Load Factor Improvement of the Electricity Grid Considering Distributed Energy Resources Operation and Regulation of Peak Load.

• A MILP model is introduced to regulate peak demand. • Efficient coordination of DERs and load shifting to improve LF. • Optimal bulk scheduling of equipment used in the EN. • Mutual benefits for customers and the energy company. • The proposed model found the optimal solution to the problem. In recent decades, in urban centers, several services (such as health, food, security, connectivity, etc.) have become more dependent on electricity. With the population increase, the energy requirements of these services can lead the electricity network (EN) to a state of operational stress. In this scenario, distribution companies (DISCOs) need to develop efficient energy management strategies to avoid wasting electricity in its EN. The load factor (LF) of an EN is an indicator related to efficient electricity usage within a time horizon (e.g., day, month, year, etc.). LF improvement can be achieved through an efficient operational scheme that combines several strategies. Among them, peak load regulation in the demand profile of all the consumers, together with the operation of distributed energy resources (DERs), such as renewable energy sources (RESs) and capacitor banks (CBs), represents a promising alternative. In order to address this efficient scheme, this work proposes a mixed-integer linear programming (MILP) model that aims to increase the LF through the bulk scheduling of residential, commercial, and industrial electrical appliances during the day, considering a baseline demand and an hourly rate. At the same time, voltage fluctuations and technical losses are mitigated by the presence of DERs in the EN. Operational constraints related to the performance of EN, RESs, and CBs are considered. Uncertainties in the habitual demand profiles and solar irradiance during the day are represented through simulation algorithms. In order to evaluate the proposed model, a modified 14-node IEEE EN was used. The results corroborate the applicability of this proposed MILP model, reducing electricity waste and ensuring an efficient EN operation. [ABSTRACT FROM AUTHOR]