The Optics Inspired Optimization (OIO) algorithm is a new metaheuristic optimization method. In this paper, the OIO algorithm was proposed for automatic production control parameters in electrical power systems. The performance of the proposed algorithm was realized on two power systems that have different structures. The first structure is a two-area interconnected thermal reheat power system and the other one is a two-area interconnected multi-unit hydro-thermal power system. The results obtained with the proposed algorithm were compared with an artificial bee colony and particle swarm optimization, initial values are randomly defined that are commonly used in literature. The results were examined using four different cost functions based on area control error. Considering the obtained results, the proposed algorithm reached to the global minimum value with less number of iterations and is more suitable for online optimization. According to the results obtained with this novel method, it has a better performance for maximum overshoot and settling time values when the test systems are implemented.

The use of renewable energy sources (RESs) is increasing every day to meet increasing energy demands and reduce dependence on fossil fuels. When designing hybrid renewable energy systems (HRESs), it is necessary to examine their technical, economic, and environmental feasibility. In this study, a new strategy is proposed using the HOMER Matlab Link (ML) connection for an HRES model consisting of a photovoltaic (PV) system, a wind turbine (WT), a biogas generator (BGG), and a battery storage system (BSS) designed to meet the electrical energy needs of Doğanevler village located in the rural area of Bingöl province. The data obtained as a result of the proposed strategy (PS) are compared with HOMER’s loop charging (CC) and load following (LF) optimization results. According to the PS, the optimum capacity values for the HRES components are 10 kW for WT, 10 kW for PV, 8 kW for BGG, 12 kWh for BSS, and 12 kW for the converter. According to the optimum design, 16,205 kWh of the annual energy produced was generated by PV systems, 22,927 kWh by WTs, and 22,817 kWh by BGGs. This strategy’s NPC and LCOE (Levelized Cost of Energy) values are calculated as USD 130,673.91 and USD 0.207/kWh, respectively. For the CC dispatch strategy, the NPC and LCOE values are calculated as USD 141,892.28 and USD 0.240/kWh, while for the LF dispatch strategy, these values are USD 152,456.89 and USD 0.257/kWh. The CO₂ emission value for the system using a BGG was calculated as 480 kg/year, while for the system using a DG, this value increased approximately 57 times and was calculated to be 27,709 kg/year. The results show that the PS is more economical than the other two strategies. The PS provides energy security, reduces costs, and increases environmental sustainability. Finally, a sensitivity analysis was conducted based on the availability of renewable resources, fuel cost, and inflation parameters, and the results were analyzed.

Today, many factors, especially the increasing world population and developing technology, increase the energy needs of people and societies day by day. The fact that fossil resources are both in danger of depletion and have negative environmental impacts has directed countries to new resources. The study focuses on the effective use of renewable energy sources (RES) and the evaluation of waste to meet the electricity and heat energy needs of Yiğit Harman Village, located in the Solhan district of Bingöl Province. For this purpose, a renewable-energy-based combined heat and power system (CHP) was designed using HOMER Pro software (version 3.14.2, Homer Energy LLC, Boulder, CO, USA). Solar, wind, biomass, and hydrogen energy sources were used, considering the resources of the region. Using the designed model, the entire electricity energy requirement and half of the heat energy were completely met by the region’s available RESs. In addition to the technical analysis, economic and environmental analyses were also conducted, and LCOE, NPC, and CO₂ emission values were obtained as 0.271 USD/kWh, USD 739,772, and 37,958 kg/yr, respectively. These results indicate that with an investment of approximately USD 7000 per household, the electrical and thermal energy needs for 25 years can be met.

Solar energy, which is an inexhaustible, clean and easily accessible energy source, can be converted into electrical energy with the help of photovoltaic (PV) panels. Environmental factors such as dust and dirt cause pollution of PV panels and decrease the efficiency of energy conversion. One of the methods used to reduce the negative effect of dirt on panel efficiency is to coat the surface of the panels with photocatalytic materials. Oxygen and nanoparticles are formed on photocatalytic surfaces with the help of ultraviolet rays in sunlight. These particles form a chemical reaction between the coating and the surface, breaking down and destroying the dirt on the surface. In this study, the effect of titanium dioxide (TiO2) as a photocatalytic material on the efficiency of solar panels was investigated. Experimental studies were carried out in Bingöl city using two 285 W polycrystalline solar panels. One of the panel surfaces is coated with TiO2and no treatment has been applied to the surface of the other panel. When the measured data were analyzed, it was seen that while the powers of the two panels were almost the same at the beginning, with the contamination of the panels, the power obtained from theTiO2coated panel was up to 19% higher. In addition, it was observed that the excess power produced as a result of cleaning the PV panels after rainy days decreased again.