Libao Shi

Optimal Power Flow Solution Incorporating Wind Power

This paper presents a solution of optimal power flow (OPF) incorporating wind power. A paradigm for modeling the cost of wind-generated electricity from a wind farm is proposed. Based on the Weibull wind speed distribution and wind turbine model represented by function approximation, the frequency distribution of wind farm power output to be the basis for modeling wind generation cost is established via applying Monte Carlo simulation. The proposed wind generation cost model consists of the opportunity cost of wind power shortage and the opportunity cost of wind power surplus, which reflect the cost of dispatching additional reserve capacity and the cost of environmental benefit loss, respectively, and it is integrated into the conventional OPF program. Furthermore, the small signal stability constraints are considered simultaneously as well during optimization. A self-adaptive evolutionary programming method is employed to solve the OPF with wind power involved. A case study is conducted based on the IEEE New England test system (10-Generator-39-Bus) as a benchmark. The simulation results demonstrate the effectiveness and validity of the proposed model and method.

A Survey on Wind Power Technologies in Power Systems

As one of the most promising renewable energy sources, wind power technology has been widely developed in recent years. As increasing of penetration levels of wind power on power systems, several research fields in power systems involving system modeling, planning, control and dynamics et al., are emphasized further with the consideration of wind power. This paper reviews the wind turbine dynamic models, control systems. The corresponding applications in power systems including planning and reliability, stability analysis have been discussed. Furthermore, the hybrid wind power systems considering the fuel cell and photovoltaic energies are reviewed as well.

Optimal power flow with consideration of wind generation cost

This paper discusses the solution of optimal power flow incorporating wind generation cost. A new model of wind generation cost is presented based on the probability distribution of wind farm power output. In this model, the wind farm generation cost consists of two components: the reserve capacity cost and the environmental benefit loss. Both of the two components could be attributed to the intermittence and uncertainties of wind power. A self-adaptive evolutionary programming method is employed to solve the OPF with wind power incorporated. A case study is conduced based on the IEEE New England test system (10-Geneartor-39-Bus) as benchmark. The simulation results demonstrate the effectiveness and validity of the proposed model and method.

Challenges of large wind generation intermittence and fluctuation for future smart grids

With introduction of smart grid concept, how to face up to the impacts of grid-connected renewable energy sources, especially like wind power on power systems becomes one of the most important issues in development of smart grid. This paper will discuss the potential challenges the smart grids will confront with respect to large wind generation intermittence and fluctuation from a technical point of view. The context will involve power system planning, reliability evaluation, voltage stability and frequency stability. Technical requirements and solutions in dealing with those challenges imposed by wind generation for future smart grids are also proposed.

Impact of Intermittent Wind Generation on Power System Small Signal Stability

In recent years, the increasing concerns to environmental issues demand the search for more sustainable electrical sources. Wind energy can be said to be one of the most prominent renewable energy sources in years to come (Ackermann, 2005). And wind power is increasingly considered as not only a means to reduce the CO2 emissions generated by traditional fossil fuel fired utilities but also a promising economic alternative in areas with appropriate wind speeds. Albeit wind energy currently supplies only a fraction of the total power demand relative to the fossil fuel fired based conventional energy source in most parts of the world, statistical data show that in Northern Germany, Denmark or on the Swedish Island of Gotland, wind energy supplies a significant amount of the total energy demand. Specially it should be pointed out that in the future, many countries around the world are likely to experience similar penetration levels. Naturally, in the technical point of view, power system engineers have to confront a series of challenges when wind power is integrated with the existing power system. One of important issues engineers have to face is the impact of wind power penetration on an existing interconnected large-scale power system dynamic behaviour, especially on the power system small signal stability. It is known that the dynamic behavior of a power system is determined mainly by the generators. So far, nearly all studies on the dynamic behavior of the grid-connected generator under various circumstances have been dominated by the conventional synchronous generators world, and much of what is to be known is known. Instead, the introduction of wind turbines equipped with different types of generators, such as doublyfed induction generator (DFIG), will affect the dynamic behaviour of the power system in a way that might be different from the dominated synchronous generators due to the intermittent and fluctuant characteristics of wind power in nature. Therefore, it is necessary and imperative to study the impact of intermittent wind generation on power system small signal stability. It should be noticed that most published literature are based on deterministic analysis which assumes that a specific operating situation is exactly known without considering and responding to the uncertainties of power system behavior. This significant drawback of deterministic stability analysis motivates the research of probabilistic stability analysis in which the uncertainty and randomness of power system can be fully understood. The

