Reactive power outputs of DGs are used along with capacitor banks to regulate distribution network voltage. However, reactive power capability of a DG is limited by the inverter ratings and real power outputs of the DG. In order to achieve optimal power flow, minimize power losses, and minimize switching of capacitor banks, a day-ahead coordinated dispatch method of reactive power is proposed. Forecast errors of DG real power in every period are used to estimate the probability distribution of DGs reactive power capacity. Considering different output characteristics and constraints of reactive power sources, a dynamic preliminary-coarse-fine adjustment method is designed to optimize DG and shunt compensator outputs, decrease the switching cost, and reduce loss. The preliminary optimization obtains initial values, and multiple iterations between the coarse and fine optimizations are used to achieve a coordinated result. Simulations studies are performed to verify the proposed method.

More and more distributed energy resources (DERs) are being integrated into the distribution networks raising the new concerns of secure and economic operations. Some traditional distribution networks are upgraded to active distribution networks (ADNs) which can communicate with and control the DERs. A microgrid connected to an ADN can be coordinated with the ADN. In this paper, a two-stage hierarchical congestion management mechanism is proposed for an ADN connected with multi-type DERs and microgrids. At the first stage, a hierarchical optimization model is built considering the dispatch of direct control resources (DCRs) and microgrids. An analytical target cascading (ATC) method is employed to optimize the microgrid autonomy model and the ADN optimization model simultaneously. A second stage optimization is designed to deal with the case when the control of DCRs and microgrids is not enough to completely eliminate the congestion. A congestion management model calling for the ancillary services provided by DERs is established, with an objective of minimizing the operational cost of distribution system operator (DSO). Case studies are carried out on modified IEEE 33 and PG&E 69 bus systems. The simulation results show that the proposed method can balance the interests of different stakeholders and eliminate the network congestion efficiently. Wireless communication ... Flexible load control teminal Wireless communication DG and distributed energy storage control terminal Wireless communication ...

Abstract:With large-scale integration of distributed energy resources (DERs), distribution networks have turned into active distribution networks (ADNs). However, management risks and obstacles are caused by this in due to renewable energy generation (REG) forecasting errors. In this paper, a day-ahead active power scheduling method considering REG forecast errors is proposed to eliminate the risks, minimize the costs of distribution companies and achieve optimal power flow. A hierarchical coordination optimization model based on chance constrained programming is established to realize day-ahead optimal scheduling of active power in ADNs coordinated with network reconfiguration, achieving an optimal solution of network topologies and DER outputs. The hierarchical method includes three levels: the first level provides initial values, and multiple iterations between the second and third level are used to solve the multi-period mixed integer nonlinear optimization problem. The randomness due to REG forecast errors is tackled with chance constrained programming in the scheduling procedure. The hybrid particle swarm optimization algorithm is employed to solve the proposed model. Simulation results verify the validity of the proposed method with an improved 33 nodes distribution network.

With the integration of more and more renewable energy generations (REGs), the structure of traditional distribution networks is hard to accommodate the volatile power injections of REGs. As a new power electronic device, soft open point (SOP) can be installed to control both active and reactive power flow among active distribution networks (ADNs). This paper presents a comprehensive optimization method for allocating SOPs within an ADN with high penetration of REGs. In order to find proper SOP candidate locations, a selection strategy based on two technical indices is proposed. To mitigate the risk of voltage violation caused by REG forecast errors and improve the adaptiveness of allocation results, a two-stage robust optimization model for SOP allocation is formulated to minimize the total cost of SOP investment and network operation. The proposed model is converted into a mixed-integer second-order cone programming (MISCOP) problem, which is then decoupled into a master problem of planning and a subproblem of operation and solved by column and constraint generation (CCG) algorithm. Simulation results show that the proposed method can effectively find the optimal SOP allocation schemes. Comparisons with different mathematical formulation and solution methods show the advantages of the proposed method.

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