# Optimal design and operation of Photovoltage distributed generators and shunt compensators for the Vietnam alternative current distribution network to reduce annual energy loss

## TL;DR

This paper compares two new optimization algorithms to reduce energy loss in Vietnam's power grid and standard networks.

## Contribution

The study introduces and compares two novel meta-heuristic algorithms for optimizing power grid components in real and standard networks.

## Key findings

- AOO outperforms FGO in reducing total active power loss across multiple scenarios.
- AOO achieves significant TAPL improvements in IEEE and Vietnam networks.
- Operational Scenario 4 with PVDGs and SCBs minimizes energy loss in most quarters.

## Abstract

This study presents the application of two novel meta-heuristic algorithms, including the Fungal Growth Optimizer (FGO) and Animated Oat Optimization Algorithm (AOO), to optimize the placement of DGs and SCBs for power loss reduction in three alternative current distribution networks (ACDNs), including a practical ACDN with 55 nodes in Vietnam, besides the two IEEE standard ACDNs. In the study, placement of DGs and SCBs on the three grids is conducted in two phases, including the designing phase and the operational phase. In the designing phase, DGs and SCBs were optimized in their placement on the grids by the two algorithms in various scenarios with different DG configurations. The results achieved through scenarios indicate that AOO completely outperforms FGO in terms of the optimal total active power loss values (TAPL) and the stability of the outputs. Particularly, in the two scenarios conducted on the IEEE 69-node, the TAPL achieved by AOO is better than FGO, 3.65% for the first scenario and 72.28% for the second scenario. In the other two scenarios conducted on the IEEE 85-node, AOO still proves its high effectiveness over FGO by reaching the better TAPL at 6.02% in Scenario 1 and 44.88% in Scenario 2. Lastly, AOO is continuously superior to FGO in the four scenarios in the Vietnam ACDN, with 55-node by 1.04% in Scenario 1, 19.52% in Scenario 2, 7.07% in Scenario 3, and 69.60% in Scenario 4. Next in the operational phase, AOO is reapplied to optimize the power output of PVDGs and SCBs within an average day of the first month in the four quarters of the year, with load demand variation and dynamic supplied power from PVDGs in four scenarios with different settings of PVDGs and SCBs. The results clearly reveal that the operational Scenario 4 with PVDGs is configured to supply both active and reactive power to the grid, along with SCBs, which offer the best value of energy loss in the three quarters, except for the third one, where the operational Scenario 2 is the most suited for energy loss.