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{"load_seed": 383329927, "renew_seed": 3324115916, "gen_p_forecast_seed": 2811363264}
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{"length": 2018}
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{
"amount_curtailed_for": 469426.61708912934,
"avg": 3.1741631412533544e-06,
"forecast_generation_time": 228.77297825299996,
"forecasts_nb_fail": 27,
"forecasts_t0_errors": {
"1323": "cvxpy failed to find a solution for t0 1323 and returned an infinite cost",
"1324": "cvxpy failed to find a solution for t0 1324 and returned an infinite cost",
"1325": "cvxpy failed to find a solution for t0 1325 and returned an infinite cost",
"1326": "cvxpy failed to find a solution for t0 1326 and returned an infinite cost",
"1327": "cvxpy failed to find a solution for t0 1327 and returned an infinite cost",
"1328": "cvxpy failed to find a solution for t0 1328 and returned an infinite cost",
"1329": "cvxpy failed to find a solution for t0 1329 and returned an infinite cost",
"1724": "cvxpy failed to find a solution for t0 1724 and returned an infinite cost",
"1725": "cvxpy failed to find a solution for t0 1725 and returned an infinite cost",
"1726": "cvxpy failed to find a solution for t0 1726 and returned an infinite cost",
"1727": "cvxpy failed to find a solution for t0 1727 and returned an infinite cost",
"1728": "cvxpy failed to find a solution for t0 1728 and returned an infinite cost",
"1785": "cvxpy failed to find a solution for t0 1785 and returned an infinite cost",
"1786": "cvxpy failed to find a solution for t0 1786 and returned an infinite cost",
"1787": "cvxpy failed to find a solution for t0 1787 and returned an infinite cost",
"1788": "cvxpy failed to find a solution for t0 1788 and returned an infinite cost",
"1789": "cvxpy failed to find a solution for t0 1789 and returned an infinite cost",
"1790": "cvxpy failed to find a solution for t0 1790 and returned an infinite cost",
"1791": "cvxpy failed to find a solution for t0 1791 and returned an infinite cost",
"1792": "cvxpy failed to find a solution for t0 1792 and returned an infinite cost",
"1793": "cvxpy failed to find a solution for t0 1793 and returned an infinite cost",
"1794": "cvxpy failed to find a solution for t0 1794 and returned an infinite cost",
"1795": "cvxpy failed to find a solution for t0 1795 and returned an infinite cost",
"1821": "cvxpy failed to find a solution for t0 1821 and returned an infinite cost",
"1822": "cvxpy failed to find a solution for t0 1822 and returned an infinite cost",
"1823": "cvxpy failed to find a solution for t0 1823 and returned an infinite cost",
"1824": "cvxpy failed to find a solution for t0 1824 and returned an infinite cost"
},
"generation_time": 367.686130256,
"info": [
"avg, percent_95, percent_99, max: this 'quality' is the difference between the DC solver and the AC solver. This is the number of MW that will differ from the grid2op observation compared to the generated data by chronix2grid.",
"total_load, total_gen: total amount of energy consumed / produced for the generated scenario.",
"losses_mwh: total amount of losses for the scenario (in energy)",
"losses_avg: average (per step) of the loss (avg[loss_this_step / total_generation_this_step])",
"wind_curtailed_opf: total (in energy) wind power curtailed by the OPF",
"wind_curtailed_losses: total (in energy) wind power curtailed by the loss",
"solar_curtailed_opf: total (in energy) solar power curtailed by the OPF",
"iter_num: number of iteration of the loss algorithm",
"generation_time: total time spent to generate these data (in seconds)",
"saving_time: total time spent to save the generated data (in seconds), this excludes the metadata saving time",
"amount_curtailed_for: sum of all the power that has been curtailed for the forecasts"
],
"iter_num": 4,
"losses_avg": 0.025284625460195272,
"losses_mwh": 15341.746037597302,
"max": 0.0029449462890625,
"percent_95": 0.0,
"percent_99": 0.0001068115234375,
"saving_time": 8.158646755999996,
"solar_curtailed_opf": 2.3909534017244973e-05,
"total_gen": 601907.625,
"total_load": 586565.8789624027,
"wind_curtailed_losses": -0.014984166657086462,
"wind_curtailed_opf": 225.9584371978805
}
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{
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"41_48_131", "39_41_121", "43_44_125", "44_45_126", "34_35_110",
"54_58_154", "74_117_81", "80_79_175", "93_95_43", "88_91_33",
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2034-12-31 23:55
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00:05
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{"load_seed": 383329927, "renew_seed": 3324115916, "gen_p_forecast_seed": 2811363264}
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{"length": 2018}
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{
"amount_curtailed_for": 463154.47103195434,
"avg": 3.906881616008781e-06,
