profitByPlant.h

/*
** Copyright 2007-2024, RTE (https://www.rte-france.com)
** See AUTHORS.txt
** SPDX-License-Identifier: MPL-2.0
** This file is part of Antares-Simulator,
** Adequacy and Performance assessment for interconnected energy networks.
**
** Antares_Simulator is free software: you can redistribute it and/or modify
** it under the terms of the Mozilla Public Licence 2.0 as published by
** the Mozilla Foundation, either version 2 of the License, or
** (at your option) any later version.
**
** Antares_Simulator is distributed in the hope that it will be useful,
** but WITHOUT ANY WARRANTY; without even the implied warranty of
** MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
** Mozilla Public Licence 2.0 for more details.
**
** You should have received a copy of the Mozilla Public Licence 2.0
** along with Antares_Simulator. If not, see <https://opensource.org/license/mpl-2-0/>.
*/
 
#pragma once
 
#include "antares/solver/variable/variable.h"
 
namespace Antares
{
namespace Solver
{
namespace Variable
{
namespace Economy
{
struct VCardProfitByPlant
{
    static std::string Caption()
    {
        return "Profit by plant";
    }
 
    static std::string Unit()
    {
        return "Profit - Euro";
    }
 
    static std::string Description()
    {
        return "Profit for thermal units";
    }
 
    typedef Results<R::AllYears::Average< // The average values throughout all years
      >>
      ResultsType;
 
    typedef VCardProfitByPlant VCardForSpatialAggregate;
 
    static constexpr uint8_t categoryDataLevel = Category::DataLevel::area;
    static constexpr uint8_t categoryFileLevel = ResultsType::categoryFile
                                                 & (Category::FileLevel::de);
    static constexpr uint8_t precision = Category::all;
    static constexpr uint8_t nodeDepthForGUI = +0;
    static constexpr uint8_t decimal = 0;
    static constexpr int columnCount = Category::dynamicColumns;
    static constexpr uint8_t spatialAggregate = Category::spatialAggregateSum;
    static constexpr uint8_t spatialAggregateMode = Category::spatialAggregateEachYear;
    static constexpr uint8_t spatialAggregatePostProcessing = 0;
    static constexpr uint8_t hasIntermediateValues = 1;
    static constexpr uint8_t isPossiblyNonApplicable = 0;
 
    typedef IntermediateValues IntermediateValuesDeepType;
    typedef std::vector<IntermediateValues> IntermediateValuesBaseType;
    typedef std::vector<IntermediateValuesBaseType> IntermediateValuesType;
}; // class VCard
 
template<class NextT = Container::EndOfList>
class ProfitByPlant: public Variable::IVariable<ProfitByPlant<NextT>, NextT, VCardProfitByPlant>
{
public:
    typedef NextT NextType;
    typedef VCardProfitByPlant VCardType;
    typedef Variable::IVariable<ProfitByPlant<NextT>, NextT, VCardType> AncestorType;
 
    typedef typename VCardType::ResultsType ResultsType;
 
    typedef VariableAccessor<ResultsType, VCardType::columnCount> VariableAccessorType;
 
    enum
    {
        count = 1 + NextT::count,
    };
 
    template<int CDataLevel, int CFile>
    struct Statistics
    {
        enum
        {
            count = ((VCardType::categoryDataLevel & CDataLevel
                      && VCardType::categoryFileLevel & CFile)
                       ? (NextType::template Statistics<CDataLevel, CFile>::count
                          + VCardType::columnCount * ResultsType::count)
                       : NextType::template Statistics<CDataLevel, CFile>::count),
        };
    };
 
public:
    ProfitByPlant():
        pNbClustersOfArea(0)
    {
    }
 
    void initializeFromStudy(Data::Study& study)
    {
        // Next
        NextType::initializeFromStudy(study);
    }
 
    void initializeFromArea(Data::Study* study, Data::Area* area)
    {
        // Get the number of years in parallel
        pNbYearsParallel = study->maxNbYearsInParallel;
        pValuesForTheCurrentYear.resize(pNbYearsParallel);
 
        // Get the area
        pNbClustersOfArea = area->thermal.list.enabledCount();
        if (pNbClustersOfArea)
        {
            AncestorType::pResults.resize(pNbClustersOfArea);
            for (unsigned int numSpace = 0; numSpace < pNbYearsParallel; numSpace++)
            {
                pValuesForTheCurrentYear[numSpace].resize(pNbClustersOfArea);
            }
 
            for (unsigned int numSpace = 0; numSpace < pNbYearsParallel; numSpace++)
            {
                for (unsigned int i = 0; i != pNbClustersOfArea; ++i)
                {
                    pValuesForTheCurrentYear[numSpace][i].initializeFromStudy(*study);
                }
            }
 
            for (unsigned int i = 0; i != pNbClustersOfArea; ++i)
            {
                AncestorType::pResults[i].initializeFromStudy(*study);
                AncestorType::pResults[i].reset();
            }
        }
        else
        {
            AncestorType::pResults.clear();
        }
 
