Datasets:

mengmengmmm

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csn_python_trainuse

like 1

def _var_bounds ( self ) : x0 = array ( [ ] ) xmin = array ( [ ] ) xmax = array ( [ ] ) for var in self . om . vars : x0 = r_ [ x0 , var . v0 ] xmin = r_ [ xmin , var . vl ] xmax = r_ [ xmax , var . vu ] return x0 , xmin , xmax

Returns bounds on the optimisation variables .

def _initial_interior_point ( self , buses , generators , xmin , xmax , ny ) : Va = self . om . get_var ( "Va" ) va_refs = [ b . v_angle * pi / 180.0 for b in buses if b . type == REFERENCE ] x0 = ( xmin + xmax ) / 2.0 x0 [ Va . i1 : Va . iN + 1 ] = va_refs [ 0 ] if ny > 0 : yvar = self . om . get_var ( "y" ) c = [ ] for g in generators : if g . pcost_model == PW_LINEAR : for _ , y in g . p_cost : c . append ( y ) x0 [ yvar . i1 : yvar . iN + 1 ] = max ( c ) * 1.1 return x0

Selects an interior initial point for interior point solver .

def solve ( self ) : base_mva = self . om . case . base_mva Bf = self . om . _Bf Pfinj = self . om . _Pfinj bs , ln , gn , cp = self . _unpack_model ( self . om ) ipol , ipwl , nb , nl , nw , ny , nxyz = self . _dimension_data ( bs , ln , gn ) AA , ll , uu = self . _linear_constraints ( self . om ) Npwl , Hpwl , Cpwl , fparm_pwl , any_pwl = self . _pwl_costs ( ny , nxyz , ipwl ) Npol , Hpol , Cpol , fparm_pol , polycf , npol = self . _quadratic_costs ( gn , ipol , nxyz , base_mva ) NN , HHw , CCw , ffparm = self . _combine_costs ( Npwl , Hpwl , Cpwl , fparm_pwl , any_pwl , Npol , Hpol , Cpol , fparm_pol , npol , nw ) HH , CC , C0 = self . _transform_coefficients ( NN , HHw , CCw , ffparm , polycf , any_pwl , npol , nw ) _ , xmin , xmax = self . _var_bounds ( ) x0 = self . _initial_interior_point ( bs , gn , xmin , xmax , ny ) s = self . _run_opf ( HH , CC , AA , ll , uu , xmin , xmax , x0 , self . opt ) Va , Pg = self . _update_solution_data ( s , HH , CC , C0 ) self . _update_case ( bs , ln , gn , base_mva , Bf , Pfinj , Va , Pg , s [ "lmbda" ] ) return s

Solves DC optimal power flow and returns a results dict .

def _pwl_costs ( self , ny , nxyz , ipwl ) : any_pwl = int ( ny > 0 ) if any_pwl : y = self . om . get_var ( "y" ) Npwl = csr_matrix ( ( ones ( ny ) , ( zeros ( ny ) , array ( ipwl ) + y . i1 ) ) ) Hpwl = csr_matrix ( ( 1 , 1 ) ) Cpwl = array ( [ 1 ] ) fparm_pwl = array ( [ [ 1. , 0. , 0. , 1. ] ] ) else : Npwl = None Hpwl = None Cpwl = array ( [ ] ) fparm_pwl = zeros ( ( 0 , 4 ) ) return Npwl , Hpwl , Cpwl , fparm_pwl , any_pwl

Returns the piece - wise linear components of the objective function .

def _quadratic_costs ( self , generators , ipol , nxyz , base_mva ) : npol = len ( ipol ) rnpol = range ( npol ) gpol = [ g for g in generators if g . pcost_model == POLYNOMIAL ] if [ g for g in gpol if len ( g . p_cost ) > 3 ] : logger . error ( "Order of polynomial cost greater than quadratic." ) iqdr = [ i for i , g in enumerate ( generators ) if g . pcost_model == POLYNOMIAL and len ( g . p_cost ) == 3 ] ilin = [ i for i , g in enumerate ( generators ) if g . pcost_model == POLYNOMIAL and len ( g . p_cost ) == 2 ] polycf = zeros ( ( npol , 3 ) ) if npol > 0 : if len ( iqdr ) > 0 : polycf [ iqdr , : ] = array ( [ list ( g . p_cost ) for g in generators ] ) if len ( ilin ) > 0 : polycf [ ilin , 1 : ] = array ( [ list ( g . p_cost [ : 2 ] ) for g in generators ] ) polycf = polycf * array ( [ base_mva ** 2 , base_mva , 1 ] ) Pg = self . om . get_var ( "Pg" ) Npol = csr_matrix ( ( ones ( npol ) , ( rnpol , Pg . i1 + array ( ipol ) ) ) , ( npol , nxyz ) ) Hpol = csr_matrix ( ( 2 * polycf [ : , 0 ] , ( rnpol , rnpol ) ) , ( npol , npol ) ) Cpol = polycf [ : , 1 ] fparm_pol = ( ones ( npol ) * array ( [ [ 1 ] , [ 0 ] , [ 0 ] , [ 1 ] ] ) ) . T else : Npol = Hpol = None Cpol = array ( [ ] ) fparm_pol = zeros ( ( 0 , 4 ) ) return Npol , Hpol , Cpol , fparm_pol , polycf , npol

Returns the quadratic cost components of the objective function .

def _combine_costs ( self , Npwl , Hpwl , Cpwl , fparm_pwl , any_pwl , Npol , Hpol , Cpol , fparm_pol , npol , nw ) : NN = vstack ( [ n for n in [ Npwl , Npol ] if n is not None ] , "csr" ) if ( Hpwl is not None ) and ( Hpol is not None ) : Hpwl = hstack ( [ Hpwl , csr_matrix ( ( any_pwl , npol ) ) ] ) Hpol = hstack ( [ csr_matrix ( ( npol , any_pwl ) ) , Hpol ] ) HHw = vstack ( [ h for h in [ Hpwl , Hpol ] if h is not None ] , "csr" ) CCw = r_ [ Cpwl , Cpol ] ffparm = r_ [ fparm_pwl , fparm_pol ] return NN , HHw , CCw , ffparm

Combines pwl polynomial and user - defined costs .

def _transform_coefficients ( self , NN , HHw , CCw , ffparm , polycf , any_pwl , npol , nw ) : nnw = any_pwl + npol + nw M = csr_matrix ( ( ffparm [ : , 3 ] , ( range ( nnw ) , range ( nnw ) ) ) ) MR = M * ffparm [ : , 2 ] HMR = HHw * MR MN = M * NN HH = MN . T * HHw * MN CC = MN . T * ( CCw - HMR ) C0 = 1. / 2. * MR . T * HMR + sum ( polycf [ : , 2 ] ) return HH , CC , C0 [ 0 ]

Transforms quadratic coefficients for w into coefficients for x .

def _ref_bus_angle_constraint ( self , buses , Va , xmin , xmax ) : refs = [ bus . _i for bus in buses if bus . type == REFERENCE ] Varefs = array ( [ b . v_angle for b in buses if b . type == REFERENCE ] ) xmin [ Va . i1 - 1 + refs ] = Varefs xmax [ Va . iN - 1 + refs ] = Varefs return xmin , xmax

