Economic Dispatch of Diesel Generators Considering Photovoltaic Energy and Thermal Congestion in Distribution Networks in Isolated Areas

To address the current challenges, the proposed work makes the following contributions: • Evaluation of the Thermal Capacity of Distribution Networks: The model incorporates the effect of ambient temperature on the current-carrying capacity of power lines, enabling the identification of thermal congestion situations that may compromise the reliability and security of electricity supply in distribution networks, particularly in areas with extreme climatic conditions. • Analysis of the Climatic Impact on Photovoltaic Efficiency: The developed methodology allows for an in-depth analysis of how meteorological conditions, specifically ambient temperature, affect the efficiency of photovoltaic modules. It is shown that as the temperature of solar cells increases, their efficiency significantly decreases. The integration of distributed photovoltaic generation contributes to mitigating thermal congestion in distribution networks. • Proposal of an Efficient Economic Dispatch Model with Renewable Integration: The study presents a quadratic optimisation approach for the economic dispatch of diesel generators, which includes the integration of distributed photovoltaic generation. This integration explicitly considers thermal constraints both in generation and the network, thereby improving the operational efficiency of the system. • Application in Non-Interconnected Zones with a Focus on Sustainability: The methodology was applied in a non-interconnected zone (NIZ), demonstrating that the incorporation of distributed photovoltaic generation helps mitigate thermal congestion in distribution networks, reduces fossil fuel consumption, and lowers greenhouse gas (GHG) emissions, thus supporting the energy transition and climate change mitigation. The increase in extreme temperatures significantly affects electrical distribution networks, reducing both their transmission capacity and the efficiency of photovoltaic generation, thereby compromising operational security. In this context, the present study develops a computational model to evaluate the impact of ambient temperature on thermal congestion in power lines and on the efficiency of photovoltaic generation within the economic dispatch process of thermal generators. The model is formulated as a convex quadratic programming problem and implemented in Python using the IPOPT (Interior Point Optimizer) solver. It was applied to a case study in the city of Inírida, Colombia. The results indicate that the integration of distributed generation (DG) helps to mitigate thermal congestion in distribution networks by 6.91% and 12.10%, depending on the thermal conditions evaluated according to the IEEE 738 standard. Moreover, the efficiency of solar modules was found to decrease by 16.8% under elevated temperatures. Furthermore, operating costs were reduced by 36.7%, decreasing from USD 17,719.1 in the base scenario to USD 11,210.42 with the incorporation of distributed generation. Solar generation also contributed 7.9% of the total demand coverage, directly impacting the reduction of technical losses, which decreased from 553 kW to 362 kW. Similarly, a daily reduction in fuel consumption of 4,400.4 gallons and a reduction in CO₂ emissions of 43,641.4 kg were achieved. These findings demonstrate that the joint incorporation of climatic variables and renewable energy sources into the economic dispatch process enhances operational efficiency, improves the thermal resilience of the system, and promotes a more sustainable energy transition in isolated areas.