Shiyu Liu

A Two-Stage Robust Reactive Power Optimization Considering Uncertain Wind Power Integration in Active Distribution Networks

Traditional reactive power optimization aims to minimize the total transmission losses by control reactive power compensators and transformer tap ratios, while guaranteeing the physical and operating constraints, such as voltage magnitudes and branch currents to be within their reasonable range. However, large amounts of renewable resources coming into power systems bring about great challenges to traditional planning and operation due to the stochastic nature. In most of the practical cases from China, the wind farms are centrally integrated into active distribution networks. By the use of conic relaxation based branch flow formulation, the reactive optimization problem in active distribution networks can be formulated as a mixed integer convex programming model that can be tractably dealt with. Furthermore, to address the uncertainties of wind power output, a two-stage robust optimization model is proposed to coordinate the discrete and continuous reactive power compensators and find a robust optimal solution that can hedge against any possible realization within the uncertain wind power output. Moreover, the second order cone programming-based column-and-constraint generation algorithm is employed to solve the proposed two-stage robust reactive power optimization model. Numerical results on 33-, 69- and 123-bus systems and comparison with the deterministic approach demonstrate the effectiveness of the proposed method.

Sequential power flow simulation of integrated dynamic wireless power transfer systems

In view of the advance of dynamic wireless power transfer (DWPT) for electric vehicles (EVs) charging, integrated DWPT systems are conceivable to emerge. However, quasi-continuous and time-varying DWPT charging loads bring large challenges to the power flow analysis of integrated DWPT systems. In this paper, a sequential load model is proposed to describe the temporal dependency of DWPT charging demands. Furthermore, on the basis of back/forward sweep method, a new power flow analysis method is addressed to deal with quasi-continuous and time-varying DWPT charging loads. Then a daylong sequential power flow simulation is conducted on a test system. Simulation results show that the fluctuation of branch flows varies significantly. Adequate power and energy managements are necessary to integrated DWPT systems.

A second order cone based relaxation and decomposition algorithm for multi-period reactive power optimization considering uncertain PV integration in active distribution networks

To address daily operating times of discrete reactive power compensators, multi-period reactive power optimization (MPRPO) is set up to minimize energy loss over multiple periods. This paper proposes a second-order cone relaxation and decomposition (SOCRD) algorithm for solving MPRPO problem considering uncertain PV integration in active distribution networks to improve computational performance. To deal with uncertainty output of PV generation, an extended stochastic programming is employed in this method, coordinating with continuous and discrete reactive power compensators. Solution quality and computation performance are compared with deterministic model as well as traditional algorithms on IEEE-33 bus system, which illustrates efficiency and effectiveness of the proposed method.

Researches on the optimization model and strategies against low voltage in power distribution network

Low voltages and high power loss are two main problems in distribution network especially in remote area. To solve these problems, typical events of low voltage in distribution network need to be analyzed and identify the similarities. Furthermore, building general optimization model for low voltage in distribution network and proposing improved strategies related to such problems are also necessary. This paper proposes optimization model and strategies against low voltage using Matlab as the main platform with objective functions and several constraints. The particle swarm optimization (PSO) is used to solve the problem. With the open DSS COM interface connected to Matlab, the open DSS are called to calculate distribution network 3-phase power flow repeatedly. Finally, the optimizing strategy, including transformer tap positions and capacitors in each node are obtained. Results from simulations verify the effectiveness and feasibility of the proposed model.

Optimal power flow with Series Static Voltage Restorer (SSVR) in distribution systems considering PV integration

DFACTS are technically used in distributed systems to handle with voltage sags, reactive power compensation and other power quality problems. Series Static Voltage Restorer (SSVR) is one of typical DFACTSs for voltage profile improvement that is modeled in this paper. Furthermore, the optimal power flow in distribution systems with PV integration is subsequently performed to minimize the power loss. IEEE 33 as well as IEEE 69 bus systems are utilized to show the effectiveness of the performance of SSVR on the active networks with PV integration. Finally, the effect of capacity and location of SSVR on voltage mitigation and power loss reduction is discussed.