Adds a constraint on the reference bus angles .

def _f ( self , x , user_data = None ) : p_gen = x [ self . _Pg . i1 : self . _Pg . iN + 1 ] q_gen = x [ self . _Qg . i1 : self . _Qg . iN + 1 ] xx = r_ [ p_gen , q_gen ] * self . _base_mva if len ( self . _ipol ) > 0 : f = sum ( [ g . total_cost ( xx [ i ] ) for i , g in enumerate ( self . _gn ) ] ) else : f = 0 if self . _ny : y = self . om . get_var ( "y" ) self . _ccost = csr_matrix ( ( ones ( self . _ny ) , ( range ( y . i1 , y . iN + 1 ) , zeros ( self . _ny ) ) ) , shape = ( self . _nxyz , 1 ) ) . T f = f + self . _ccost * x else : self . _ccost = zeros ( ( 1 , self . _nxyz ) ) return f

Evaluates the objective function .

def _df ( self , x , user_data = None ) : p_gen = x [ self . _Pg . i1 : self . _Pg . iN + 1 ] q_gen = x [ self . _Qg . i1 : self . _Qg . iN + 1 ] xx = r_ [ p_gen , q_gen ] * self . _base_mva iPg = range ( self . _Pg . i1 , self . _Pg . iN + 1 ) iQg = range ( self . _Qg . i1 , self . _Qg . iN + 1 ) df_dPgQg = zeros ( ( 2 * self . _ng , 1 ) ) for i in self . _ipol : p_cost = list ( self . _gn [ i ] . p_cost ) df_dPgQg [ i ] = self . _base_mva * polyval ( polyder ( p_cost ) , xx [ i ] ) df = zeros ( ( self . _nxyz , 1 ) ) df [ iPg ] = df_dPgQg [ : self . _ng ] df [ iQg ] = df_dPgQg [ self . _ng : self . _ng + self . _ng ] df = df + self . _ccost . T return asarray ( df ) . flatten ( )

Evaluates the cost gradient .

def _d2f ( self , x ) : d2f_dPg2 = lil_matrix ( ( self . _ng , 1 ) ) d2f_dQg2 = lil_matrix ( ( self . _ng , 1 ) ) for i in self . _ipol : p_cost = list ( self . _gn [ i ] . p_cost ) d2f_dPg2 [ i , 0 ] = polyval ( polyder ( p_cost , 2 ) , self . _Pg . v0 [ i ] * self . _base_mva ) * self . _base_mva ** 2 i = r_ [ range ( self . _Pg . i1 , self . _Pg . iN + 1 ) , range ( self . _Qg . i1 , self . _Qg . iN + 1 ) ] d2f = csr_matrix ( ( vstack ( [ d2f_dPg2 , d2f_dQg2 ] ) . toarray ( ) . flatten ( ) , ( i , i ) ) , shape = ( self . _nxyz , self . _nxyz ) ) return d2f

Evaluates the cost Hessian .

def _gh ( self , x ) : Pgen = x [ self . _Pg . i1 : self . _Pg . iN + 1 ] Qgen = x [ self . _Qg . i1 : self . _Qg . iN + 1 ] for i , gen in enumerate ( self . _gn ) : gen . p = Pgen [ i ] * self . _base_mva gen . q = Qgen [ i ] * self . _base_mva Sbus = self . om . case . getSbus ( self . _bs ) Vang = x [ self . _Va . i1 : self . _Va . iN + 1 ] Vmag = x [ self . _Vm . i1 : self . _Vm . iN + 1 ] V = Vmag * exp ( 1j * Vang ) mis = V * conj ( self . _Ybus * V ) - Sbus g = r_ [ mis . real , mis . imag ] flow_max = array ( [ ( l . rate_a / self . _base_mva ) ** 2 for l in self . _ln ] ) for i , v in enumerate ( flow_max ) : if v == 0.0 : flow_max [ i ] = Inf if self . flow_lim == IFLOW : If = self . _Yf * V It = self . _Yt * V h = r_ [ ( If * conj ( If ) ) - flow_max , ( It * conj ( It ) ) - flow_max ] else : i_fbus = [ e . from_bus . _i for e in self . _ln ] i_tbus = [ e . to_bus . _i for e in self . _ln ] Sf = V [ i_fbus ] * conj ( self . _Yf * V ) St = V [ i_tbus ] * conj ( self . _Yt * V ) if self . flow_lim == PFLOW : h = r_ [ Sf . real ( ) ** 2 - flow_max , St . real ( ) ** 2 - flow_max ] elif self . flow_lim == SFLOW : h = r_ [ ( Sf * conj ( Sf ) ) - flow_max , ( St * conj ( St ) ) - flow_max ] . real else : raise ValueError return h , g

Evaluates the constraint function values .

def _costfcn ( self , x ) : f = self . _f ( x ) df = self . _df ( x ) d2f = self . _d2f ( x ) return f , df , d2f

Evaluates the objective function gradient and Hessian for OPF .

def _consfcn ( self , x ) : h , g = self . _gh ( x ) dh , dg = self . _dgh ( x ) return h , g , dh , dg

Evaluates nonlinear constraints and their Jacobian for OPF .

def read ( self , file_or_filename ) : if isinstance ( file_or_filename , basestring ) : fname = os . path . basename ( file_or_filename ) logger . info ( "Unpickling case file [%s]." % fname ) file = None try : file = open ( file_or_filename , "rb" ) except : logger . error ( "Error opening %s." % fname ) return None finally : if file is not None : case = pickle . load ( file ) file . close ( ) else : file = file_or_filename case = pickle . load ( file ) return case

Loads a pickled case .

def write ( self , file_or_filename ) : if isinstance ( file_or_filename , basestring ) : fname = os . path . basename ( file_or_filename ) logger . info ( "Pickling case [%s]." % fname ) file = None try : file = open ( file_or_filename , "wb" ) except : logger . error ( "Error opening '%s'." % ( fname ) ) return False finally : if file is not None : pickle . dump ( self . case , file ) file . close ( ) else : file = file_or_filename pickle . dump ( file , self . case ) return True

Writes the case to file using pickle .

def process_token ( self , tok ) : if ( tok [ 0 ] . __str__ ( ) in ( 'Token.Comment.Multiline' , 'Token.Comment' , 'Token.Literal.String.Doc' ) ) : self . comments += tok [ 1 ] . count ( '\n' ) + 1 elif ( tok [ 0 ] . __str__ ( ) in ( 'Token.Comment.Single' ) ) : self . comments += 1 elif ( self . contains_code and tok [ 0 ] . __str__ ( ) . startswith ( 'Token.Text' ) and tok [ 1 ] . count ( u'\n' ) ) : self . contains_code = False self . sloc += 1 elif ( tok [ 0 ] . __str__ ( ) == 'Token.Comment.Preproc' and tok [ 1 ] . count ( u'\n' ) ) : self . contains_code = False self . sloc += 1 elif ( tok [ 0 ] [ 0 ] in token_types ) : self . contains_code = True

count comments and non - empty lines that contain code

def get_metrics ( self ) : if ( self . sloc == 0 ) : if ( self . comments == 0 ) : ratio_comment_to_code = 0.00 else : ratio_comment_to_code = 1.00 else : ratio_comment_to_code = float ( self . comments ) / self . sloc metrics = OrderedDict ( [ ( 'sloc' , self . sloc ) , ( 'comments' , self . comments ) , ( 'ratio_comment_to_code' , round ( ratio_comment_to_code , 2 ) ) ] ) return metrics

