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Research Article

A Hybrid Improved Whale Optimization Algorithm with Support Vector Machine for Short-Term Photovoltaic Power Prediction

, , ORCID Icon, , &
Article: 2014187 | Received 11 May 2021, Accepted 30 Nov 2021, Published online: 07 Jan 2022

Figures & data

Table 1. Test functions

Table 2. Test convergence values

Figure 1. Test convergence results using various test functions.

Figure 1. Test convergence results using various test functions.

Figure 2. Flow chart of photovoltaic power output predicted by IMWOASVM model.

Figure 2. Flow chart of photovoltaic power output predicted by IMWOASVM model.

Figure 3. The relationship between meteorological elements and PV output power in sunny weather.

Figure 3. The relationship between meteorological elements and PV output power in sunny weather.

Figure 4. The relationship between meteorological elements and PV output power in cloudy weather.

Figure 4. The relationship between meteorological elements and PV output power in cloudy weather.

Table 3. Definition of correlation degree

Table 4. The value of ρ in sunny and cloudy

Figure 5. PV output power forecast in sunny weather.

Figure 5. PV output power forecast in sunny weather.

Figure 6. Prediction relative error in sunny weather.

Figure 6. Prediction relative error in sunny weather.

Figure 7. Output power forecast in cloudy weather.

Figure 7. Output power forecast in cloudy weather.

Figure 8. Prediction relative error of output power in cloudy weather.

Figure 8. Prediction relative error of output power in cloudy weather.

Table 5. Evaluation of output power forecast

Table A1. PV output power forecast data in sunny weather

Table A2. PV output power forecast error data in sunny weather

Table A3. PV output power forecast data in cloudy weather

Table A4. PV output power forecast error data in cloudy weather