-The increasing penetration of renewable distributed generation (DG) sources in distribution networks can lead to violations of network constraints. Thus, significant network reinforcements may be required to ensure that DG output is not constrained. However, the uncertainty around the magnitude, location and timing of future DG capacity renders planners unable to take fully-informed decisions and integrate DG at a minimum cost. In this paper we propose a novel stochastic planning model that considers investment in conventional assets as well as smart grid assets such as demandside response, coordinated voltage control and soft open points (SOPs). The model also considers the possibility of active power generation curtailment of the DG units. A node-variable formulation has been adopted to relieve the substantial computational burden of the resulting mixed integer non-linear programming (MINLP) problem. A case study shows that smart technologies can possess significant strategic value due to their inherent flexibility in dealing with different system evolution trajectories. This latent benefit remains undetected under traditional deterministic planning approaches which may hinder the transition to the smart grid.

Sending bus of line. Receiving bus of line. Reactance of line (p.u.). Weighting of time period. Decision Variables Expected operational cost at Benders iteration. , Voltage angle at time , bus (rad). , Objective function of the operational subproblem corresponding to (,) for Benders iteration. Objective function of the operational subproblem corresponding to for Benders iteration. Δ Continuous variable representing ̃, , in the operational subproblem. Total investment cost corresponding to. Total operational cost corresponding to. σ Continuous variable for consumer participation in DSR at bus after the deployment of a DSR pilot scheme.

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Abstract-We propose a novel stochastic planning model that considers investment in conventional assets as well as in Soft Open Points, as a means of treating voltage and thermal constraints caused by the increased penetration of renewable distributed generation (DG) sources. Soft Open Points are shown to hold significant option value under uncertainty; however, their multiple value streams remain undetected under traditional deterministic planning approaches, potentially undervaluing this technology and leading to a higher risk of stranded assets.

-The increasing penetration of renewable distributed generation (DG) sources in distribution networks can lead to violations of network constraints. Thus, significant network reinforcements may be required to ensure that DG output is not constrained. However, the uncertainty around the magnitude, location and timing of future DG capacity renders planners unable to take fully-informed decisions and integrate DG at a minimum cost. In this paper we propose a novel stochastic planning model that considers investment in conventional assets as well as smart grid assets such as demandside response, coordinated voltage control and soft open points (SOPs). The model also considers the possibility of active power generation curtailment of the DG units. A node-variable formulation has been adopted to relieve the substantial computational burden of the resulting mixed integer non-linear programming (MINLP) problem. A case study shows that smart technologies can possess significant strategic value due to their inherent flexibility in dealing with different system evolution trajectories. This latent benefit remains undetected under traditional deterministic planning approaches which may hinder the transition to the smart grid.