Calculate ratio_comment_to_code and return with the other values

def performAction ( self , action ) : gs = [ g for g in self . case . online_generators if g . bus . type != REFERENCE ] assert len ( action ) == len ( gs ) logger . info ( "Action: %s" % list ( action ) ) for i , g in enumerate ( gs ) : g . p = action [ i ] NewtonPF ( self . case , verbose = False ) . solve ( ) self . _Pg [ : , self . _step ] = [ g . p for g in self . case . online_generators ] if self . _step != len ( self . profile ) - 1 : pq_buses = [ b for b in self . case . buses if b . type == PQ ] for i , b in enumerate ( pq_buses ) : b . p_demand = self . _Pd0 [ i ] * self . profile [ self . _step + 1 ] self . _step += 1 logger . info ( "Entering step %d." % self . _step )

Perform an action on the world that changes it s internal state .

def reset ( self ) : logger . info ( "Reseting environment." ) self . _step = 0 gs = [ g for g in self . case . online_generators if g . bus . type != REFERENCE ] for i , g in enumerate ( gs ) : g . p = self . _Pg0 [ i ] for i , b in enumerate ( [ b for b in self . case . buses if b . type == PQ ] ) : b . p_demand = self . _Pd0 [ i ] * self . profile [ self . _step ] self . _Pg = zeros ( ( len ( self . case . online_generators ) , len ( self . profile ) ) ) self . case . reset ( )

Re - initialises the environment .

def isFinished ( self ) : finished = ( self . env . _step == len ( self . env . profile ) ) if finished : logger . info ( "Finished episode." ) return finished

Is the current episode over?

def _oneInteraction ( self ) : if self . doOptimization : raise Exception ( 'When using a black-box learning algorithm, only full episodes can be done.' ) else : self . stepid += 1 self . agent . integrateObservation ( self . task . getObservation ( ) ) self . task . performAction ( self . agent . getAction ( ) ) for i , g in enumerate ( self . task . env . case . online_generators ) : self . Pg [ i , self . stepid - 1 ] = self . Pg [ i , self . stepid - 1 ] + g . p reward = self . task . getReward ( ) self . agent . giveReward ( reward ) return reward

Does one interaction between the task and the agent .

def doEpisodes ( self , number = 1 ) : env = self . task . env self . Pg = zeros ( ( len ( env . case . online_generators ) , len ( env . profile ) ) ) rewards = super ( OPFExperiment , self ) . doEpisodes ( number ) self . Pg = self . Pg / number return rewards

Does the the given number of episodes .

def getMethodByName ( obj , name ) : try : obj = obj . _getMethodByName ( name ) except : names = name . split ( "." ) for name in names : if nameAllowed ( name ) : obj = getattr ( obj , name ) else : raise MethodNameNotAllowed ( ) return obj

searches for an object with the name given inside the object given . obj . child . meth will return the meth obj .

def waitForResponse ( self , timeOut = None ) : self . __evt . wait ( timeOut ) if self . waiting ( ) : raise Timeout ( ) else : if self . response [ "error" ] : raise Exception ( self . response [ "error" ] ) else : return self . response [ "result" ]

blocks until the response arrived or timeout is reached .

def sendRequest ( self , name , args ) : ( respEvt , id ) = self . newResponseEvent ( ) self . sendMessage ( { "id" : id , "method" : name , "params" : args } ) return respEvt

sends a request to the peer

def sendResponse ( self , id , result , error ) : self . sendMessage ( { "result" : result , "error" : error , "id" : id } )

sends a response to the peer

def newResponseEvent ( self ) : respEvt = ResponseEvent ( ) self . respLock . acquire ( ) eid = id ( respEvt ) self . respEvents [ eid ] = respEvt self . respLock . release ( ) return ( respEvt , eid )

creates a response event and adds it to a waiting list When the reponse arrives it will be removed from the list .

def handleResponse ( self , resp ) : id = resp [ "id" ] evt = self . respEvents [ id ] del ( self . respEvents [ id ] ) evt . handleResponse ( resp )

handles a response by fireing the response event for the response coming in

def handleRequest ( self , req ) : name = req [ "method" ] params = req [ "params" ] id = req [ "id" ] obj = None try : obj = getMethodByName ( self . service , name ) except MethodNameNotAllowed , e : self . sendResponse ( id , None , e ) except : self . sendResponse ( id , None , MethodNotFound ( ) ) if obj : try : rslt = obj ( * params ) self . sendResponse ( id , rslt , None ) except TypeError : s = getTracebackStr ( ) self . sendResponse ( id , None , InvalidMethodParameters ( ) ) except : s = getTracebackStr ( ) self . sendResponse ( id , None , s )

handles a request by calling the appropriete method the service exposes

def handleNotification ( self , req ) : name = req [ "method" ] params = req [ "params" ] try : obj = getMethodByName ( self . service , name ) rslt = obj ( * params ) except : pass

handles a notification request by calling the appropriete method the service exposes

def read ( self , file_or_filename ) : self . file_or_filename = file_or_filename logger . info ( "Parsing PSAT case file [%s]." % file_or_filename ) t0 = time . time ( ) self . case = Case ( ) if isinstance ( file_or_filename , basestring ) : name , _ = splitext ( basename ( file_or_filename ) ) else : name , _ = splitext ( file_or_filename . name ) self . case . name = name bus_array = self . _get_bus_array_construct ( ) line_array = self . _get_line_array_construct ( ) slack_array = self . _get_slack_array_construct ( ) pv_array = self . _get_pv_array_construct ( ) pq_array = self . _get_pq_array_construct ( ) demand_array = self . _get_demand_array_construct ( ) supply_array = self . _get_supply_array_construct ( ) case = ZeroOrMore ( matlab_comment ) + bus_array + ZeroOrMore ( matlab_comment ) + line_array + ZeroOrMore ( matlab_comment ) + slack_array + ZeroOrMore ( matlab_comment ) + pv_array + ZeroOrMore ( matlab_comment ) + pq_array + ZeroOrMore ( matlab_comment ) + demand_array + ZeroOrMore ( matlab_comment ) + supply_array case . parseFile ( file_or_filename ) elapsed = time . time ( ) - t0 logger . info ( "PSAT case file parsed in %.3fs." % elapsed ) return self . case

Parses a PSAT data file and returns a case object

def _get_bus_array_construct ( self ) : bus_no = integer . setResultsName ( "bus_no" ) v_base = real . setResultsName ( "v_base" ) v_magnitude = Optional ( real ) . setResultsName ( "v_magnitude" ) v_angle = Optional ( real ) . setResultsName ( "v_angle" ) area = Optional ( integer ) . setResultsName ( "area" ) region = Optional ( integer ) . setResultsName ( "region" ) bus_data = bus_no + v_base + v_magnitude + v_angle + area + region + scolon bus_data . setParseAction ( self . push_bus ) bus_array = Literal ( "Bus.con" ) + "=" + "[" + "..." + ZeroOrMore ( bus_data + Optional ( "]" + scolon ) ) bus_array . setParseAction ( self . sort_buses ) return bus_array

