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With the deregulation of the power sector, distribution system planning is transforming from the traditional integrated decision mode to the multiple-player-based decentralized paradigm. However, this could potentially cause an adverse impact on the performance of the system due to interest conflict of market players during operations. To address such an issue, this paper develops a game-theoretic framework for active distribution network planning under the electricity market. The interplay between the distribution utility (DISCO) and distributed generation investors (DGO) is formulated as a noncooperative, two-person-based Stackelberg game in which the DISCO, as the leader of the game, makes expansion of the grid to achieve the least-cost operation, and DGOs, as followers, pursue for maximizing their profits from DG investment based on the condition of the network structure. The real-time network reconfiguration has been considered as a new active management option in this work, and the uncertainties associated with DG are also taken into account. To solve such game-theoretic model effectively, a heuristic-based algorithm is also proposed and combined with the dynamic optimal power flow analysis. The numerical results on a 33-bus distribution network verify the validity of the proposed methodology.

With the unbundling of power sector, the conflicting interests between different market entities (e.g. distribution company (DISCO) and DG owner (DGO)) can raise huge barriers for exploitation of renewable energies in an active distribution systems (ADS). To address this issue, a bilevel planning approach as a possible solution is presented in this study. The model considers the decision-making of DISCO in the upper-level, which seeks the minimization of overall payments. The optimization is constrained by the reaction of DGO in the lower-level which pursues maximum profits obtainable from DG investment. Multiple active network management (ANM) schemes, including voltage regulation, real-time network reconfiguration, and demand response, have been considered. The proposed problem is solved using an evolutionary algorithm along with the dynamic optimal power flow. Numerical results based on a 33-bus distribution system verify the effectiveness of the proposed method.Index Terms--Active distribution system, active network management, bilevel programming, deregulated market, renewable distributed generation I.

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