<![CDATA[Distribution feeders increasingly require load schedules that respond to time-varying prices while preserving operational limits. This paper presents a Hybrid Grey Wolf Optimizer (HGWO) for 24-hour distribution grid load scheduling underprice incentives. The method augments the leader-guided position update of the conventional Grey Wolf Optimizer with a momentum-based directional term and evaluates candidate schedules through a penalty-aware objective that combines energy price, incentive reward, and constraint violations. The model was implemented in MATLAB and assessed using hourly price, base-load, and incentive data obtained for a representative 11 kV feeder of the Port Harcourt Electricity Distribution Company. Thirty independent runs were conducted and compared with classical GWO. HGWO attained a best objective value of 38,910 ¢, approximately 2.3% below the GWO result, and reached a stable solution in 58 iterations compared with 82 iterations. Its standard deviation decreased from 760 ¢ to 412 ¢, indicating more consistent search performance. Sensitivity tests on penalty coefficient and population size further showed lower and flatter objective responses. The results demonstrate that HGWO can improve convergence speed, robustness, and price-responsive peak-load redistribution for day-ahead feeder scheduling.]]>
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