Returns a construct for an array of bus data .

def _get_line_array_construct ( self ) : from_bus = integer . setResultsName ( "fbus" ) to_bus = integer . setResultsName ( "tbus" ) s_rating = real . setResultsName ( "s_rating" ) v_rating = real . setResultsName ( "v_rating" ) f_rating = real . setResultsName ( "f_rating" ) length = real . setResultsName ( "length" ) v_ratio = real . setResultsName ( "v_ratio" ) r = real . setResultsName ( "r" ) x = real . setResultsName ( "x" ) b = real . setResultsName ( "b" ) tap_ratio = real . setResultsName ( "tap" ) phase_shift = real . setResultsName ( "shift" ) i_limit = Optional ( real ) . setResultsName ( "i_limit" ) p_limit = Optional ( real ) . setResultsName ( "p_limit" ) s_limit = Optional ( real ) . setResultsName ( "s_limit" ) status = Optional ( boolean ) . setResultsName ( "status" ) line_data = from_bus + to_bus + s_rating + v_rating + f_rating + length + v_ratio + r + x + b + tap_ratio + phase_shift + i_limit + p_limit + s_limit + status + scolon line_data . setParseAction ( self . push_line ) line_array = Literal ( "Line.con" ) + "=" + "[" + "..." + ZeroOrMore ( line_data + Optional ( "]" + scolon ) ) return line_array

Returns a construct for an array of line data .

def _get_slack_array_construct ( self ) : bus_no = integer . setResultsName ( "bus_no" ) s_rating = real . setResultsName ( "s_rating" ) v_rating = real . setResultsName ( "v_rating" ) v_magnitude = real . setResultsName ( "v_magnitude" ) ref_angle = real . setResultsName ( "ref_angle" ) q_max = Optional ( real ) . setResultsName ( "q_max" ) q_min = Optional ( real ) . setResultsName ( "q_min" ) v_max = Optional ( real ) . setResultsName ( "v_max" ) v_min = Optional ( real ) . setResultsName ( "v_min" ) p_guess = Optional ( real ) . setResultsName ( "p_guess" ) lp_coeff = Optional ( real ) . setResultsName ( "lp_coeff" ) ref_bus = Optional ( boolean ) . setResultsName ( "ref_bus" ) status = Optional ( boolean ) . setResultsName ( "status" ) slack_data = bus_no + s_rating + v_rating + v_magnitude + ref_angle + q_max + q_min + v_max + v_min + p_guess + lp_coeff + ref_bus + status + scolon slack_data . setParseAction ( self . push_slack ) slack_array = Literal ( "SW.con" ) + "=" + "[" + "..." + ZeroOrMore ( slack_data + Optional ( "]" + scolon ) ) return slack_array

Returns a construct for an array of slack bus data .

def _get_pv_array_construct ( self ) : bus_no = integer . setResultsName ( "bus_no" ) s_rating = real . setResultsName ( "s_rating" ) v_rating = real . setResultsName ( "v_rating" ) p = real . setResultsName ( "p" ) v = real . setResultsName ( "v" ) q_max = Optional ( real ) . setResultsName ( "q_max" ) q_min = Optional ( real ) . setResultsName ( "q_min" ) v_max = Optional ( real ) . setResultsName ( "v_max" ) v_min = Optional ( real ) . setResultsName ( "v_min" ) lp_coeff = Optional ( real ) . setResultsName ( "lp_coeff" ) status = Optional ( boolean ) . setResultsName ( "status" ) pv_data = bus_no + s_rating + v_rating + p + v + q_max + q_min + v_max + v_min + lp_coeff + status + scolon pv_data . setParseAction ( self . push_pv ) pv_array = Literal ( "PV.con" ) + "=" + "[" + "..." + ZeroOrMore ( pv_data + Optional ( "]" + scolon ) ) return pv_array

Returns a construct for an array of PV generator data .

def _get_pq_array_construct ( self ) : bus_no = integer . setResultsName ( "bus_no" ) s_rating = real . setResultsName ( "s_rating" ) v_rating = real . setResultsName ( "v_rating" ) p = real . setResultsName ( "p" ) q = real . setResultsName ( "q" ) v_max = Optional ( real ) . setResultsName ( "v_max" ) v_min = Optional ( real ) . setResultsName ( "v_min" ) z_conv = Optional ( boolean ) . setResultsName ( "z_conv" ) status = Optional ( boolean ) . setResultsName ( "status" ) pq_data = bus_no + s_rating + v_rating + p + q + v_max + v_min + z_conv + status + scolon pq_data . setParseAction ( self . push_pq ) pq_array = Literal ( "PQ.con" ) + "=" + "[" + "..." + ZeroOrMore ( pq_data + Optional ( "]" + scolon ) ) return pq_array

Returns a construct for an array of PQ load data .

def _get_demand_array_construct ( self ) : bus_no = integer . setResultsName ( "bus_no" ) s_rating = real . setResultsName ( "s_rating" ) p_direction = real . setResultsName ( "p_direction" ) q_direction = real . setResultsName ( "q_direction" ) p_bid_max = real . setResultsName ( "p_bid_max" ) p_bid_min = real . setResultsName ( "p_bid_min" ) p_optimal_bid = Optional ( real ) . setResultsName ( "p_optimal_bid" ) p_fixed = real . setResultsName ( "p_fixed" ) p_proportional = real . setResultsName ( "p_proportional" ) p_quadratic = real . setResultsName ( "p_quadratic" ) q_fixed = real . setResultsName ( "q_fixed" ) q_proportional = real . setResultsName ( "q_proportional" ) q_quadratic = real . setResultsName ( "q_quadratic" ) commitment = boolean . setResultsName ( "commitment" ) cost_tie_break = real . setResultsName ( "cost_tie_break" ) cost_cong_up = real . setResultsName ( "cost_cong_up" ) cost_cong_down = real . setResultsName ( "cost_cong_down" ) status = Optional ( boolean ) . setResultsName ( "status" ) demand_data = bus_no + s_rating + p_direction + q_direction + p_bid_max + p_bid_min + p_optimal_bid + p_fixed + p_proportional + p_quadratic + q_fixed + q_proportional + q_quadratic + commitment + cost_tie_break + cost_cong_up + cost_cong_down + status + scolon demand_data . setParseAction ( self . push_demand ) demand_array = Literal ( "Demand.con" ) + "=" + "[" + "..." + ZeroOrMore ( demand_data + Optional ( "]" + scolon ) ) return demand_array

Returns a construct for an array of power demand data .

