', bus='hub', e_nom=30, e_cyclic_per_period=True)
    n.add('Store', 'e_reset', bus='hub', e_nom=30, e_initial=10, e_initial_per_period=True)
    n.add('Load', 'hub_load', bus='hub', p_set=[40, 60, 70, 40, 90, 110, 120, 90])
    return n