Optimal transmission network reconfiguration is an important means to improve the economy and reliability of power grid. However, the traditional optimal transmission switching only considers the transmission line switching strategy and some approximate power flow models are adopted to make it tractable, such as linearisation or convex relaxation ones. In this article, first, a comprehensive network reconfiguration model considering both the line switching strategy and the bus splitting strategy inside substations is established. This optimal network reconfiguration incorporating AC power flow equations is an intractable mixed integer non-linear programming problem. The model is first relaxed to a mixed integer second-order cone programming to get the initial solution and an extended feasibility recovery algorithm is developed to obtain the solution satisfying the AC power flow equations. Numerical tests show that the proposed method can reduce the total generation cost and guarantee the system security while the baseline methods cannot obtain feasible solution in most cases.

针对光热电站和热电联供(combined heat and power,CHP)系统联合优化调度难题,提出了一种以运行成本最低为目标的两阶段随机优化调度模型.在日前调度阶段,以能源出力预测值作为输入量,制定各微元出力的日前调度计划.在实时调整阶段,采用动态场景生成和削减的方法,建立光热出力的不确定性模型,从而制定日内实际备用计划.通过天津地区典型案例仿真分析,表明本文提出的两阶段优化调度模型能够保证所制定的日前调度阶段出力计划和日内实时调整阶段备用计划的有效性,提高了系统可靠性且降低运行成本.

Convex relaxation methods have been studied and used extensively to obtain an optimal solution to the optimal power flow (OPF) problem. Meanwhile, convex relaxed power flow equations are also prerequisites for efficiently solving a wide range of problems in power systems including mixed-integer nonlinear programming (MINLP) and distributed optimization. When the exactness of convex relaxations is not guaranteed, it is important to recover a feasible solution for the convex relaxation methods. This paper presents an alternative convex optimization (ACP) approach that can efficiently recover a feasible solution from the result of second-order cone programming (SOCP) relaxed OPF in mesh networks. The OPF problem is first formulated as a difference-of-convex (DC) programming problem, then efficiently solved by a penalty convex concave procedure (CCP). CCP iteratively linearizes the concave parts of the power flow constraints and solves a convex approximation of the DCP problem. Numerical tests show that the proposed method can find a global or near-global optimal solution to the AC OPF problem, and outperforms those semidefinite programming (SDP) based algorithms.

In this paper, a fully distributed power flow algorithm is proposed. The method is composed of outer iteration and inner iteration. The outer iteration is identical to newton's method, while the inner iteration solves the power flow correction equation using an exponentially fast converged distributed algorithm. The proposed algorithm does not need coordination infrastructure and each area in power systems only need to communicate less important information with neighbors. The numerical tests show that the method is able to converge with the same behavior as Newton's method.

基于电压源型换流器的多端直流输电电网是解决可再生能源并网和消纳的有效途径,因此研究交直流混合电网的潮流算法很有必要。提出了一种基于扩展节点法的交直流混合电网统一潮流算法。首先建立了电压源型换流站的稳态模型和控制策略及基于扩展节点法的交流和直流电网的网络模型。然后推导了基于牛顿法的统一潮流算法,将交直流混合电网的节点注入电流、支路电流和节点电压作为未知变量同时求解。通过IEEE 30节点交直流混合电网算例验证了所提算法的有效性。

The branch flow based optimal power flow (OPF) problem in radially operated distribution networks can be exactly relaxed to a second-order cone programming model without considering transformers. However, the introduction of nonlinear transformer models will make the OPF model nonconvex. This letter presents an exact linearized transformer's on-load tap-changer model to keep the OPF model convex via a binary expansion scheme and big-M method. Validity of the proposed method is verified using IEEE 33-bus test network.

This study presents a comprehensive optimisation model that combines reactive power (VAR) optimisation and network reconfiguration to minimise power losses and eliminate voltage violations. In this model, the reactive power of distributed generators (DGs), VAR compensators, the position of tap-changer and the states of branches are formulated as continuous and discrete decision variables. The original non-convex three-phase optimisation model was converted to a mixed-integer second-order cone programming model using the second-order cone relaxation, big-M method and piecewise linearisation. The results of numerical tests showed that the proposed model can achieve significant additional gains in network loss reduction and voltage violation mitigation. This developed method can be used as a basic analysis tool for active distribution networks operation schedule or planning.

This letter presents a mixed integer quadratic programming (MIQP) based topology identification model, which is suitable for radially operated distribution networks. This approach finds the topology configuration with weighted least square (WLS) of measurement residues. Validity of the proposed method is demonstrated using an IEEE 33-bus test network.