High Wind Power Penetration Research Articles

Voltage stability analysis of wind power plant integration into transmission network of Nepal

Government of Nepal has realized that wind energy could become a major source of alternative energy to solve energy crisis in the country as well as serve the purpose of energy mix. Various studies have identified several locations with potential for wind power generation in Nepal. The integration of wind power plant to the national grid, however, raises concerns regarding the power system stability. The voltage stability of the grid is a key issue, the effect on which increases with the increase in wind power penetration in the grid. This study performs voltage stability analysis due to high penetration of wind power in Integrated Nepalese Power System (INPS). Both steady state and dynamic stability study is performed using the power system simulation software DigSILENT/PowerFactory for different types of wind turbine generators.

Study of offshore wind power penetration rate in gas turbine generator platform power grid

Because of the energy supply of the offshore oil platforms mainly relies on the supply of gas turbine, the development of renewable energy will become a rich energy supply for offshore oil platforms and a reliable way to improve the stability of the grid of the platforms. This paper developed the simulation model of offshore oil gas turbine platform power grid, simulated the hybrid power grid structure, the energy storage of frequency regulation, high wind power penetration rate, wind power and gas turbine power frequency stability and fault treatment. The method of increasing renewable energy penetration rate was proposed, and the hybrid energy coordinated control strategy of offshore oil platform was also carried out. Based on the weakly connected distributed offshore oil platform power grid project, this paper studied the influence of wind power and turbine power penetration rate on the power grid, in order to explore, determine and verify the limit of high wind power penetration rate under the condition of “large generation machine and small grid”. The simulation experiment of high wind power penetration rate under the condition of different load conditions and different wind speed limits were discussed, on the basis of research the influence degree of the stability of power grid frequency of low wind power swings, as well as to the wind power is given priority to with gas turbine mainly in both cases the advantages and disadvantages of the grid system, and attempt to put forward the corresponding switch control strategy.

Planning of electric vehicle charging stations and distribution system with highly renewable penetrations

With the increasing prevalence of electric vehicles (EVs), the EV charging station (EVCS) and power distribution have become a coupled physical system. A multi-objective planning model is developed herein for the sizing and siting of EVCSs and the expansion of a power distribution network with high wind power penetration. The objectives of the planning model are to minimise the total cost of investment and energy losses of the distribution system while maximising the total captured traffic flow. The uncertainties associated with wind power sources are considered. Additionally, the uncertainties in EV daily charging loads are also important concerns in the optimisation of the planning model. To model the EV load uncertainties, a recent scenario generation (SG) method is adopted. Further, a multi-objective optimisation tool, Multi-Objective Natural Aggregation Algorithm (MONAA), is introduced to obtain the final solutions of the planning model. The simulations based on coupled 54-node distribution network and 25-node traffic network systems are conducted to verify the efficiency of the proposed model and the effectiveness of SG-based MONAA.

Overvoltage Suppression Strategy for Sending AC Grid With High Penetration of Wind Power in the LCC-HVdc System Under Commutation Failure

With the increase of wind power installation capacity, the line commutated converter (LCC)-based high-voltage direct current (HVdc) transmission system is an effective scheme for long distance transmission of wind power. Commutation failure is a common fault for LCC-HVdc transmission system. During the commutation failure, the voltage of sending ac grid presents the “first decreased then increased” characteristic. In order to avoid the overvoltage under the commutation failure causing the wind power generation system (WPGS) to separate from the power grid, it is necessary to suppress the overvoltage of sending ac grid under commutation failure. This article quantitatively analyzes for the first time the transient voltage characteristics of the sending ac grid under commutation failure. The analysis indicates that the delay of the grid voltage detection part in the wind turbine is the significant influence factor on the overvoltage of sending ac grid. Based on the analysis results, this article proposes the delay compensation control strategy of WPGS to suppress the over voltage of the sending ac grid with high penetration of wind power under commutation failure. The effectiveness of the strategy is verified by simulation and control hardware in-loop experiment, and it is also verified that the strategy is also applicable for conventional low-voltage ride through faults, which shows that the control strategy is universal.

