During the deregulation of retail power market, multiple stakeholders are gradually involved in distribution network to invest distributed resources and participate in power transactions, bringing great uncertainty to grid operation. This paper proposes a novel robust coordination expansion planning method that considers non-network solutions in a deregulated retail market, including the closed-loop demand response and other controllable strategies. A double-nested game model is constructed to simulate the bi-directional interaction between distribution system operator and stakeholders. Given that this model cannot be solved directly, a tri-layer decomposition algorithm is presented to enable a distributed optimization of the coupled problem. Furthermore, the case study is implemented on an IEEE 33-bus distribution system and an IEEE 123-bus distribution system, which demonstrates the efficiency and practicability of the proposed method and highlights its merits on enhancing flexibility and postponing unnecessary investments.

The burgeoning integration of distributed energy resources (DER) poses new challenges for the economic and safe operation of the electricity system. The current distribution-side policy is largely based on mandatory regulations and incentives, rather than the design of a competitive market mechanism to arouse DERs to freely compete in the retail market. To address this issue, we proposed a transactive retail market mechanism to attract the active participation of profit-driven DER retailers in a deregulated way. Considering the limited competitive property of the retail market, a bi-level DSO-dominated framework is constructed to simulate the virtual game between distribution system operator (DSO) and DER retailers. Specifically, the flexible interval pricing of retailers is modeled as a series of binary revenue constraints to influence the DSO's centralized economic dispatch decisions, where the time-varying distribution locational marginal price is adopted to settle energy activities at different locations over the time horizon. Due to the uncertain power flow path during the coordinated decision-making process, we proposed a general undirected second-order cone-based AC radial power flow model and provided sufficient conditions to ensure its exactness. Also, we applied a series of approximation and relaxation techniques to transform the bi-level mixed-integer quadratic framework with highly discrete induced domains into a solvable mixed-integer semidefinite programming problem. It is demonstrated in the case study that the proposed mechanism not only improves market efficiency but also eliminates market power and the resulting market failures.

Sizing and configuring community-shared energy storage according to the actual demand of community users is important for the development of user-side energy storage. To solve this problem, this paper first proposes a community energy storage cooperative sharing mode containing multiple transaction types and then establishes a sizing and configuration model of community-shared energy storage based on a cooperative game among community users and energy storage operators, in which the loss caused by the capacity decay of energy storage is quantified by a dynamic power loss cost factor. To improve the solving efficiency, a distributed and cooperating solving method based on ADMM is used to solve the sizing and configuration model. On this basis, the bilateral Shapley method is used to allocate the total annual cost according to the marginal expected cost brought by each user. Compared with existing strategies, this paper calculates the economic benefits of community-shared energy storage based on several typical days of each year and quantifies the capacity decay of energy storage by a dynamic power loss cost factor which increases year by year to be closer to the real situation. Finally, the simulation verifies that the model proposed in this paper can be used for the sizing and configuration of community-shared energy storage. Compared with the original annual cost, the total annual cost of the community is reduced by 3.92%, and the annual operation cost of the community which equals annual electricity purchasing cost minus annual electricity selling income plus annual power loss cost is reduced by 25.6%.

Developing a coordinated optimal dispatch (COD) strategy for distribution systems (DS) and accessed microgrids (MGs) is one of the solutions to enhance the flexible operation of power systems. Under the premise of the operational autonomy of MGs, existing COD studies can be classified into iterative methods that allow for independent decision-making in DS and MGs, and non-iterative methods based on the operational region (OR) modeling of MGs. However, the iterative methods hardly guarantee computational convergence and efficiency, while non-iterative methods struggle to solve equivalent projections with high-dimensional ORs. To this end, a fast approximation progressive vertex enumerations (FAPVE) algorithm-based non-iterative COD approach is proposed, where the high-dimensional OR considering time coupling characteristics can be formed effectively. First, a reliable outer normal vectors calculation method along with a vertices and normal vectors count limiting mechanism are introduced to enhance the computational efficiency and stability of the FAPVE algorithm. Second, a time-decoupling method for day-ahead MGs’ OR based on initial MG decisions is presented to ensure the applicability of the proposed algorithm to day-ahead COD problem. Statistical analysis verifies the computational efficiency and accuracy of the FAPVE algorithm, and demonstrates the effectiveness of the proposed time-decoupling method based on non-iterative framework.