Improve Short Term Load Forecasting Using Artificial Neural Network by Incorporating Solar PV generation
| Author(s) | : | Pallavi M. Rathod |
| Institution | : | M.E.(Electrical) Lecturer Sir BPI Bhavnagar Gujarat |
| Published In | : | Vol. 7, Issue 6 — June 2020 |
| Page No. | : | 116-119 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Incentive, eco-friendly and cost benefit of photovoltaic are resulting in large amount of roof top solar PVsystems being installed in Gujarat. The effect of high penetration of solar PV is that the short term load forecasting resultare becoming less reliable. This paper presents the incorporation of photovoltaic generation in short term loadforecasting carried out on 11kv ‘shivaji circle’ feeder of 66kv sardarnagar GETCO substation, Bhavnagar, Gujarat.Artificial Neural Network is used. Data for the month of 15th February to 15th June is taken for network training, testingand forecasting. Matlab is used. This gives load forecast one hour ahead of time.
Pallavi M. Rathod, “Improve Short Term Load Forecasting Using Artificial Neural Network by Incorporating Solar PV generation”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 7, Issue 6, pp. 116-119, June 2020.
