Optimal Allocation of PV-Based Distributed Generations and Scheduling of Battery Storage in Grid-Connected Micro-grid Using Bi-level Optimisation

被引:0
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作者
Das S.K. [1 ]
Sarkar S. [1 ]
Bhattacharya A. [1 ]
机构
[1] Department of Electrical Engineering, National Institute of Technology, West Bengal, Durgapur
关键词
2m-Point Estimation Method; Battery allocation; Battery scheduling; Load variation; Photo-voltaic based distributed generation; Solar radiation uncertainty;
D O I
10.1007/s42979-023-02003-9
中图分类号
学科分类号
摘要
The presence of photovoltaic-based distributed generation in distribution networks brings a concern regarding intermittency of power generation. This concern can be mitigated through energy storage systems, incorporated into the network allowing instantaneous filling up of the gap between the generation and load demand. These energy storages are scheduled in such a way that they get charged during excess generation and discharged during the low generation periods. In this paper, a two-layer optimisation of the grid-connected active distribution network is performed in which the optimal location and sizes of the ‘solar generation and battery storage’ are optimised in the outer layer and accordingly the optimal battery scheduling considering the variations of solar radiation and load demand is performed in the inner layer. The optimisation is performed based on multiple objectives of energy loss reduction, voltage stability improvement and cost reduction of battery and local generation. The intermittency of the photovoltaic-based generation is considered using a probability-based 2m-Point Estimation Method. The above mentioned problem is solved using Honey Badger Optimisation due to its better exploration and exploitation ability to find better quality results. Moreover, this technique is not applied in the field of power system earlier. The proposed methodology has been applied on a radial network and has shown better voltage stability along with reduced energy losses, total costs of power purchase and total investments in solar based distributed generations and battery storage systems. Performance of the optimisation algorithm is also compared with few other well established optimisation algorithm. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.
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