The frequency diversion in hybrid power systems is a major challenge due to the unpredictable power generation of renewable energies. An automatic generation controller (AGC) system is utilised in a hybrid power system to correct the frequency when the power generation of renewable energies and consumers’ load demand are changing rapidly. While a neural network (NN) model based on a back-propagation (BP) training algorithm is commonly used to design AGCs, it requires a complicated training methodology and a longer processing time. In this paper, a bacterial foraging algorithm (BF) was employed to enhance the learning of the NN model for AGCs based on adequately identifying the initial weights of the model. Hence, the training error of the NN model was addressed quickly when it was compared with the traditional NN model, resulting in an accurate signal prediction. To assess the proposed AGC, a power system with a photovoltaic (PV) generation test model was designed using MATLAB/Simulink. The outcomes of this research demonstrate that the AGC of the BF-NN-based model was effective in correcting the frequency of the hybrid power system and minimising its overshoot under various conditions. The BP-NN was compared to a PID, showing that the former achieved the lowest standard transit time of 5.20 s under the mismatching power conditions of load disturbance and PV power generation fluctuation.

The Iraqi power sector is at a critical stage that requires urgent reforms. Concerns regarding the ability of the system to provide steady power and its operational inefficiencies, in general, have been expressed by the industry and academia. Currently, the power industry is experiencing one of the highest demand growth in the world, and given that it is capital intensive, it takes up a large share of Iraq’s government capital investment program. More so, there is a huge increase in the financial burden of the Iraqi electricity supply industry due to the high subsidies required for the coverage of the recurrent expenditure. This subsidy is regarded as one of the highest in the world, given the extremely low traffic which does not cover up to 20% of the periodic expenditure. Apart from the huge subsidy in electricity tariff, another major and indirect socioeconomic subsidy is the fact that the industry is over-staffed with over 50,000 employees which under normal circumstances should not be more than 15,000. The estimated annual cost of the aforementioned inefficiencies and insufficient power supply is about $3 to 4 billion. In 2013, about 70% of the generated electricity was lost, and this loss is in three areas, including commercial, technical, and administrative losses. Therefore, there is a need for massive reforms that are targeted at addressing the entire issue. This can be achieved through the engagement of the private sector, higher competition, and the introduction of novel regulatory and legislative frameworks. In addition to that, the available sources of energy in Iraq need to be optimized alongside gas usage related to oil extraction, while solar energy in Iraq is explored and the solar hybridization of the current power stations.