Development of PV hosting-capacity prediction method based on Markov Chain for high PV penetration with utility-scale battery storage on low-voltage grid

Figures & data

Figure 1. PV penetration model based on (a) Monte Carlo (previous studies) and (b) Markov chain (proposed study).

Figure 2. IEEE 123-bus test feeder.

Table 1. States of Markov chain constructed.

State name	Description
State 1	PV sizes $\le$ 2.5 kW
State 2	2.5 kW $<$ PV sizes $\le$ 5.0 kW
State 3	5.0 kW $<$ PV sizes $\le$ 7.5 kW
State 4	7.5 kW $<$ PV sizes $\le$ 10 kW

Figure 3. Algorithm for the proposed method.

Figure 4. PV hosting capacities for all Markov chain simulations.

Figure 5. The time-series impact of solar irradiance and load demand during August on maximum voltages.

Figure 6. Impact of the increase of PV penetration on maximum voltage.

Table 2. PV hosting capacity results.

Penetration	PV hosting capacity (kW)
Customer-scale PV	123.58
Customer-scale PV with utility-scale battery	3676.4

Figure 7. MAE comparison of Monte Carlo and Markov chain for PV hosting capacity prediction.

Figure 8. RMSE comparison of Monte Carlo and Markov chain for PV hosting capacity prediction.