def _get_supply_array_construct ( self ) : bus_no = integer . setResultsName ( "bus_no" ) s_rating = real . setResultsName ( "s_rating" ) p_direction = real . setResultsName ( "p_direction" ) p_bid_max = real . setResultsName ( "p_bid_max" ) p_bid_min = real . setResultsName ( "p_bid_min" ) p_bid_actual = real . setResultsName ( "p_bid_actual" ) p_fixed = real . setResultsName ( "p_fixed" ) p_proportional = real . setResultsName ( "p_proportional" ) p_quadratic = real . setResultsName ( "p_quadratic" ) q_fixed = real . setResultsName ( "q_fixed" ) q_proportional = real . setResultsName ( "q_proportional" ) q_quadratic = real . setResultsName ( "q_quadratic" ) commitment = boolean . setResultsName ( "commitment" ) cost_tie_break = real . setResultsName ( "cost_tie_break" ) lp_factor = real . setResultsName ( "lp_factor" ) q_max = real . setResultsName ( "q_max" ) q_min = real . setResultsName ( "q_min" ) cost_cong_up = real . setResultsName ( "cost_cong_up" ) cost_cong_down = real . setResultsName ( "cost_cong_down" ) status = Optional ( boolean ) . setResultsName ( "status" ) supply_data = bus_no + s_rating + p_direction + p_bid_max + p_bid_min + p_bid_actual + p_fixed + p_proportional + p_quadratic + q_fixed + q_proportional + q_quadratic + commitment + cost_tie_break + lp_factor + q_max + q_min + cost_cong_up + cost_cong_down + status + scolon supply_data . setParseAction ( self . push_supply ) supply_array = Literal ( "Supply.con" ) + "=" + "[" + "..." + ZeroOrMore ( supply_data + Optional ( "]" + scolon ) ) return supply_array

Returns a construct for an array of power supply data .

def _get_generator_ramping_construct ( self ) : supply_no = integer . setResultsName ( "supply_no" ) s_rating = real . setResultsName ( "s_rating" ) up_rate = real . setResultsName ( "up_rate" ) down_rate = real . setResultsName ( "down_rate" ) min_period_up = real . setResultsName ( "min_period_up" ) min_period_down = real . setResultsName ( "min_period_down" ) initial_period_up = integer . setResultsName ( "initial_period_up" ) initial_period_down = integer . setResultsName ( "initial_period_down" ) c_startup = real . setResultsName ( "c_startup" ) status = boolean . setResultsName ( "status" ) g_ramp_data = supply_no + s_rating + up_rate + down_rate + min_period_up + min_period_down + initial_period_up + initial_period_down + c_startup + status + scolon g_ramp_array = Literal ( "Rmpg.con" ) + "=" + "[" + ZeroOrMore ( g_ramp_data + Optional ( "]" + scolon ) ) return g_ramp_array

Returns a construct for an array of generator ramping data .

def _get_load_ramping_construct ( self ) : bus_no = integer . setResultsName ( "bus_no" ) s_rating = real . setResultsName ( "s_rating" ) up_rate = real . setResultsName ( "up_rate" ) down_rate = real . setResultsName ( "down_rate" ) min_up_time = real . setResultsName ( "min_up_time" ) min_down_time = real . setResultsName ( "min_down_time" ) n_period_up = integer . setResultsName ( "n_period_up" ) n_period_down = integer . setResultsName ( "n_period_down" ) status = boolean . setResultsName ( "status" ) l_ramp_data = bus_no + s_rating + up_rate + down_rate + min_up_time + min_down_time + n_period_up + n_period_down + status + scolon l_ramp_array = Literal ( "Rmpl.con" ) + "=" + "[" + ZeroOrMore ( l_ramp_data + Optional ( "]" + scolon ) ) return l_ramp_array

Returns a construct for an array of load ramping data .

def push_bus ( self , tokens ) : logger . debug ( "Pushing bus data: %s" % tokens ) bus = Bus ( ) bus . name = tokens [ "bus_no" ] bus . v_magnitude = tokens [ "v_magnitude" ] bus . v_angle = tokens [ "v_angle" ] bus . v_magnitude = tokens [ "v_magnitude" ] bus . v_angle = tokens [ "v_angle" ] self . case . buses . append ( bus )

Adds a Bus object to the case .

def push_line ( self , tokens ) : logger . debug ( "Pushing line data: %s" % tokens ) from_bus = self . case . buses [ tokens [ "fbus" ] - 1 ] to_bus = self . case . buses [ tokens [ "tbus" ] - 1 ] e = Branch ( from_bus = from_bus , to_bus = to_bus ) e . r = tokens [ "r" ] e . x = tokens [ "x" ] e . b = tokens [ "b" ] e . rate_a = tokens [ "s_limit" ] e . rate_b = tokens [ "p_limit" ] e . rate_c = tokens [ "i_limit" ] if tokens [ "tap" ] == 0 : e . ratio = 1.0 else : e . ratio = tokens [ "tap" ] e . phase_shift = tokens [ "shift" ] self . case . branches . append ( e )

Adds a Branch object to the case .

def push_slack ( self , tokens ) : logger . debug ( "Pushing slack data: %s" % tokens ) bus = self . case . buses [ tokens [ "bus_no" ] - 1 ] g = Generator ( bus ) g . q_max = tokens [ "q_max" ] g . q_min = tokens [ "q_min" ] self . case . generators . append ( g ) bus . type = "ref"

Finds the slack bus adds a Generator with the appropriate data and sets the bus type to slack .

def push_pv ( self , tokens ) : logger . debug ( "Pushing PV data: %s" % tokens ) bus = self . case . buses [ tokens [ "bus_no" ] - 1 ] g = Generator ( bus ) g . p = tokens [ "p" ] g . q_max = tokens [ "q_max" ] g . q_min = tokens [ "q_min" ] self . case . generators . append ( g )

Creates and Generator object populates it with data finds its Bus and adds it .

def push_pq ( self , tokens ) : logger . debug ( "Pushing PQ data: %s" % tokens ) bus = self . case . buses [ tokens [ "bus_no" ] - 1 ] bus . p_demand = tokens [ "p" ] bus . q_demand = tokens [ "q" ]

Creates and Load object populates it with data finds its Bus and adds it .

def push_supply ( self , tokens ) : logger . debug ( "Pushing supply data: %s" % tokens ) bus = self . case . buses [ tokens [ "bus_no" ] - 1 ] n_generators = len ( [ g for g in self . case . generators if g . bus == bus ] ) if n_generators == 0 : logger . error ( "No generator at bus [%s] for matching supply" % bus ) return elif n_generators > 1 : g = [ g for g in self . case . generators if g . bus == bus ] [ 0 ] logger . warning ( "More than one generator at bus [%s] for demand. Using the " "first one [%s]." % ( bus , g ) ) else : g = [ g for g in self . case . generators if g . bus == bus ] [ 0 ] g . pcost_model = "poly" g . poly_coeffs = ( tokens [ "p_fixed" ] , tokens [ "p_proportional" ] , tokens [ "p_quadratic" ] )

Adds OPF and CPF data to a Generator .

def _parse_file ( self , file ) : case = Case ( ) file . seek ( 0 ) line = file . readline ( ) . split ( ) if line [ 0 ] != "function" : logger . error ( "Invalid data file header." ) return case if line [ 1 ] != "mpc" : self . _is_struct = False base = "" else : base = "mpc." case . name = line [ - 1 ] for line in file : if line . startswith ( "%sbaseMVA" % base ) : case_data = line . rstrip ( ";\n" ) . split ( ) case . base_mva = float ( case_data [ - 1 ] ) elif line . startswith ( "%sbus" % base ) : self . _parse_buses ( case , file ) elif line . startswith ( "%sgencost" % base ) : self . _parse_gencost ( case , file ) elif line . startswith ( "%sgen" % base ) : self . _parse_generators ( case , file ) elif line . startswith ( "%sbranch" % base ) : self . _parse_branches ( case , file ) return case