Conventional generation emulation for power grids with a high penetration of wind power

Abstract Integrating large-scale wind plants with the electricity grids has many challenges for grid operators. Besides the variability and uncertainty of wind power, coordinating between different technologies of generation in the same grid can be considered the main problem, specifically for short-term frequency stability. Therefore, a large penetration of wind power generation in modern power grids has a risky influence on the power-system frequency. Wind-generation plants have contradictory behaviour compared to classic thermal plants, especially in active generated power-shortage events due to the variable nature of wind power. Existing experience in wind plants keeps part of the available wind power unloaded, using what are known as deloading techniques. Different deloading techniques are usually applied to emulate the thermal-plant-governor function and confirm a proper spinning reserve for any active-power shortages. These techniques decrease the generated power from wind plants continuously from maximum point tracking ones. Consequently, the practical capacity, annual generated energy and economical income of wind plants are reduced. In addition, grid-protection and control sub-schemes are set and designed according to the well-known conventional responses of thermal plants, which increase the need for thermal-plant-behaviour emulation. In this paper, instead of the usual deloading methods, a supercapacitors scheme is proposed with wind turbines to emulate the response of conventional power plants. The study discusses the technical and economic benefits of the proposed addition of supercapacitors in the wind-plant-planning phase. Restricted frequency grid-code indices are selected to evaluate studied behaviours. Simulation results of the IEEE four-generation two-area system determines the effectiveness of suggested schemes technically. The System Advisor Model (SAM) program estimates the economic benefits of a typical US study case compared with the existing wind-deloading technique.

A data-adaptive robust unit commitment model considering high penetration of wind power generation and its enhanced uncertainty set

Wind power generation is increasingly penetrating into the power grid, which brings great challenges to the dispatch of power systems. With the popularization of data mining technology, further exploration of the random characteristics of wind power based on the available wind power data can significantly improve the applicability of scheduling decisions. In this paper, a novel data-adaptive robust unit commitment model under high penetration of wind power is proposed, which derives a robust dispatch solution with minimal generation cost while hedging against the worst case in the uncertainty set. Firstly, copula theory is carried out to formulate a joint probabilistic distribution function and capture the correlation of power outputs among multiple wind farms. A large number of wind power scenarios are then generated and the imprecise Dirichlet model (IDM) is applied to derive the boundaries of wind power generation, which helps to construct a more practical polyhedron uncertainty set. Moreover, due to the correlation of adjacent wind farms, the auxiliary variables which determine the fluctuation of wind power have a synchronous trend. Here, the synchronous characteristic is introduced to the enhanced polyhedron uncertainty set by means of the synchronous volatility of the auxiliary variables in adjacent wind farms. Experimental studies are conducted out on a modified IEEE-118 bus system and the obtained scheduling solution is turned out to be superior under wind power uncertainties, which verifies the effectiveness of the proposed data-adaptive robust unit commitment model.

A Novel Hybrid Neural Network-Based Day-Ahead Wind Speed Forecasting Technique

As a dominant form of renewable energy sources with significant technical progress over the past decades, wind power is increasingly integrated into power grids. Wind is chaotic, random and irregular. For proper planning and operation of power systems with high wind power penetration, accurate wind speed forecasting is essential. In this paper, a novel hybrid Neural Network (NN)-based day-ahead (24 hour horizon) wind speed forecasting is proposed, where five hybrid neural network algorithms are evaluated. The five algorithms include Wavelet Neural Network (WNN) trained by Improved Clonal Selection Algorithm (ICSA), WNN trained by Particle Swarm Optimization (PSO), Extreme Learning Machine (ELM)-based neural network, Radial Basis Function (RBF) neural network, and Multi-Layer Perceptron (MLP) Neural Network. Single- and multi-features and their effect on the accuracy of wind speed prediction are also analyzed. The wind speed dataset used in this paper is Saskatchewan’s recorded historical wind speed data. Despite the excellent wind power potential, only 6.5% of the total electricity demand is currently supplied by wind power in Saskatchewan, Canada. This study paves the way for economical operation, planning, and optimization of Saskatchewan’s future wind power generation.

