Optimization study of a double-layer pumped storage model based on a step penalty mechanism for carbon emissions and new energy abandonment

doi:10.19799/j.cnki.2095-4239.2024.0043

Abstract

Abstract:

With the implementation of the "double carbon" goal, increasing integration of new energy sources within grids, planned decommissioning of thermal power plants, and accelerated construction of pumped storage solutions as flexible regulating resources, rational planning has emerged as the most crucial factor ensuring the stability of power systems and guaranteeing the sustainable conversion of multiple energy forms. This study investigates optimization methods for pumped storage capacity planning and dispatching, considering scenarios of new energy utilization. Furthermore, it constructs a two-layer optimization model for pumped storage considering the minimization of the whole-life cycle costs, carbon emissions, and abandonment penalty costs of each power source as its upper-layer optimization objectives and the minimization of the carbon emissions and wind power fluctuations of each power source as its lower-layer optimization objectives. Subsequently, the study compares the star crow, genetic, and gray wolf algorithms, focusing on their advantages and disadvantages. By adaptively optimizing the parameters of the star crow algorithm, the study identifies the algorithm with superior optimization performance and speed and integrates it with CPLEX to solve the two-layer optimization model. Additionally, the upper and lower optimization objectives of the model are established by introducing a step penalty mechanism for carbon emissions and new energy abandonment. Experimental results reveal that regional power grids must accelerate the construction of pumped storage facilities by approximately 74.21% and reasonably decommission thermal power by approximately 40.79%. Remarkably, the developed model effectively reduces the comprehensive system cost by approximately 5.80%, decreases the abandonment rate of wind and solar power by approximately 20.43%, lowers carbon emissions by approximately 25.96%, and smooths out wind and solar power fluctuations by approximately 1.18%. These outcomes validate the effectiveness of the model and highlight the importance of rational planning, offering valuable references for the medium- and long-term planning of power systems.

Key words: high percentage of new energy, pumped storage, step penalty costs, two-tier optimization

CLC Number:

TM 74

Shihao HOU, Bo ZHAO, Li ZHANG. Optimization study of a double-layer pumped storage model based on a step penalty mechanism for carbon emissions and new energy abandonment[J]. Energy Storage Science and Technology, 2024, 13(7): 2414-2424.

Figures/Tables 11

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测试函数	指标	NOA	GWO	GA	ANOA
F1	最优函数值	300	300	512.4684	300
F1	最小运行时间	1.8357	3.0608	3.4058	1.3360

F2	最优函数值	400.3851	400.9161	408.3825	400.3851
F2	最小运行时间	1.3203	1.3242	3.0977	1.3011

F6	最优函数值	1.8003e+03	3.4049e+03	1.8740e+03	1.8078e+03
F6	最小运行时间	1.4040	3.1603	3.5852	1.3687

F9	最优函数值	2.5293e+3	2.5449e+3	2.5293e+3	2.5293e+3
F9	最小运行时间	1.8751	3.3305	3.8453	1.6004

机组	配置成本/(万元/MW)	运维成本/(万元/MWh)	生命周期/年	折算后日配置成本/(万元/MW)
抽水蓄能	600	0.03	40	0.041
风电	715	0.06	20	0.098
光伏	350	0.06	30	0.032
水电	300	0.01	30	0.141
火电	330	0.03	30	0.030

场景	综合成本/万元	弃风光惩罚成本/万元	碳排放惩罚成本/万元	碳排放量/吨	弃风弃光量/万千瓦时
初始场景	6619.70	398.84	111.33	21517.40	6721.23
仅采用碳排放阶梯惩罚场景	6548.77	386.74	107.95	20954.61	6586.73
仅采用新能源弃电阶梯惩罚场景	6463.96	425.41	105.19	17532.01	6393.44
采用新能源弃电与碳排放阶梯惩罚场景	6398.74	423.34	101.86	16975.97	6370.44

场景	综合成本/万元	弃风光惩罚成本/万元	碳排放惩罚成本/万元	碳排放量/吨	弃风弃光量/万千瓦时	火电机组容量/万千瓦	抽水蓄能容量/ 万千瓦
初始场景	6619.70	398.84	111.33	21517.40	6721.23	7712	861
NOA	6239.98	320.89	95.59	15931.36	5348.24	4706	1500
GWO	6278.20	320.89	95.59	15931.36	5348.24	5980	1500
GA	6359.06	322.18	95.72	15953.27	5369.72	8617	1490
ANOA	6235.78	320.89	95.59	15931.36	5348.24	4566	1500

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