Adaptive Active Power Control for Aligning Photovoltaic Output with Consumer Demand in Rural Feeders

The increasing global integration of photovoltaic (PV) systems, vital for sustainable development, presents significant operational challenges in rural distribution networks. These feeders, particularly those in Kenya with high resistance-to-reactance (R/X) ratios, are prone to reverse power flow (RPF) and voltage instability, with generic smart inverter controls often proving ineffective due to insufficient voltage rise. This paper addresses this critical gap by developing and validating an adaptive, coordinated smart inverter control algorithm. Employing both Volt-VAR for reactive power support and Active Power Curtailment (APC), the strategy dynamically aligns PV output with real-time local load demand using quasi-static time-series simulations in OpenDSS for a representative Murang'a 11kV rural feeder in Kenya. This grid compliance was achieved at a quantified cost of approximately 1,500 kWh of curtailed renewable energy per day during the dry season. Critically, a comparative seasonal analysis was performed by repeating the simulations under rainy season (long rains) conditions, characterized by significantly reduced and variable solar irradiance. The rainy season results confirmed the absence of reverse power flow due to the naturally lower PV generation, which remained below local load demand throughout the day. This seasonal comparison validates that RPF is predominantly a dry-season phenomenon in this context and that the proposed adaptive control strategy is both critically necessary during high-irradiance periods and benignly non-intrusive during low-irradiance seasons. The study validates a practical methodology for high-penetration PV integration in challenging rural grids, emphasizing the necessity of feeder-specific, seasonally-informed control strategies to balance grid safety with renewable energy yield.