Day Ahead Thermal-photovoltaic Economic Dispatch Considering Uncertainty of Photovoltaic Power Generation

doi:10.16182/j.issn1004731x.joss.21-0336

Abstract

Abstract:

Aiming at the uncertainty and randomness of photovoltaic power generation affected by weather factors, a mathematical model of day ahead thermal-photovoltaic economic dispatch considering seasonal weather factors is established. The mathematical model takes the operation cost of thermal power units, the cost of photovoltaic power generation, the cost of spinning reserve and the forecast error cost of photovoltaic power generation affected by weather factors as the economic objective function, and the sulfur dioxide emission of thermal power units as the environmental objective function. In order to improve the accuracy of photovoltaic output prediction, the long short term memory neural network with seasonal weather factors is used to predict the photovoltaic power generation. The model is solved by Cplex, and the effectiveness and feasibility of the proposed model are proved by case simulation.

Key words: economic dispatch, photovoltaic power generation, prediction error cost, long short term memory neural network

CLC Number:

Xinghua Liu, Chen Geng, Shenghan Xie, Jiaqiang Tian, Hui Cao. Day Ahead Thermal-photovoltaic Economic Dispatch Considering Uncertainty of Photovoltaic Power Generation[J]. Journal of System Simulation, 2022, 34(8): 1874-1884.

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时间/h	负荷/MW	时间/h	负荷/MW	时间/h	负荷/MW
1	400	9	520	17	490
2	420	10	555	18	520
3	430	11	570	19	530
4	440	12	585	20	540
5	450	13	520	21	560
6	480	14	500	22	540
7	490	15	490	23	500
8	500	16	580	24	405

季节	晴天	阴天	雨天
冬季	0.076	0.381	0.543
春季	0.506	0.325	0.169
夏季	0.541	0.320	0.139
秋季	0.065	0.607	0.328

指标	考虑季节天气因素		不考虑季节天气因素
指标	LSTM	BP	LSTM	BP
RMES	17.250 3	21.508 4	20.286 3	28.697 5
MAE	0.101 9	0.192 1	0.183 6	0.274 4

场景	案例1调度结果	案例2调度结果
1	175 741	175 207
2	184 283	183 719
3	190 547	185 751
4	175 922	182 076
5	189 118	187 374
6	184 227	182 180
7	186 717	181 451
8	173 242	169 967
9	185 728	187 051
10	183 679	170 365

场景	案例2	案例3
1	315 421	335 603
2	321 266	337 204
3	323 424	335 442
4	318 108	335 948
5	323 862	335 526
6	320 397	324 865
7	318 940	334 052
8	310 452	335 446
9	325 452	334 981
10	310 896	334 747