Information gap decision theory with risk aversion strategy for robust planning of hybrid photovoltaic/wind/battery storage system in distribution networks considering uncertainty

In this paper, robust planning of hybrid photovoltaic/wind/battery storage (PV/WT/Battery) system is performed in the distribution network to minimize power losses cost, purchasing power cost from the hybrid system as well as purchasing power cost from the upstream network considering uncertainties of network demand and renewable generation using information gap decision theory (IGDT) based on risk aversion strategy (RAS). The decision variables are considered as the optimal installation location and capacity of the hybrid system components in the network as well as the uncertainty radius of the uncertain parameters, which is determined using the flow direction algorithm (FDA), which is inspired by the movement of surface water flow to the pond outlet. The planning problem is implemented with deterministic and robust-based IGDT approaches. The proposed methodology is performed on the IEEE 33- and 69-bus distribution networks. The deterministic results indicate that the optimal hybrid PV/WT/Battery system planning in the networks significantly reduces system costs by injecting the optimal renewable power into the network and the battery power reserve management. The better capability of the FDA in deterministic planning is confirmed compared to the particle swarm optimization (PSO), crow search algorithm (CSA), and moth-flame optimizer (MFO) in achieving lower system cost. Moreover, in the IGDT robust approach, the maximum uncertainty radius of the renewable generation and network load is determined for the different uncertainties budget. The IGDT effectiveness is proved compared with deterministic and Monte Carlo simulation (MCS) methods. The total cost of the 33-bus network in deterministic, IGDT, and MCS is obtained at $ 17978.18, $ 20996.19, and $ 26178.02, respectively, and for the 69-bus network are achieved at $ 16846.26, $ 20215.39, and $ 20597.84, respectively. A comparison of the results showed that the MCS strongly depends on the defined scenarios, is very time-consuming, and is also not able to provide a level of cost assurance, the deterministic method is not able to determine the effect of uncertainties on system planning, but the IGDT can easily determine the cost of the system based on changes in uncertainty parameters. Also, planning based on the IGDT has resulted in the achievement of a robust hybrid system against forecasting errors caused by uncertainties.

Automated summary

In this paper, robust planning of a hybrid photovoltaic/wind/battery storage system in the distribution network is performed. The study aims to minimize power losses cost and purchasing power cost from both the hybrid system and upstream network, by considering uncertainties in network demand and renewable generation. The proposed methodology, based on information gap decision theory, uses the flow direction algorithm to determine the optimal installation location and capacity of the hybrid system components, as well as the uncertainty radius of the uncertain parameters. The results show that the planning approach significantly reduces system costs and provides a robust hybrid system against forecasting errors caused by uncertainties.