Effects of wind power variability and intermittency on power flow

The variability and intermittency of wind generation have brought new challenges to the planning and operation of interconnected power systems with high penetration of grid-connected wind farms. In this paper, the probability theory and fuzzy sets theory are employed to carry out systematic and thorough studies on power system fuzzy power flow calculation incorporating uncertainties of wind power from different types of wind turbines. The Weibull distribution which can reflect the variability and intermittency of wind power well is used as wind speed probability density model. With the possibility/ probability consistency principle(PPCP), it is transformed to the wind speed possibility distribution. In accordance with the simplified power-speed curve of wind turbine, the fuzzy modeling for power outputs of SCIG and DFIG is then presented. The proposed fuzzy model is linearized further for simplicity. The sensitivity analysis based method is employed to solve the possibility distributions of fuzzy power flow solutions. Numerical results based on a modified IEEE 14-bus system demonstrate the validity and effectiveness of the proposed models and methods.

Electric grid vulnerability assessment under attack-defense scenario based on game theory

In recent years, how to effectively assess the electric grid vulnerability in protecting against a malicious attack becomes one of the most challenging cutting-edge issues to be solved in power systems. This paper presents a framework to analyze the vulnerability of electric grid under different attack-defense scenarios based on the knowledge of game theory. Pure strategy and mixed strategy Nash Equilibrium corresponding to the attack-defense contest can be obtained by solving the payoff matrix under different pre-defined attack-defense scenarios. Based on the Nash Equilibrium, the vulnerability rankings of power grid components can be obtained and the vulnerability assessment can be conducted as well as the allocation plan of defense fund.

Real-time simulation on wind power system dynamics incorporating STATCOM

Based on an advanced distributed real-time platform named Real-Time Laboratory (RT-LAB), the impacts of the static synchronous compensator (STATCOM) on wind power system dynamics is studied in this paper. Firstly, a small-scale wind farm model based on squirrel-cage induction generator (SCIG) is built in MATLABTM/Simulink environment. This model is then rebuilt to be suitable for the real-time operation mode in RT-LAB environment in terms of the operating requirements of RT-LAB. The corresponding comparisons of simulation results carried out in RT-LAB and MATLABTM/Simulink environments respectively demonstrate that it is applicable for wind power system to implement real-time simulation in RT-LAB environment. Finally, the STATCOM device is connected to the power grid. And the comparisons of real-time simulation results of the wind power system with and without STATCOM connected illustrate that the integration of STATCOM can improve the voltage stability of the system.

Optimal distribution network expansion planning incorporating distributed generation

An optimization model is proposed to give an economical evaluation on different network expansion plans when installing distributed generations (DGs) together with building new lines. The expenditure of construction and maintaining of new DGs as well as new lines, the annual power loss costs are both integrated into the objective function which is to minimize the annual cost of network expansion during planning period. The genetic algorithm (GA) is employed to solve the aforementioned optimization problem. Finally, case studies are carried out on the 3-feeder-16-bus system and a single-feeder-33-bus system as benchmark to demonstrate the validity of the proposed model and method.

Multi-objective optimal operation incorporating wind power

In this paper, a wind generation cost model reflecting the intermittency of wind power is proposed and integrated into a multi-objective optimal operation issue of power system. The proposed wind generation cost model is based on the frequency distribution of wind farm power output, which is obtained by applying Monte Carlo simulation to the wind speed model. Total 3 objectives involving minimization of power generation costs (inclusion of wind generation), minimization of pollution emissions and minimization of transmission losses as well as the small signal stability constraints are considered during modelling. An improved evolutionary algorithm called as self-adaptive evolutionary programming (SAEP) is employed to solve the multi-objective optimal operation problem with wind power incorporated. The IEEE New England test system is employed as benchmark to carry out the case studies. Numerical results illustrate the effectiveness and validity of the proposed model and method.