Abstract:What needs to be developed from the concept of “Smart Grid” is that: when renewable energy sources are absolutely prevailing in power generation, distributed power generation and distributed energy storage systems are widespread across the grid, and electric vehicle charging loads are prevailing in power load demands, how can the power grid support electric power as a core secondary energy source, undertake the role of a bridge between primary energy and end-use energy, and achieve the coordination and the optimization in macro energy perspective; how to guarantee the security of both macro energy and environment as well as the reliability of electricity. If a new term is needed, it should be Comprehensive Energy Network, not Energy Internet.

Abstract:Shale gas resources have the potential to significantly contribute to worldwide energy portfolio. A great number shale gas reserves have been identified in many countries. Connections of newly found gas reserves to the existing energy infrastructures are challenging, as many stakeholders and market uncertainties are involved. The proposed co-planning approach is formulated as a mixed integer nonlinear programming problem so as to minimize investments and enhance the reliability of the overall system. We propose a reliability assessment approach that is applicable for the coupled gas and electricity networks. In addition, the IEEE 24-bus RTS and a test gas system are applied to validate the performance of our approach. Based on the simulation results, the novel expansion co-planning approach is a robust and flexible decision tool, which provides network planners with comprehensive information regarding trade-offs between cost and system reliability.

Abstract:An approach of transmission network expansion planning with embedded constraints of short circuit currents and N-1 security is proposed in this paper. The problem brought on by the strong nonlinearity property of short circuit currents is solved with a linearization method based on the DC power flow. The model can be converted to a mixed-integer linear programming problem, realizing the optimization of planning model that considers the constraints of linearized short circuit currents and N-1 security. To compensate the error caused by the assumptions of DC power flow, the compensation factor is proposed. With this factor, an iterative algorithm that can compensate the linearization error is then presented. The case study based on the IEEE 118-bus system shows that the proposed model and approach can be utilized to: optimize the construction strategy of transmission lines; ensure the N-1 security of the network; and effectively limit the short circuit currents of the system.

Abstract:Cyber threats are serious concerns for power systems. For example, hackers may attack power control systems via interconnected enterprise networks. This paper proposes a risk assessment framework to enhance the resilience of power systems against cyber attacks. The duality element relative fuzzy evaluation method is employed to evaluate identified security vulnerabilities within cyber systems of power systems quantitatively. The attack graph is used to identify possible intrusion scenarios that exploit multiple vulnerabilities. An intrusion response system (IRS) is developed to monitor the impact of intrusion scenarios on power system dynamics in real time. IRS calculates the conditional Lyapunov exponents (CLEs) on line based on the phasor measurement unit data. Power system stability is predicted through the values of CLEs. Control actions based on CLEs will be suggested if power system instability is likely to happen. A generic wind farm control system is used for case study. The effectiveness of IRS is illustrated with the IEEE 39 bus system model.

Abstract:The low frequency oscillation characteristics of East China Power Grid after commissioning of the first ultra-high voltage alternating current (UHVAC) project—the Huai-Hu UHVAC project are studied. Several low frequency oscillation cases occurred in East China Power Grid in the past few years are reviewed and summarized. Based on the analysis of the different typical operation modes, the main low frequency oscillation modes in East China Power Grid in the early stages of development of ultra-high voltage (UHV) are summarized, and the impacts of the significant power grid maintenance on low frequency oscillation characteristics are analyzed. Besides, the oscillation mode of UHV generators to East China Power Grid is researched, and the importance of the power system stabilizator (PSS) is emphasized. Furthermore, the comparative analysis between the time domain and the frequency domain is carried out, and the influences of the governing system on low frequency oscillation characteristics are revealed. Finally, both the focus and the direction of low frequency oscillation research are presented.

Abstract:Under the background of complicated interconnected network, the splitting criterion for accurately capturing the electrical center in real time is the prerequisite of power grid splitting. This paper studies the features of electric quantity in the electrical center in aspect of the instantaneous frequency, and proposes the out-of-step splitting criterion for power systems based on bus voltage frequency. Firstly, through the establishment and solution to the out-of-step model of the power grid, the analytical expression of the voltage frequency at any position is obtained in the out-of-step oscillation, and the voltage frequency features of electrical center and non-electrical center are analyzed in details. Then, this paper constructs the typical scene of migration of electrical center to study the change rules of voltage frequency. Finally, the splitting criterion based on bus voltage frequency is proposed as well as the instruction for use. This criterion is easy to be realized and can adapt to the migration of electrical center. Also it is free from the limits of power network structure and operational mode. Simulation results of CEPRI-36 system and interconnected network example of one actual region verify the accuracy and the effectiveness of the proposed criterion.