"forecast_generation_time": 272.795833097,
"forecasts_nb_fail": 17,
"forecasts_t0_errors": {
"1276": "cvxpy failed to find a solution for t0 1276 and returned an infinite cost",
"1325": "cvxpy failed to find a solution for t0 1325 and returned an infinite cost",
"1725": "cvxpy failed to find a solution for t0 1725 and returned an infinite cost",
"1726": "cvxpy failed to find a solution for t0 1726 and returned an infinite cost",
"1727": "cvxpy failed to find a solution for t0 1727 and returned an infinite cost",
"1783": "cvxpy failed to find a solution for t0 1783 and returned an infinite cost",
"1784": "cvxpy failed to find a solution for t0 1784 and returned an infinite cost",
"1785": "cvxpy failed to find a solution for t0 1785 and returned an infinite cost",
"1786": "cvxpy failed to find a solution for t0 1786 and returned an infinite cost",
"1787": "cvxpy failed to find a solution for t0 1787 and returned an infinite cost",
"1788": "cvxpy failed to find a solution for t0 1788 and returned an infinite cost",
"1789": "cvxpy failed to find a solution for t0 1789 and returned an infinite cost",
"1790": "cvxpy failed to find a solution for t0 1790 and returned an infinite cost",
"1791": "cvxpy failed to find a solution for t0 1791 and returned an infinite cost",
"1792": "cvxpy failed to find a solution for t0 1792 and returned an infinite cost",
"1793": "cvxpy failed to find a solution for t0 1793 and returned an infinite cost",
"1794": "cvxpy failed to find a solution for t0 1794 and returned an infinite cost"
},
"generation_time": 457.9057276350002,
"info": [
"avg, percent_95, percent_99, max: this 'quality' is the difference between the DC solver and the AC solver. This is the number of MW that will differ from the grid2op observation compared to the generated data by chronix2grid.",
"total_load, total_gen: total amount of energy consumed / produced for the generated scenario.",
"losses_mwh: total amount of losses for the scenario (in energy)",
"losses_avg: average (per step) of the loss (avg[loss_this_step / total_generation_this_step])",
"wind_curtailed_opf: total (in energy) wind power curtailed by the OPF",
"wind_curtailed_losses: total (in energy) wind power curtailed by the loss",
"solar_curtailed_opf: total (in energy) solar power curtailed by the OPF",
"iter_num: number of iteration of the loss algorithm",
"generation_time: total time spent to generate these data (in seconds)",
"saving_time: total time spent to save the generated data (in seconds), this excludes the metadata saving time",
"amount_curtailed_for: sum of all the power that has been curtailed for the forecasts"
],
"iter_num": 4,
"losses_avg": 0.02488959669350729,
"losses_mwh": 15770.240967319114,
"max": 0.003856658935546875,
"percent_95": 0.0,
"percent_99": 0.0001220703125,
"saving_time": 9.174658130999887,
"solar_curtailed_opf": -5.658737306172649e-05,
"total_gen": 628784.4583333333,
"total_load": 613014.2173660141,
"wind_curtailed_losses": -0.010934166668448597,
"wind_curtailed_opf": 83.73941451240292
}
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{
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"29_37_117","62_58_180", "62_63_160", "48_50_136", "48_53_141",
"41_48_131", "39_41_121", "43_44_125", "44_45_126", "34_35_110",
"54_58_154", "74_117_81", "80_79_175", "93_95_43", "88_91_33",
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2035-02-28 23:55
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00:05
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{"load_seed": 383329927, "renew_seed": 3324115916, "gen_p_forecast_seed": 2811363264}
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{"length": 2018}
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{
"amount_curtailed_for": 501466.2740727471,
"avg": 1.733146583817873e-05,
"forecast_generation_time": 212.39482305899992,
"forecasts_nb_fail": 11,
"forecasts_t0_errors": {
"1726": "cvxpy failed to find a solution for t0 1726 and returned an infinite cost",
"1727": "cvxpy failed to find a solution for t0 1727 and returned an infinite cost",
"1784": "cvxpy failed to find a solution for t0 1784 and returned an infinite cost",
"1785": "cvxpy failed to find a solution for t0 1785 and returned an infinite cost",
"1786": "cvxpy failed to find a solution for t0 1786 and returned an infinite cost",
"1787": "cvxpy failed to find a solution for t0 1787 and returned an infinite cost",
"1788": "cvxpy failed to find a solution for t0 1788 and returned an infinite cost",
"1789": "cvxpy failed to find a solution for t0 1789 and returned an infinite cost",
"1790": "cvxpy failed to find a solution for t0 1790 and returned an infinite cost",
"1791": "cvxpy failed to find a solution for t0 1791 and returned an infinite cost",
"1792": "cvxpy failed to find a solution for t0 1792 and returned an infinite cost"
},
"generation_time": 384.1067777760002,
"info": [