Probabilistic Estimation of Wind Generating Resources Based on the Spatio-Temporal Penetration Scenarios for Power Grid Expansions

The proportion of renewable energy generation is expanding worldwide with the goal of reducing greenhouse gas. According to the 8th Basic Plan for Long-term Electricity Supply and Demand in South Korea, South Korea reduces traditional energy generation such as nuclear and coal plants and achieves 20% (58.5GW) of renewable energy generation by 2030. Wind Generating Resources (WGRs) are affected by meteorological variables such as temperature, wind speed and wind direction. Specifically, WGRs have uncertainty and variability issues depending on temporal and spatial characteristics. In this paper, we propose the probabilistic estimation of wind generating resources based on the spatiotemporal penetration scenarios for power grid expansion. The data of WGRs are analyzed based on clustering method considering the spatiotemporal penetration scenarios, and the potential scenarios are estimated using Monte Carlo simulation by selecting a representative power distribution probability for each cluster. The proposed estimation model of WGRs will play a key role to develop the hedging strategies of investment decision on power grid expansion planning with high wind power penetrations.

Mixed Game Theory Based Coordinated Development and Planning of Wind Power, Thermal Power and Grid

In order to reduce the investment waste caused by independent planning of wind power, thermal power and power grid in high penetration wind power system, and promote wind power consumption, a new hybrid game planning method for wind fire power grid is proposed. Firstly, combined with renewable energy quota system and green certificate trading mechanism, the game relationship of generation network under high penetration rate is analyzed. Then, a two-stage planning model including master-slave game between network sources and cooperative game of wind power generation is established with grid expansion scheme and wind power capacity as decision variables, and a profit distribution method considering economic and environmental gains of both partners is proposed.

Robust Transmission Expansion Planning Based on Adaptive Uncertainty Set Optimization Under High-Penetration Wind Power Generation

Previous robust transmission expansion planning (RTEP) studies have rarely considered the important question of how large the uncertainty set should be, and hence, how the uncertainty budget can be determined objectively. This study addresses this issue by proposing a novel adaptive optimization method that optimizes the value of the uncertainty budget to minimize the size of the uncertainty set while considering the underlying risk for wind power generation (WPG) fluctuations residing outside of the proposed uncertainty set. As such, the proposed method ensures a good tradeoff between the robustness and costs of RTEP solutions. In addition, the proposed method optimizes investment strategies under forecasted WPG scenarios, while providing a security guarantee under extreme WPG scenarios. The variable-limit integral terms introduced by the proposed method are addressed in the solution process by applying the piecewise linearization approximation method combined with the quadratic Newton-Gregory interpolating polynomial technique, which allows the solution process to be cast as a mixed integer linear programming problem. The good performance and effectiveness of the proposed adaptive uncertainty set optimization method are verified by numerical results.

Evaluation of DFIGs’ Primary Frequency Regulation Capability for Power Systems with High Penetration of Wind Power

Accompanying the continuous increase in wind power penetration, the power system inertia is reduced, and the system frequency regulation performance deteriorates. Wind turbine generators are required to participate in primary frequency regulation (PFR) to support system frequency. Here, the PFR capability of the widely-used doubly-fed induction generator (DFIG) is evaluated to estimate the participation of the DFIG in system frequency control. The frequency regulation model of the DFIG is established and briefly discussed. The equivalent PFR droop coefficient is then deduced from the model using a small signal increment method to evaluate the DFIG’s PFR capability. Key factors affecting the equivalent droop coefficient are studied, and the droop control is optimized to keep the equivalent droop coefficient in the desired range. The proposed method is verified utilizing a provincial power grid model of China.

Development of HVRT and LVRT Control Strategy for PMSG-Based Wind Turbine Generators

Various challenges are acknowledged in practical cases with high wind power penetration. Fault ride-through (FRT) capability has become the most dominant grid integration requirements for the wind energy conversion system worldwide. The high voltage ride-through (HVRT) and low voltage ride-through (LVRT) performance play a vital role in the grid-friendly integration into the system. In this paper, a coordinated HVRT and LVRT control strategy is proposed to enhance the FRT capability of the permanent magnet synchronous generator (PMSG)-based wind turbine generators (WTG). A dual-mode chopper protection is developed to avoid DC-link overvoltage, and a deadband protection is proposed to prevent oscillations under edge voltage conditions. The proposed strategy can ride through different levels of voltage sags or swells and provide auxiliary dynamic reactive power support simultaneously. The performance of the proposed control scheme is validated through various comparison case tests in PSCAD/EMTDC.