Abstract:The high penetration of wind energy sources in power systems has substantially increased the demand for faster-ramping thermal units participating in the frequency regulation service. To fulfill the automatic generation control (AGC) and compensate the influence of wind power fluctuations simultaneously, ramping capacity should be considered in the dispatch model of thermals. Meanwhile, conventional methods in this area do not take the impact of transmission loss into the dispatch model, or rely on offline network model and parameters, failing to reflect the real relationships between the wind farms and thermal generators. This paper proposes an online approach for AGC dispatch units considering the above issues. Firstly, the power loss sensitivity is online identified using recursive least square method based on the real-time data of phasor measurement units. It sets up power balance constraint and results in a more accurate dispatch model. Then, an improved multi-objective optimization model of dispatch is proposed and a connection is established between the thermal units with fast ramping capacity and the wind farms with rapid fluctuations. Genetic algorithm is used to solve the dispatch model. The proposed method is compared with conventional methods in simulation case in the IEEE 30-bus system. Finally, simulation results verify the validity and the feasibility of identification method and optimization model.

Abstract:A novel multi-dimensional scenario forecast approach which can capture the dynamic temporal-spatial interdependence relation among the outputs of multiple wind farms is proposed. In the proposed approach, support vector machine (SVM) is applied for the spot forecast of wind power generation. The probability density function (PDF) of the SVM forecast error is predicted by sparse Bayesian learning (SBL), and the spot forecast result is corrected according to the error expectation obtained. The copula function is estimated using a Gaussian copula-based dynamic conditional correlation matrix regression (DCCMR) model to describe the correlation among the errors. And the multi-dimensional scenario is generated with respect to the estimated marginal distributions and the copula function. Test results on three adjacent wind farms illustrate the effectiveness of the proposed approach.

Abstract:Wind power ramp events increasingly affect the integration of wind power and cause more and more problems to the safety of power grid operation in recent years. Several forecasting techniques for wind power ramp events have been reported. In this paper, the statistical scenarios forecasting method is proposed for wind power ramp event probabilistic forecasting based on the probability generating model. Multi-objective fitness functions are established considering cumulative density functions and higher order moment autocorrelation functions with respect to the consistency of distribution and timing characteristics, respectively. Parameters of probability generating model are calculated by the iterative optimization using the modified genetic algorithm with multi-objective fitness functions. A number of statistical scenarios captured bands are generated accordingly. Eventually, ramp event probability characteristics are detected from scenarios captured bands to evaluate the ramp event forecasting method. A wind plant of Bonneville Power Administration with actual wind power data is selected for calculation and statistical analysis. It is shown that statistical results with multi-objective functions are more accurate than the results with single objective functions. Moreover, the statistical scenarios forecasting method can accurately estimate the characteristics of wind power ramp events. The results verify that the proposed method can guide the generation method of statistical scenarios and forecasting models for ramp events.

Abstract:Wind speed dependences on different areas in a wind farm have influences on security and economic operation in power system. In order to simulate the correlation of wind speed series between different positions, this paper applies Copula function and rank correlation matrix methods to measure the coherence of wind speed in a wind farm. The correlated wind sample space is established. According to active power output characteristics of wind turbines, the polymerization model in a wind farm can be achieved. Monte Carlo optimal power flow is applied to IEEE-30 and IEEE-300 bus systems based on the principle of energy saving dispatching. The study shows that the accuracy of outputs is improved, thus reducing the fluctuation ranges in unit generating costs and power flow in branches while considering wind speed polymerization. This approach provides a new method to improve the effectiveness of energy saving dispatching and system operation arrangement. Results have been tested to be effective.

Abstract:Demand response (DR) and wind power are beneficial to low-carbon electricity to deal with energy and environmental problems. However, the uncertain wind power generation (WG) which has anti-peaking characteristic would be hard to exert its ability in carbon reduction. This paper introduces DR into traditional unit commitment (UC) strategy and proposes a multi-objective day-ahead optimal scheduling model for wind farm integrated power systems, since incentive-based DR can accommodate excess wind power and can be used as a source of system spinning reserve to alleviate generation side reserve pressure during both peak and valley load periods. Firstly, net load curve is obtained by forecasting load and wind power output. Then, considering the behavior of DR, a day-ahead optimal dispatching scheme is proposed with objectives of minimum generating cost and carbon emission. Non-dominated sorting genetic algorithm-II (NSGA-II) and satisfaction-maximizing method are adopted to solve the multi-objective model with Pareto fronts and eclectic decision obtained. Finally, a case study is carried out to demonstrate that the approach can achieve economic and environmental aims and DR can help to accommodate the wind power.