Parses the given file - like object .

def write ( self , file_or_filename ) : if isinstance ( file_or_filename , basestring ) : self . _fcn_name , _ = splitext ( basename ( file_or_filename ) ) else : self . _fcn_name = self . case . name self . _fcn_name = self . _fcn_name . replace ( "," , "" ) . replace ( " " , "_" ) super ( MATPOWERWriter , self ) . write ( file_or_filename )

Writes case data to file in MATPOWER format .

def write_case_data ( self , file ) : file . write ( "function mpc = %s\n" % self . _fcn_name ) file . write ( '\n%%%% MATPOWER Case Format : Version %d\n' % 2 ) file . write ( "mpc.version = '%d';\n" % 2 ) file . write ( "\n%%%%----- Power Flow Data -----%%%%\n" ) file . write ( "%%%% system MVA base\n" ) file . write ( "%sbaseMVA = %g;\n" % ( self . _prefix , self . case . base_mva ) )

Writes the case data in MATPOWER format .

def write_generator_cost_data ( self , file ) : file . write ( "\n%%%% generator cost data\n" ) file . write ( "%%\t1\tstartup\tshutdown\tn\tx1\ty1\t...\txn\tyn\n" ) file . write ( "%%\t2\tstartup\tshutdown\tn\tc(n-1)\t...\tc0\n" ) file . write ( "%sgencost = [\n" % self . _prefix ) for generator in self . case . generators : n = len ( generator . p_cost ) template = '\t%d\t%g\t%g\t%d' for _ in range ( n ) : template = '%s\t%%g' % template template = '%s;\n' % template if generator . pcost_model == PW_LINEAR : t = 2 c = [ v for pc in generator . p_cost for v in pc ] elif generator . pcost_model == POLYNOMIAL : t = 1 c = list ( generator . p_cost ) else : raise vals = [ t , generator . c_startup , generator . c_shutdown , n ] + c file . write ( template % tuple ( vals ) ) file . write ( "];\n" )

Writes generator cost data to file .

def write_area_data ( self , file ) : file . write ( "%% area data" + "\n" ) file . write ( "%\tno.\tprice_ref_bus" + "\n" ) file . write ( "areas = [" + "\n" ) file . write ( "\t1\t1;" + "\n" ) file . write ( "];" + "\n" )

Writes area data to file .

def process_file ( self , language , key , token_list ) : self . language = language for tok in token_list : self . process_token ( tok )

Initiate processing for each token .

def draw_plot ( self ) : pylab . ion ( ) fig = pylab . figure ( 1 ) reward_axis = fig . add_subplot ( 3 , 1 , 3 ) reward_lines = reward_axis . plot ( self . reward_data [ 0 , 0 ] , [ 0 ] , "mx-" ) self . reward_line = reward_lines [ 0 ] pylab . draw ( )

Initialises plots of the environment .

def write_case_data ( self , file ) : change_code = 0 s_base = self . case . base_mva timestr = time . strftime ( "%Y%m%d%H%M" , time . gmtime ( ) ) file . write ( "%d, %8.2f, 30 / PSS(tm)E-30 RAW created by Pylon (%s).\n" % ( change_code , s_base , timestr ) ) file . write ( "Modified by Hantao Cui, CURENT, UTK\n " ) file . write ( "%s, %d BUSES, %d BRANCHES\n" % ( self . case . name , len ( self . case . buses ) , len ( self . case . branches ) ) )

Writes case data to file .

def plotGenCost ( generators ) : figure ( ) plots = [ ] for generator in generators : if generator . pcost_model == PW_LINEAR : x = [ x for x , _ in generator . p_cost ] y = [ y for _ , y in generator . p_cost ] elif generator . pcost_model == POLYNOMIAL : x = scipy . arange ( generator . p_min , generator . p_max , 5 ) y = scipy . polyval ( scipy . array ( generator . p_cost ) , x ) else : raise plots . append ( plot ( x , y ) ) xlabel ( "P (MW)" ) ylabel ( "Cost ($)" ) legend ( plots , [ g . name for g in generators ] ) show ( )

Plots the costs of the given generators .

def write ( self , file ) : file . write ( "State\n" ) file . write ( ( "-" * 5 ) + "\n" ) self . writeDataTable ( file , type = "state" ) file . write ( "Action\n" ) file . write ( ( "-" * 6 ) + "\n" ) self . writeDataTable ( file , type = "action" ) file . write ( "Reward\n" ) file . write ( ( "-" * 6 ) + "\n" ) self . writeDataTable ( file , type = "reward" )

Writes market experiment data to file in ReStructuredText format .

def writeDataTable ( self , file , type ) : agents = self . experiment . agents numAgents = len ( self . experiment . agents ) colWidth = 8 idxColWidth = 3 sep = ( "=" * idxColWidth ) + " " + ( "=" * colWidth + " " ) * numAgents + "\n" file . write ( sep ) file . write ( ".." . rjust ( idxColWidth ) + " " ) for agent in agents : file . write ( agent . name [ - colWidth : ] . center ( colWidth ) + " " ) file . write ( "\n" ) file . write ( sep ) if agents : rows , _ = agents [ 0 ] . history . getField ( type ) . shape else : rows , _ = ( 0 , 0 ) for sequence in range ( min ( rows , 999 ) ) : file . write ( str ( sequence + 1 ) . rjust ( idxColWidth ) + " " ) for agent in agents : field = agent . history . getField ( type ) file . write ( "%8.3f " % field [ sequence , 0 ] ) file . write ( "\n" ) file . write ( sep )

Writes agent data to an ReST table . The type argument may be state action or reward .

def performAction ( self , action ) : self . t += 1 Task . performAction ( self , action ) self . samples += 1

Execute one action .

def split_dae_alg ( eqs : SYM , dx : SYM ) -> Dict [ str , SYM ] : dae = [ ] alg = [ ] for eq in ca . vertsplit ( eqs ) : if ca . depends_on ( eq , dx ) : dae . append ( eq ) else : alg . append ( eq ) return { 'dae' : ca . vertcat ( * dae ) , 'alg' : ca . vertcat ( * alg ) }

Split equations into differential algebraic and algebraic only

def permute ( x : SYM , perm : List [ int ] ) -> SYM : x_s = [ ] for i in perm : x_s . append ( x [ i ] ) return ca . vertcat ( * x_s )

Perumute a vector

def blt ( f : List [ SYM ] , x : List [ SYM ] ) -> Dict [ str , Any ] : J = ca . jacobian ( f , x ) nblock , rowperm , colperm , rowblock , colblock , coarserow , coarsecol = J . sparsity ( ) . btf ( ) return { 'J' : J , 'nblock' : nblock , 'rowperm' : rowperm , 'colperm' : colperm , 'rowblock' : rowblock , 'colblock' : colblock , 'coarserow' : coarserow , 'coarsecol' : coarsecol }