Techno-economic and environmental assessment of the coordinated operation of regional grid-connected energy hubs considering high penetration of wind power

Nowadays, the high penetration of renewable energy sources (RESs) with non-uniformly distributed patterns has created unprecedented challenges for regional power systems to maintain system flexibility and reliability. These technical challenges obligate power system operators to curtail part of the produced renewable energy at various scheduling intervals. Motivated by these challenges, grid-connected energy hubs are seen as a way forward to boost system flexibility, decrease the rate of renewable power curtailment, and increase energy efficiency. However, simplified models may significantly affect the performance of the grid-connected energy hubs in practice. Hence, this paper proposes a holistic structure to determine the optimal coordinated operation of the grid-connected energy hubs and the regional power system by relying on the high penetration of wind power. In this regard, various fundamental challenges that have not yet been addressed in an integrated manner, including the CO2 emission rate and the amount of curtailed renewable energy along with total operating costs of the integrated energy system, are among the main objectives of the optimization problem. The proposed structure is developed in the form of tractable mixed-integer nonlinear programming (MINLP) problem to handle the day-ahead security-constrained unit commitment (SCUC). The information-gap decision theory (IGDT)-based robust model is used for accurate modeling of wind power uncertainty. The characteristics of the proposed IGDT-based robust SCUC model and its benefits are investigated through several technical case studies conducted on the modified 6-bus and 24-bus test systems. The simulation results validate the effectiveness and feasibility of the proposed structure. According to the obtained results for the 6-bus test system, networked energy hubs can help the system operator to reduce the total operating cost, wind power curtailment cost, and CO2 emission cost by 16.62%, 100%, and 30.44%, respectively, through utilizing up-to-date energy conversion facilities and energy storage systems as well as managing energy demands. It can be seen that the proposed strategy is a very effective step towards achieving a 100% renewable energy system.

Frequency regulation analysis of modern power systems using start-stop peak shaving and deep peak shaving under different wind power penetrations

Frequency regulation has attracted considerable attentions with the integration of large-scale renewable energy into power systems. The de-commitment of conventional units reduces the system inertia, thus causes the poor frequency performance under high wind power penetration. Start-stop of conventional units is always set in power system simulations under high wind power penetration by default. In this work, power systems with deep peak shaving are considered in frequency regulation analysis for supplement. The system parameters of modern power systems in LFC are claimed and some assumptions are made first. The variety of regulating capability of conventional units and models of frequency sensitive wind energy conversion systems (WECS) are considered under different wind power penetrations. The simulation models are then derived according to the physical meaning of these two operation modes under different wind power penetrations. The modeling process is also improved by maintaining controllers optimal in each scenario. Load disturbances and stochastic wind speed are then employed as disturbance sources in the simulation tests. Results show that frequency oscillations of power systems with deep peak shaving would increase along with the wind power penetrations. However, compared with start-stop peak shaving, deep peak shaving can strongly keep systems away from large frequency deviations. Moreover, the regulation effects between the two methods become evident with increasing wind power penetration. The results would help system managers in daily operation.

An Elitist Multi-Objective Particle Swarm Optimization Algorithm for Sustainable Dynamic Economic Emission Dispatch Integrating Wind Farms

In recent years, wind energy has been widely used as an alternative energy source as it is a clean energy with a low running cost. However, the high penetration of wind power (WP) in power networks has created major challenges due to their intermittency. In this study, an elitist multi-objective evolutionary algorithm called non-dominated sorting particle swarm optimization (NSPSO) is proposed to solve the dynamic economic emission dispatch (DEED) problem with WP. The proposed optimization technique referred to as NSPSO uses the non-dominated sorting principle to rank the non-dominated solutions. A crowding distance calculation is added at the end of all iterations of the algorithm. In this study, WP is represented by a chance-constraint which describes the probability that the power balance cannot be met. The uncertainty of WP is described by the Weibull distribution function. In this study, the chance constraint DEED problem is converted into a deterministic problem. Then, the NSPSO is applied to simultaneously minimize the total generation cost and emission of harmful gases. To proof the performance of the proposed method, the ten-unit and forty-unit systems—including wind farms—are used. Simulation results obtained by the NSPSO method are compared with other optimization techniques that were presented recently in the literature. Moreover, the impact of the penetration ratio of WP is investigated.

