| Title |
Smart Grid Project Benefit Evaluation Based on a Hybrid Intelligent Model |
| ID_Doc |
41578 |
| Authors |
Liang, Y; Fan, YY; Peng, YF; An, HG |
| Title |
Smart Grid Project Benefit Evaluation Based on a Hybrid Intelligent Model |
| Year |
2022 |
| Published |
Sustainability, 14, 17 |
| DOI |
10.3390/su141710991 |
| Abstract |
With the accelerated development of smart cities, the construction and development of smart grids have an increasing impact on the safe and stable operation of power systems. The benefit evaluation of smart grids can find out the problems of smart grids more comprehensively, which is of great practical significance for the further development of smart cities. In order to ensure accuracy and real-time evaluation, this paper proposes a new hybrid intelligent evaluation model using an improved technique for order preference by similarity to an ideal solution (TOPSIS) and long-short-term memory (LSTM) optimized by a modified sparrow search algorithm (MSSA). First, a set of smart grid benefit evaluation index systems is established in the context of considering smart city development. Then, aiming at the reverse order problem existing in TOPSIS, an improved evaluation model with entropy weight and modified TOPSIS is established. Finally, an intelligent evaluation model based on LSTM with MSSA optimization is designed. The example analysis verifies the accuracy of the model proposed, points out the important factors affecting the benefits of smart grids, and provides a new idea to achieve effective evaluation and rapid prediction, which can help to improve the benefit level of smart grids. |
| Author Keywords |
smart city; smart grid; benefit evaluation; improved TOPSIS; MSSA; LSTM |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000851778800001 |
| WoS Category |
Green & Sustainable Science & Technology; Environmental Sciences; Environmental Studies |
| Research Area |
Science & Technology - Other Topics; Environmental Sciences & Ecology |
| PDF |
https://www.mdpi.com/2071-1050/14/17/10991/pdf?version=1662447699
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