Multi-objective Demand Side Management in Distribution Networks with Renewable Generation

The integration of Low Carbon Technologies (LCTs) and renewable energy sources has introduced significant technical challenges in distribution networks (DNs), including voltage rise, reverse power flows, and increased losses. Demand-side management (DSM) offers a viable solution to address these issues by optimizing load profiles, reducing peak loads, and mitigating the impacts of renewable energy intermittency. This paper proposes a novel DSM framework designed to enhance distribution network performance while maintaining steady-state and dynamic stability. The framework solves a multi-objective optimization problem using optimal power flow over a 24-hour horizon, incorporating constraints such as load payback, supply-demand balance, voltage limits, and line capacities. A composite load model, combining static and dynamic components, captures the voltage-dependent behaviour of loads. Additionally, probabilistic models for renewable energy generation are integrated to represent wind and solar variability. The study addresses the limitations of existing DSM strategies by incorporating internal DN constraints and monitoring time-varying performance indicators such as voltage stability and network losses. It further explores the coordinated optimization of DSM with renewable generation, leveraging advanced algorithms for load forecasting and scheduling. Case studies on a benchmark network demonstrate significant improvements in grid stability, operational efficiency, and energy flexibility, providing insights into future-ready energy management systems.