The access of large‐scale distributed generation (DG) easily leads to energy imbalance in distribution network. To deal with this issue, this paper proposes an energy optimal schedule method for distribution network considering the participation of source‐load‐storage aggregation groups (SAGs). Firstly, the system model consisting of distribution network layer and SAGs layer is established, and the schedule objectives and constraints of each layer are also given. Secondly, considering the fluctuation on the load side, a forecasting method based on Adaboost integrated convolutional neural networks and bidirectional long‐short term memory is proposed. Then, the improved sparrow search algorithm (ISSA) is proposed by using the tent map and Levy flight on the original sparrow search algorithm. At the same time, by introducing Pareto dominance relation and adaptive grid algorithm, the multi‐objective sparrow search algorithm (MOSSA) is derived. After that, a two‐layer optimization framework (ISSA–MOSSA) is proposed to solve the studied system. The simulation results verify the accuracy of the proposed load forecasting model, the superiority of ISSA as well as MOSSA, and the effectiveness of ISSA–MOSSA in solving the energy optimal schedule problem of the distribution system with the access of DG.

This study investigates the optimal power flow (OPF) problem for distribution networks with the integration of distributed generation (DG). By considering the objectives of minimal line loss, minimal voltage deviation and maximum DG active power output, the proposed OPF formulation is a multi‐object optimisation problem. Through normalisation of each objective function, the multi‐objective optimisation is transformed to single‐objective optimisation. To solve such a non‐convex problem, the trust‐region sequential quadratic programming (TRSQP) method is proposed, which iteratively approximates the OPF by a quadratic programming with the trust‐region guidance. The TRSQP utilises the sensitivity analysis to approximate all the constraints with linear ones, which will reduce the optimisation scale. Active set method is utilised in TRSQP to solve quadratic programming sub‐problem. Numerical tests on IEEE 33‐, PG&E 69‐ and actual 292‐, 588‐, 1180‐bus systems show the applicability of the proposed method, and comparisons with the primal–dual interior point method and sequential linear programming method are provided. The initialisation and convergence condition of the proposed method are also discussed. The computational result indicates that the proposed algorithm for DG control optimisation in distribution system is feasible and effective.

A deeper coupling of information and power would make active distribution networks (ADNs) evolve into typical cyber-physical systems (CPSs). The unreliability of cyber systems can affect the security of ADNs. In this article, a methodology based on cyber-power joint analysis is presented to quantitatively evaluate the operational risk of ADNs caused by cyber contingencies. First, a typical CPS structure of ADNs is demonstrated and the influence ways of cyber contingencies are discussed. Then, a CPS modeling framework is proposed to analyze the information flow and cyber contingencies of cyber systems. To determine the best data transmission paths in cyber networks, a routing algorithm based on the link-state protocol is presented. Furthermore, in view of the response of ADNs to physical failures, an optimization model is developed to minimize the load shedding that results from the over-limited voltage. Finally, the expected load curtailment and the expected fault coverage used to quantify potential system losses are calculated using Monte Carlo simulation. The simulation results explain the effectiveness and practicability of the proposed models and methods.

The reactive power coordinated optimisation problem for distribution network (DN) with the integration of renewable distributed generation (DG) is investigated in this study. By actively participating in reactive power control together with an under‐load tap changer and shunt capacitors, DG can operate more effectively in the DN. Non‐dispatchable DG is considered in the coordinated optimisation method. The objective of the proposed reactive power coordinated optimisation method is to minimise active power loss and to decrease the number of switching device operations while maintaining the grid voltage within the allowable range. The optimisation problem is to solve a variable combination including integers and continuous variables, which will formulate a mixed integer non‐linear programming (MINLP) problem. The control variable includes operations of traditional reactive power control devices and the reactive power adjustments of DGs. To solve the MINLP problem, a heuristic searching method, an improved harmony search algorithm is proposed with adaptive parameters process. Numerical tests on a standard 10‐kV distribution system and a real distribution system demonstrate the applicability of the proposed reactive power coordinated optimisation method.