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This study presents an integrated methodology that considers renewable distributed generation (RDG) and demand responses (DR) as options for planning distribution systems in a transition towards low-carbon sustainability. It is assumed that demand responsiveness is enabled by real-time pricing (RTP), and the problem has been formulated as a dynamic two-stage model. It co-optimizes the allocation of renewables including wind and solar photovoltaic (PV), non-renewable DG units (gas turbines) and smart metering (SM) simultaneously with network reinforcement for minimizing the total economic and carbon-emission costs over planning horizons. The behavior compliance to RTP is described through a nodal-based DR model, in which the fading effect attended during the load recovery is highlighted. Besides, uncertainties associated with renewable energy generation and price-responsiveness of customers are also taken into account and represented by multiple probabilistic scenarios. The proposed methodology is implemented by employing an efficient hybrid algorithm and applied to a typical distribution test system. The results demonstrate the effectiveness in improving the efficiency of RDG operations and mitigating CO ₂ footprint of distribution systems, when compared with the conventional planning paradigms.
Zeng et al. (Fri,) studied this question.
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