Sort equations by dependence

def create_function_f_m ( self ) : return ca . Function ( 'f_m' , [ self . t , self . x , self . y , self . m , self . p , self . c , self . pre_c , self . ng , self . nu ] , [ self . f_m ] , [ 't' , 'x' , 'y' , 'm' , 'p' , 'c' , 'pre_c' , 'ng' , 'nu' ] , [ 'm' ] , self . func_opt )

Discrete state dynamics

def create_function_f_J ( self ) : return ca . Function ( 'J' , [ self . t , self . x , self . y , self . m , self . p , self . c , self . ng , self . nu ] , [ ca . jacobian ( self . f_x_rhs , self . x ) ] , [ 't' , 'x' , 'y' , 'm' , 'p' , 'c' , 'ng' , 'nu' ] , [ 'J' ] , self . func_opt )

Jacobian for state integration

def to_ode ( self ) -> HybridOde : res_split = split_dae_alg ( self . f_x , self . dx ) alg = res_split [ 'alg' ] dae = res_split [ 'dae' ] x_rhs = tangent_approx ( dae , self . dx , assert_linear = True ) y_rhs = tangent_approx ( alg , self . y , assert_linear = True ) return HybridOde ( c = self . c , dx = self . dx , f_c = self . f_c , f_i = self . f_i , f_m = self . f_m , f_x_rhs = x_rhs , y_rhs = y_rhs , m = self . m , ng = self . ng , nu = self . nu , p = self . p , pre_m = self . pre_m , pre_c = self . pre_c , prop = self . prop , sym = self . sym , t = self . t , x = self . x , y = self . y , )

Convert to a HybridOde

def format_from_extension ( fname ) : _base , ext = os . path . splitext ( fname ) if not ext : return None try : format = known_extensions [ ext . replace ( '.' , '' ) ] except KeyError : format = None return format

Tries to infer a protocol from the file extension .

def pickle_matpower_cases ( case_paths , case_format = 2 ) : import pylon . io if isinstance ( case_paths , basestring ) : case_paths = [ case_paths ] for case_path in case_paths : case = pylon . io . MATPOWERReader ( case_format ) . read ( case_path ) dir_path = os . path . dirname ( case_path ) case_basename = os . path . basename ( case_path ) root , _ = os . path . splitext ( case_basename ) pickled_case_path = os . path . join ( dir_path , root + '.pkl' ) pylon . io . PickleWriter ( case ) . write ( pickled_case_path )

Parses the MATPOWER case files at the given paths and pickles the resulting Case objects to the same directory .

def fair_max ( x ) : value = max ( x ) i = [ x . index ( v ) for v in x if v == value ] idx = random . choice ( i ) return idx , value

Takes a single iterable as an argument and returns the same output as the built - in function max with two output parameters except that where the maximum value occurs at more than one position in the vector the index is chosen randomly from these positions as opposed to just choosing the first occurance .

def factorial ( n ) : f = 1 while ( n > 0 ) : f = f * n n = n - 1 return f

Returns the factorial of n .

def _get_name ( self ) : if self . _name is None : self . _name = self . _generate_name ( ) return self . _name

Returns the name which is generated if it has not been already .

def save_to_file_object ( self , fd , format = None , ** kwargs ) : format = 'pickle' if format is None else format save = getattr ( self , "save_%s" % format , None ) if save is None : raise ValueError ( "Unknown format '%s'." % format ) save ( fd , ** kwargs )

Save the object to a given file like object in the given format .

def load_from_file_object ( cls , fd , format = None ) : format = 'pickle' if format is None else format load = getattr ( cls , "load_%s" % format , None ) if load is None : raise ValueError ( "Unknown format '%s'." % format ) return load ( fd )

Load the object from a given file like object in the given format .

def save ( self , filename , format = None , ** kwargs ) : if format is None : format = format_from_extension ( filename ) with file ( filename , 'wb' ) as fp : self . save_to_file_object ( fp , format , ** kwargs )

Save the object to file given by filename .

def load ( cls , filename , format = None ) : if format is None : format = format_from_extension ( filename ) with file ( filename , 'rbU' ) as fp : obj = cls . load_from_file_object ( fp , format ) obj . filename = filename return obj

Return an instance of the class that is saved in the file with the given filename in the specified format .

def solve ( self ) : case = self . case logger . info ( "Starting DC power flow [%s]." % case . name ) t0 = time . time ( ) self . case . index_buses ( ) ref_idx = self . _get_reference_index ( case ) if ref_idx < 0 : return False B , Bsrc , p_businj , p_srcinj = case . Bdc v_angle_guess = self . _get_v_angle_guess ( case ) v_angle , p_ref = self . _get_v_angle ( case , B , v_angle_guess , p_businj , ref_idx ) logger . debug ( "Bus voltage phase angles: \n%s" % v_angle ) self . v_angle = v_angle self . _update_model ( case , B , Bsrc , v_angle , p_srcinj , p_ref , ref_idx ) logger . info ( "DC power flow completed in %.3fs." % ( time . time ( ) - t0 ) ) return True

Solves a DC power flow .

def _get_reference_index ( self , case ) : refs = [ bus . _i for bus in case . connected_buses if bus . type == REFERENCE ] if len ( refs ) == 1 : return refs [ 0 ] else : logger . error ( "Single swing bus required for DCPF." ) return - 1

Returns the index of the reference bus .

def _get_v_angle_guess ( self , case ) : v_angle = array ( [ bus . v_angle * ( pi / 180.0 ) for bus in case . connected_buses ] ) return v_angle

Make the vector of voltage phase guesses .

def _get_v_angle ( self , case , B , v_angle_guess , p_businj , iref ) : buses = case . connected_buses pv_idxs = [ bus . _i for bus in buses if bus . type == PV ] pq_idxs = [ bus . _i for bus in buses if bus . type == PQ ] pvpq_idxs = pv_idxs + pq_idxs pvpq_rows = [ [ i ] for i in pvpq_idxs ] Bpvpq = B [ pvpq_rows , pvpq_idxs ] Bref = B [ pvpq_rows , [ iref ] ] p_surplus = array ( [ case . s_surplus ( v ) . real for v in buses ] ) g_shunt = array ( [ bus . g_shunt for bus in buses ] ) Pbus = ( p_surplus - p_businj - g_shunt ) / case . base_mva Pbus . shape = len ( Pbus ) , 1 A = Bpvpq b = Pbus [ pvpq_idxs ] - Bref * v_angle_guess [ iref ] x = spsolve ( A , b ) v_angle = r_ [ x [ : iref ] , v_angle_guess [ iref ] , x [ iref : ] ] return v_angle , Pbus [ iref ]

Calculates the voltage phase angles .

def _update_model ( self , case , B , Bsrc , v_angle , p_srcinj , p_ref , ref_idx ) : iref = ref_idx base_mva = case . base_mva buses = case . connected_buses branches = case . online_branches p_from = ( Bsrc * v_angle + p_srcinj ) * base_mva p_to = - p_from for i , branch in enumerate ( branches ) : branch . p_from = p_from [ i ] branch . p_to = p_to [ i ] branch . q_from = 0.0 branch . q_to = 0.0 for j , bus in enumerate ( buses ) : bus . v_angle = v_angle [ j ] * ( 180 / pi ) bus . v_magnitude = 1.0 g_ref = [ g for g in case . generators if g . bus == buses [ iref ] ] [ 0 ] p_inj = ( B [ iref , : ] * v_angle - p_ref ) * base_mva g_ref . p += p_inj [ 0 ]

