Jiakun Fang

Design of Anti-Windup Compensator for Energy Storage-Based Damping Controller to Enhance Power System Stability

The application of energy storage (ES) in power system is limited due to the high cost of the ES device, which exponentially increases with its capacity. This paper is to improve the saturation-dependent stability of the power system equipped with the energy storage based damping controller (ESDC), and hence, reduce the required size of the ES. The phenomenon that the capacity of ES is smaller than the required value produced by the ESDC, is modeled as actuator saturation using the saturation function. The proposed method is to design an anti-windup compensator (AWC), which in the event of saturation, produces a signal based on the output difference between the ESDC and saturated ES and then augment the signal to the ESDC to alleviate the adverse effect of saturation. The AWC is designed with the reduced-order model of power system and linear matrix inequality. Detailed design procedure is introduced. Case studies based on a modified 4-machine 2-area power system and 10-machine New England power system are carried out to demonstrate the effectiveness of the AWC design method.

Laboratory and Field Tests of Movable Conduction-Cooled High-Temperature SMES for Power System Stability Enhancement

This paper introduces the first movable conduction-cooled high-temperature superconducting magnetic energy storage (SMES) system developed in China. The SMES is rated at 380 V/35 kJ/7 kW, consisting of the high-temperature magnet confined in a Dewar, the cryogenic unit, the converter, the monitoring and control unit, the container, etc. The proposed SMES can be loaded onto a truck to move to a desired location and put into operation with easy connection. Laboratory and field tests have been carried out to investigate the operational characteristics and to demonstrate the SMES effectiveness on improvements of system voltage stability and on the oscillation damping. Test results indicate that the SMES system has the features of fast response and four-quadrant power operation. The accessories for the movability of the SMES system are well designed. The system is feasible to be used in power systems.

Power System Structural Vulnerability Assessment Based on an Improved Maximum Flow Approach

With the increasing complexity of the power grid and the concerns on major blackouts, there is an urgent need for an efficient and effective tool to assess the power system structural vulnerability. To tackle this challenge, this paper proposes a maximum flow-based complex network approach to identify the critical lines in a system. The proposed method consists of two major steps. First, the power network is modeled as a graph with edges (transmission lines, transformers, etc.) and nodes (buses, substations, etc.). The critical scenarios are identified by using the principal component analysis and convex hull. Then the second step is to use an improved maximum flow-based complex network approach for topology analysis. Weighted vertices in the network are considered, enabling taking the selected operating conditions into consideration when identifying the vulnerable lines. The proposed method is validated using the western Danish power system. The vulnerable lines in the network are ranked. Simulation results demonstrate the effectiveness of the method by intentional attacks and comparison with the planning strategy from the system operator.

Comparison study of power system small signal stability improvement using SSSC and STATCOM

A static synchronous series compensator (SSSC) has the ability to emulate a reactance in series with the connected transmission line. A static synchronous compensator (STATCOM) is able to provide the reactive power to an electricity network. When fed with some supplementary signals from the connected power system, both SSSC and STATCOM are able to participate in the power system inter-area oscillation damping by changing the compensated reactance or the provided reactive power. This paper analyses the influence of SSSC and STATCOM on power system small signal stability. The damping controller schemes for SSSC and STATCOM are presented and discussed. The IEEE 39-bus New England system model as the test system is built in DIgSIELNT PowerFactory, in which the damping control strategies for both SSSC and STATCOM are validated by time domain simulations and modal analysis. Furthermore, comparison studies show that the SSSC is a better solution in term of equipment capabilities and costs.

TCSC Nonlinear Adaptive Damping Controller Design Based on RBF Neural Network to Enhance Power System Stability

In this paper, a nonlinear adaptive damping controller based on radial basis function neural network (RBFNN), which can infinitely approximate to nonlinear system, is proposed for thyristor controlled series capacitor (TCSC). The proposed TCSC adaptive damping controller can not only have the characteristics of the conventional PID, but adjust the parameters of PID controller online using identified Jacobian information from RBFNN. Hence, it has strong adaptability to the variation of the system operating condition. The effectiveness of the proposed controller is tested on a two-machine five-bus power system and a four-machine two-area power system under different operating conditions in comparison with the lead-lag damping controller tuned by evolutionary algorithm (EA). Simulation results show that the proposed damping controller achieves good robust performance for damping the low frequency oscillations under different operating conditions and is superior to the lead-lag damping controller tuned by EA.