        // Next
        NextType::initializeFromArea(study, area);
    }
 
    size_t getMaxNumberColumns() const
    {
        return pNbClustersOfArea * ResultsType::count;
    }
 
    void initializeFromLink(Data::Study* study, Data::AreaLink* link)
    {
        // Next
        NextType::initializeFromAreaLink(study, link);
    }
 
    void simulationBegin()
    {
        // Next
        NextType::simulationBegin();
    }
 
    void simulationEnd()
    {
        NextType::simulationEnd();
    }
 
    void yearBegin(unsigned int year, unsigned int numSpace)
    {
        // Reset the values for the current year
        for (unsigned int i = 0; i != pNbClustersOfArea; ++i)
        {
            pValuesForTheCurrentYear[numSpace][i].reset();
        }
 
        // Next variable
        NextType::yearBegin(year, numSpace);
    }
 
    void yearEndBuild(State& state, unsigned int year, unsigned int numSpace)
    {
        // Next variable
        NextType::yearEndBuild(state, year, numSpace);
    }
 
    void yearEnd(unsigned int year, unsigned int numSpace)
    {
        // Merge all results for all thermal clusters
        {
            for (unsigned int i = 0; i < pNbClustersOfArea; ++i)
            {
                // Compute all statistics for the current year (daily,weekly,monthly)
                pValuesForTheCurrentYear[numSpace][i].computeStatisticsForTheCurrentYear();
            }
        }
        // Next variable
        NextType::yearEnd(year, numSpace);
    }
 
    void computeSummary(std::map<unsigned int, unsigned int>& numSpaceToYear,
                        unsigned int nbYearsForCurrentSummary)
    {
        for (unsigned int numSpace = 0; numSpace < nbYearsForCurrentSummary; ++numSpace)
        {
            for (unsigned int i = 0; i < pNbClustersOfArea; ++i)
            {
                // Merge all those values with the global results
                AncestorType::pResults[i].merge(numSpaceToYear[numSpace],
                                                pValuesForTheCurrentYear[numSpace][i]);
            }
        }
 
        // Next variable
        NextType::computeSummary(numSpaceToYear, nbYearsForCurrentSummary);
    }
 
    void hourBegin(unsigned int hourInTheYear)
    {
        // Next variable
        NextType::hourBegin(hourInTheYear);
    }
 
    void hourForEachArea(State& state, unsigned int numSpace)
    {
        // Useful local variables
        auto area = state.area;
        auto& thermal = state.thermal;
        const std::vector<double>& areaMarginalCosts = state.hourlyResults->CoutsMarginauxHoraires;
        uint hourInTheWeek = state.hourInTheWeek;
        uint hourInTheYear = state.hourInTheYear;
 
        for (auto& cluster: area->thermal.list.each_enabled())
        {
            double hourlyClusterProduction = thermal[area->index]
                                               .thermalClustersProductions[cluster->enabledIndex];
            uint tsIndex = cluster->series.timeseriesNumbers[state.year];
 
            // Thermal cluster profit
            pValuesForTheCurrentYear[numSpace][cluster->enabledIndex].hour[hourInTheYear]
              = std::max((hourlyClusterProduction - cluster->PthetaInf[hourInTheYear]), 0.)
                * (-areaMarginalCosts[hourInTheWeek]
                   - cluster->getCostProvider().getMarginalCost(tsIndex, hourInTheYear));
        }
 
        // Next variable
        NextType::hourForEachArea(state, numSpace);
    }
 
    Antares::Memory::Stored<double>::ConstReturnType retrieveRawHourlyValuesForCurrentYear(
      unsigned int,
      unsigned int numSpace) const
    {
        return pValuesForTheCurrentYear[numSpace][0].hour;
    }
 
    void localBuildAnnualSurveyReport(SurveyResults& results,
                                      int fileLevel,
                                      int precision,
                                      unsigned int numSpace) const
    {
        // Initializing external pointer on current variable non applicable status
        results.isCurrentVarNA = AncestorType::isNonApplicable;
 
        if (AncestorType::isPrinted[0])
        {
            assert(NULL != results.data.area);
            const auto& thermal = results.data.area->thermal;
 
            // Write the data for the current year
            for (auto& cluster: thermal.list.each_enabled())
            {
                // Write the data for the current year
                results.variableCaption = cluster->name(); // VCardType::Caption();
                results.variableUnit = VCardType::Unit();
                pValuesForTheCurrentYear[numSpace][cluster->enabledIndex]
                  .template buildAnnualSurveyReport<VCardType>(results, fileLevel, precision);
            }
        }
    }
 
private:
    typename VCardType::IntermediateValuesType pValuesForTheCurrentYear;
    size_t pNbClustersOfArea;
    unsigned int pNbYearsParallel;
 
}; // class
 
} // namespace Economy
} // namespace Variable
} // namespace Solver
} // namespace Antares