Updates the case with values computed from the voltage phase angle solution .

def getSbus ( self , buses = None ) : bs = self . buses if buses is None else buses s = array ( [ self . s_surplus ( v ) / self . base_mva for v in bs ] ) return s

Returns the net complex bus power injection vector in p . u .

def sort_generators ( self ) : self . generators . sort ( key = lambda gn : gn . bus . _i )

Reorders the list of generators according to bus index .

def index_buses ( self , buses = None , start = 0 ) : bs = self . connected_buses if buses is None else buses for i , b in enumerate ( bs ) : b . _i = start + i

Updates the indices of all buses .

def index_branches ( self , branches = None , start = 0 ) : ln = self . online_branches if branches is None else branches for i , l in enumerate ( ln ) : l . _i = start + i

Updates the indices of all branches .

def s_supply ( self , bus ) : Sg = array ( [ complex ( g . p , g . q ) for g in self . generators if ( g . bus == bus ) and not g . is_load ] , dtype = complex64 ) if len ( Sg ) : return sum ( Sg ) else : return 0 + 0j

Returns the total complex power generation capacity .

def s_demand ( self , bus ) : Svl = array ( [ complex ( g . p , g . q ) for g in self . generators if ( g . bus == bus ) and g . is_load ] , dtype = complex64 ) Sd = complex ( bus . p_demand , bus . q_demand ) return - sum ( Svl ) + Sd

Returns the total complex power demand .

def reset ( self ) : for bus in self . buses : bus . reset ( ) for branch in self . branches : branch . reset ( ) for generator in self . generators : generator . reset ( )

Resets the readonly variables for all of the case components .

def save_matpower ( self , fd ) : from pylon . io import MATPOWERWriter MATPOWERWriter ( self ) . write ( fd )

Serialize the case as a MATPOWER data file .

def load_psat ( cls , fd ) : from pylon . io . psat import PSATReader return PSATReader ( ) . read ( fd )

Returns a case object from the given PSAT data file .

def save_rst ( self , fd ) : from pylon . io import ReSTWriter ReSTWriter ( self ) . write ( fd )

Save a reStructuredText representation of the case .

def save_csv ( self , fd ) : from pylon . io . excel import CSVWriter CSVWriter ( self ) . write ( fd )

Saves the case as a series of Comma - Separated Values .

def save_excel ( self , fd ) : from pylon . io . excel import ExcelWriter ExcelWriter ( self ) . write ( fd )

Saves the case as an Excel spreadsheet .

def save_dot ( self , fd ) : from pylon . io import DotWriter DotWriter ( self ) . write ( fd )

Saves a representation of the case in the Graphviz DOT language .

def solve ( self ) : self . case . reset ( ) b , l , g , _ , _ , _ , _ = self . _unpack_case ( self . case ) self . case . index_buses ( b ) refs , pq , pv , pvpq = self . _index_buses ( b ) if len ( refs ) != 1 : logger . error ( "Swing bus required for DCPF." ) return { "converged" : False } t0 = time ( ) V0 = self . _initial_voltage ( b , g ) repeat = True while repeat : Ybus , Yf , Yt = self . case . getYbus ( b , l ) Sbus = self . case . getSbus ( b ) V , converged , i = self . _run_power_flow ( Ybus , Sbus , V0 , pv , pq , pvpq ) self . case . pf_solution ( Ybus , Yf , Yt , V ) if self . qlimit : raise NotImplementedError else : repeat = False elapsed = time ( ) - t0 if converged and self . verbose : logger . info ( "AC power flow converged in %.3fs" % elapsed ) return { "converged" : converged , "elapsed" : elapsed , "iterations" : i , "V" : V }

Runs a power flow

def _unpack_case ( self , case ) : base_mva = case . base_mva b = case . connected_buses l = case . online_branches g = case . online_generators nb = len ( b ) nl = len ( l ) ng = len ( g ) return b , l , g , nb , nl , ng , base_mva

Returns the contents of the case to be used in the OPF .

def _index_buses ( self , buses ) : refs = [ bus . _i for bus in buses if bus . type == REFERENCE ] pv = [ bus . _i for bus in buses if bus . type == PV ] pq = [ bus . _i for bus in buses if bus . type == PQ ] pvpq = pv + pq return refs , pq , pv , pvpq

Set up indexing for updating v .

def _initial_voltage ( self , buses , generators ) : Vm = array ( [ bus . v_magnitude for bus in buses ] ) Va = array ( [ bus . v_angle * ( pi / 180.0 ) for bus in buses ] ) V = Vm * exp ( 1j * Va ) for g in generators : i = g . bus . _i V [ i ] = g . v_magnitude / abs ( V [ i ] ) * V [ i ] return V

Returns the initial vector of complex bus voltages .

def _one_iteration ( self , F , Ybus , V , Vm , Va , pv , pq , pvpq ) : J = self . _build_jacobian ( Ybus , V , pv , pq , pvpq ) dx = - 1 * spsolve ( J , F ) npv = len ( pv ) npq = len ( pq ) if npv > 0 : Va [ pv ] = Va [ pv ] + dx [ range ( npv ) ] if npq > 0 : Va [ pq ] = Va [ pq ] + dx [ range ( npv , npv + npq ) ] Vm [ pq ] = Vm [ pq ] + dx [ range ( npv + npq , npv + npq + npq ) ] V = Vm * exp ( 1j * Va ) Vm = abs ( V ) Va = angle ( V ) return V , Vm , Va

Performs one Newton iteration .

def _build_jacobian ( self , Ybus , V , pv , pq , pvpq ) : pq_col = [ [ i ] for i in pq ] pvpq_col = [ [ i ] for i in pvpq ] dS_dVm , dS_dVa = self . case . dSbus_dV ( Ybus , V ) J11 = dS_dVa [ pvpq_col , pvpq ] . real J12 = dS_dVm [ pvpq_col , pq ] . real J21 = dS_dVa [ pq_col , pvpq ] . imag J22 = dS_dVm [ pq_col , pq ] . imag J = vstack ( [ hstack ( [ J11 , J12 ] ) , hstack ( [ J21 , J22 ] ) ] , format = "csr" ) return J

Returns the Jacobian matrix .

def _evaluate_mismatch ( self , Ybus , V , Sbus , pq , pvpq ) : mis = ( multiply ( V , conj ( Ybus * V ) ) - Sbus ) / abs ( V ) P = mis [ pvpq ] . real Q = mis [ pq ] . imag return P , Q

Evaluates the mismatch .

def _p_iteration ( self , P , Bp_solver , Vm , Va , pvpq ) : dVa = - Bp_solver . solve ( P ) Va [ pvpq ] = Va [ pvpq ] + dVa V = Vm * exp ( 1j * Va ) return V , Vm , Va

Performs a P iteration updates Va .