Dynamic Optimal Energy Flow in the Integrated Natural Gas and Electrical Power Systems

This paper focuses on the optimal operation of the integrated gas and electrical power system with bidirectional energy conversion. Considering the different response times of the gas and power systems, the transient gas flow and steady-state power flow are combined to formulate the dynamic optimal energy flow in the integrated gas and power systems. With proper assumptions and simplifications, the problem is transformed into a single-stage linear programming to obtain the optimal operation strategy for both gas and power systems. Simulation on the test case illustrates the success of the modeling and the beneficial roles of the power-to-gas are analyzed. The proposed model can be used in the decision support for both planning and operation of the coordinated natural gas and electrical power systems.

Stochastic Optimization of Economic Dispatch for Microgrid Based on Approximate Dynamic Programming

This paper proposes an approximate dynamic programming (ADP)-based approach for the economic dispatch (ED) of microgrid with distributed generations. The time-variant renewable generation, electricity price, and the power demand are considered as stochastic variables in this paper. An ADP-based ED (ADPED) algorithm is proposed to optimally operate the microgrid under these uncertainties. To deal with the uncertainties, Monte Carlo method is adopted to sample the training scenarios to give empirical knowledge to ADPED. The piecewise linear function (PLF) approximation with improved slope updating strategy is employed for the proposed method. With sufficient information extracted from these scenarios and embedded in the PLF function, the proposed ADPED algorithm can not only be used in day-ahead scheduling but also the intra-day optimization process. The algorithm can make full use of historical prediction error distribution to reduce the influence of inaccurate forecast on the system operation. Numerical simulations demonstrate the effectiveness of the proposed approach. The near-optimal decision obtained by ADPED is very close to the global optimality. And it can be adaptive to both day-ahead and intra-day operation under uncertainty.

Residue-based coordinated selection and parameter design of multiple power system stabilizers (PSSs)

Residue method is a commonly used approach to design the parameters of a power system stabilizer (PSS). In this paper, a residue identification method is adopted to obtain the system residues for different input-output pairs, using the system measurements data from time domain simulations. Then a coordinated approach for multiple PSS selection and parameter design based on residue method is proposed and formatted as an optimization problem. Particle swarm optimization (PSO) is adopted in this coordination process to find suitable parameters for PSSs so that the dominant oscillation modes can be well damped; while locations and input signals of PSSs are selected to keep PSS outputs small. The IEEE 39-bus New England system model as the test system is built in DIgSIELNT PowerFactory 14.0, in which the proposed coordination method is validated by time domain simulations and modal analysis.

Operational characteristic of the current converter based SMES

Superconducting Magnetic Energy Storage (SMES) is believed to be a potential solution for power quality improvements. This paper is to propose a power conditioner system forthe SMES operation. The SMES is located at the generator bus terminal to suppressing the power oscillation during dynamic period. Through the experiment results given, this paper developed a detailed model of the fabricated SMES. Comparison between simulation results and practical experiment demonstrates that this model can fully reflect the operational characteristics of the practical one. Interpretation to the mechanism of the experiments is proposed after, using the equal area criterion.

A multistage coordinative optimization for sitting and sizing P2G plants in an integrated electricity and natural gas system

Power-to-Gas (P2G) allows for the large scale energy storage which provides a big potential to accommodate the rapid growth of the renewables. In this paper, a long-term optimization model for the co-planning of the electricity and natural gas systems is presented. The P2G Plants are optimally sited and sized in the integrated energy system. The problem model is formulated as a multi-stage integer nonlinear optimization. The objective is to minimize the investment plus operation costs by determining the optimal location, capacity, and installation time of P2G. Case studies are simulated to illustrate the proposed approach.