Abstract:To optimize the energy capture from the wind, wind turbine (WT) should operate at variable speed. Based on the wind speed, the operating regions of the WT are divided into two parts: below and above the rated wind speed. The main aim at below rated wind speed is to maximize the energy capture from the wind with reduced oscillation on the drive train. At above rated wind speed, the aim is to maintain the rated power by using pitch control. This paper presents the control of WT at below rated wind speed by using backstepping sliding mode control (BSMC). In BSMC, generator torque is considered as the control input that depends on the optimal rotor speed. Usually, this optimal rotor speed is derived from effective wind speed. In this paper, effective wind speed is estimated from aerodynamic torque and rotor speed by using the modified Newton Rapshon (MNR) algorithm. Initially, a conventional sliding mode controller (SMC) is applied to the WT, but the performance of the controller was found to be less robust with respect to disturbances. Generally, WT external disturbance is not predictable. To overcome the above drawback, BSMC is proposed and both the controllers are tested with mathematical model and finally validated with the fatigue, aerodynamics, structures, and turbulence (FAST) WT simulator in the presence of disturbances. From the results, it is concluded that the proposed BSMC is more robust than conventional SMC in the presence of disturbances.

Abstract:Solar energy from photovoltaic (PV) is among the fastest developing renewable energy systems worldwide. Driven by governmental subsidies and technological development, Europe has seen a fast expansion of solar PV in the last few years. Among the installed PV plants, most of them are situated at the distribution systems and bring various operational challenges such as power quality and power flow management. The paper discusses the modelling requirements for PV system integration studies, as well as the possible techniques for voltage rise mitigation at low voltage (LV) grids for increasing PV penetration. Potential solutions are listed and preliminary results are presented.

Abstract:Microgrid is a good option to integrate renewable energy sources (RES) into power systems. In order to deal with the intermittent characteristics of the renewable energy based distributed generation (DG) units, a fuzzy-logic based coordinated control strategy of a battery energy storage system (BESS) and dispatchable DG units is proposed for the microgrid management system (MMS). In the proposed coordinated control strategy, the BESS is used to minimize active power exchange at the point of common coupling of the microgrid for grid-connected operation, and is used for frequency control for island operation. The efficiency of the proposed control strategy was tested by case studies using DIgSILENT/PowerFactroy.

Abstract:Islanded microgrids must be self-sufficient in terms of frequency and voltage control due to their islanded operation. A control strategy for frequency regulation by combining the operation of a wind generator, a diesel generator, a battery energy storage system and a dump load in a microgrid is proposed in this paper. In the proposed strategy, the control task is partitioned into two subtasks: 1) choosing the appropriate element to be used for regulation, and 2) providing frequency regulation. A global controller chooses the element to operate. Then, the frequency regulation is provided by separate individual controllers. The proposed control strategy is tested on a microgrid with mixed types of generation and modeled on Simulink. By monitoring the power of individual elements and system frequency, it is shown that the proposed control strategy operates efficiently. The proposed strategy facilitates the integration of renewable energy sources and enhances frequency regulation.

Abstract:The capacity and the scale of smart substation are expanding constantly, with the characteristics of information digitization and automation, leading to a quantitative trend of data. Aiming at the existing processing shortages in the big data processing, the query and analysis of smart substation, a data compression processing method is proposed for analyzing smart substation and Hive. Experimental results show that the compression ratio and query time of RCFile storage format are better than those of TextFile and SequenceFile. The query efficiency is improved for data compressed by Deflate, Gzip and Lzo compression formats. The results verify the correctness of adjacent speedup defined as the index of cluster efficiency. Results also prove that the method has a significant theoretical and practical value for big data processing of smart substation.

Abstract:Smart Grids are characterized by the application of information communication technology (ICT) to solve electrical energy challenges. Electric power networks span large geographical areas, thus a necessary component of many Smart Grid applications is a wide area network (WAN). For the Smart Grid to be successful, utilities must be confident that the communications infrastructure is secure. This paper describes how a WAN can be deployed using WiMAX radio technology to provide high bandwidth communications to areas not commonly served by utility communications, such as generators embedded in the distribution network. A planning exercise is described, using Northern Ireland as a case study. The suitability of the technology for real-time applications is assessed using experimentally obtained latency data.