"avg, percent_95, percent_99, max: this 'quality' is the difference between the DC solver and the AC solver. This is the number of MW that will differ from the grid2op observation compared to the generated data by chronix2grid.",
"total_load, total_gen: total amount of energy consumed / produced for the generated scenario.",
"losses_mwh: total amount of losses for the scenario (in energy)",
"losses_avg: average (per step) of the loss (avg[loss_this_step / total_generation_this_step])",
"wind_curtailed_opf: total (in energy) wind power curtailed by the OPF",
"wind_curtailed_losses: total (in energy) wind power curtailed by the loss",
"solar_curtailed_opf: total (in energy) solar power curtailed by the OPF",
"iter_num: number of iteration of the loss algorithm",
"generation_time: total time spent to generate these data (in seconds)",
"saving_time: total time spent to save the generated data (in seconds), this excludes the metadata saving time",
"amount_curtailed_for: sum of all the power that has been curtailed for the forecasts"
],
"iter_num": 3,
"losses_avg": 0.024323979932060473,
"losses_mwh": 9867.609543586537,
"max": 0.0142059326171875,
"percent_95": 0.0,
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"saving_time": 8.828537806999975,
"solar_curtailed_opf": 4.8455710828226675,
"total_gen": 399508.7916666666,
"total_load": 389641.1821230801,
"wind_curtailed_losses": 0.004582499997923151,
"wind_curtailed_opf": 3848.4592719879192
}
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{
"maintenance_starting_hour": 9,
"maintenance_ending_hour": 17,
"line_to_maintenance": ["26_31_106", "21_22_93", "17_18_88", "4_10_162", "12_14_68",
"29_37_117","62_58_180", "62_63_160", "48_50_136", "48_53_141",
"41_48_131", "39_41_121", "43_44_125", "44_45_126", "34_35_110",
"54_58_154", "74_117_81", "80_79_175", "93_95_43", "88_91_33",
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1, 0, 0]
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2035-06-30 23:55
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00:05
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{"load_seed": 383329927, "renew_seed": 3324115916, "gen_p_forecast_seed": 2811363264}
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{"length": 2018}
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{
"amount_curtailed_for": 449900.24014652014,
"avg": 1.961877192906389e-05,
"forecast_generation_time": 203.90490188600006,
"forecasts_nb_fail": 12,
"forecasts_t0_errors": {
"1726": "cvxpy failed to find a solution for t0 1726 and returned an infinite cost",
"1727": "cvxpy failed to find a solution for t0 1727 and returned an infinite cost",
"1728": "cvxpy failed to find a solution for t0 1728 and returned an infinite cost",
"1729": "cvxpy failed to find a solution for t0 1729 and returned an infinite cost",
"1730": "cvxpy failed to find a solution for t0 1730 and returned an infinite cost",
"1788": "cvxpy failed to find a solution for t0 1788 and returned an infinite cost",
"1789": "cvxpy failed to find a solution for t0 1789 and returned an infinite cost",
"1790": "cvxpy failed to find a solution for t0 1790 and returned an infinite cost",
"1791": "cvxpy failed to find a solution for t0 1791 and returned an infinite cost",
"1792": "cvxpy failed to find a solution for t0 1792 and returned an infinite cost",
"1793": "cvxpy failed to find a solution for t0 1793 and returned an infinite cost",
"1794": "cvxpy failed to find a solution for t0 1794 and returned an infinite cost"
},
"generation_time": 349.7025029020001,
"info": [
"avg, percent_95, percent_99, max: this 'quality' is the difference between the DC solver and the AC solver. This is the number of MW that will differ from the grid2op observation compared to the generated data by chronix2grid.",
"total_load, total_gen: total amount of energy consumed / produced for the generated scenario.",
"losses_mwh: total amount of losses for the scenario (in energy)",
"losses_avg: average (per step) of the loss (avg[loss_this_step / total_generation_this_step])",
"wind_curtailed_opf: total (in energy) wind power curtailed by the OPF",
"wind_curtailed_losses: total (in energy) wind power curtailed by the loss",
"solar_curtailed_opf: total (in energy) solar power curtailed by the OPF",
"iter_num: number of iteration of the loss algorithm",
"generation_time: total time spent to generate these data (in seconds)",
"saving_time: total time spent to save the generated data (in seconds), this excludes the metadata saving time",
"amount_curtailed_for: sum of all the power that has been curtailed for the forecasts"
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{
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00:05
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{"load_seed": 383329927, "renew_seed": 3324115916, "gen_p_forecast_seed": 2811363264}
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{"length": 2018}
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