Environment-friendly and economical scheduling optimization for integrated energy system considering power-to-gas technology and carbon capture power plant

To mitigate global warming, CO2 emission reduction has become an urgent issue in the energy sector. In China, coal-to-gas, carbon capture and renewable energy utilization are important measures available among various low-carbon plans. However, inadequate gas supply, unclear utilization methods of captured CO2, and curtailment of excessive wind and solar power have hampered the effective implementation of the above measures. To solve this issue, this paper presents a coupling model considering power to gas (P2G) technology and carbon capture power plants (CCPP), and extends it into an integrated energy system (IES) including electricity, thermal and gas, then proposes an economic and environment-friendly scheduling model at a high wind power penetration level. Through the coupling of CCPP and P2G in IES, most of CO2 emitted by the system can be captured and sent to the P2G facility to produce synthesized gas, which provides a new idea of utilizing CO2 rather than storage. The synthetic gas can be provided to the system to reduce the external gas dependency. In addition, the simulation results also show that the ability of the system to absorb renewable energy is significantly enhanced with the presence of CCPP and P2G.

Design and Optimization of Multiple FACTS Devices for Congestion Mitigation Using Sensitivity Factor with Wind Integrated System

Power generation with load optimization is an extremely important process for better planning and successful operation of the electrical power system especially in the present scenario of deregulated electricity market conditions. To increase the generation share of renewable energy resources with existing supply system, it is imperative needed that the system should not suffer problems due to congestion, voltage stability, and security. This paper presents load balancing by minimization and optimization of variety of loads when applied to pool and hybrid market designs with the application of flexible alternative current transmission system (FACTS) devices for congestion mitigation with high penetration of wind power into the existing power generation systems. Designing and comparison of multiple FACTS devices like SSSC, STATCOM, UPFC, and IPFC have been done for optimal power flow with congestion derogation so as to ensure system voltage stability within the limits. The impact of FACTS devices for high level of wind penetration with (Load index) Sensitivity Factor is also implemented for load optimization using optimal power flow to increase power flow with congestion mitigation for the wind-integrated system.

Emergency wind power plant re‐dispatching against transmission system cascading failures using reverse tracking of line power flow

Due to high wind power penetration into power system, synchronous generators may no longer be the dominant generation, which implicitly requires participation of wind power plants (WPPs) in the load-frequency control (LFC). Frequency, a common variable throughout the entire power system, is the key variable for LFC, which causes equal contribution of all distant and nearby WPPs in LFC. Power transfer from distant WPPs to the event location may overload the middle transmission lines leading to cascading failures. This study proposes an online dispatch rescheduling algorithm for WPPs participating in the LFC task to prevent over loading of transmission lines and hence cascading failures following severe frequency contingencies. The WPP dispatch limits are calculated based on line ampacity for each generation unit participating in the LFC task. Numerical simulations carried out in DigSilent PowerFactory on 39 bus IEEE standard test system, demonstrates the efficiency of suggested online dispatch rescheduling technique for keeping the loading rate of transmission lines, bus voltages and system frequency in range.

Quantifying accommodated domain of wind power for flexible look-ahead unit commitment

Properly scheduling flexible regulation resources plays a critical role in reliable operation of the power systems with high penetration of wind power. However, it remains an open question as to how to decide an operation guideline for this system to avoid the security violation and shortage of flexible ramping capacities (FRC). Amongst, it is crucial to determine the wind power injections that the system can accommodate by carefully considering FRC requirement from the whole scheduling interval. In this paper, the concept of accommodated domain of wind power (ADWP) is proposed as a metric for quantifying flexibility and an operational guideline. On this basis, two approaches for flexible look-ahead unit commitment (LAUC) are presented: Three-stage interval optimization approach, by which the largest ADWP is obtained and its corresponding operating cost is also optimized; and scenario-based stochastic optimization approach is used to minimize the overall cost, so as to obtain the most economical ADWP. Test results of IEEE 30-bus and IEEE 118-bus systems show that the proposed approaches for LAUC can effectively handle the ramping requirements and reduce the overall cost.

Static voltage stability margin calculation of power systems with high wind power penetration based on the interval optimisation method

Calculation of the static voltage stability margin (SVSM) of a power system with high wind-power penetration requires consideration of the uncertain fluctuation of wind farms' (WFs') output. Using interval numbers to describe the uncertain WF output fluctuation and based on the interval optimisation theory, a new SVSM interval calculation method is proposed. The method establishes two bi-level optimal power flow (OPF) models to calculate the SVSM interval, including a min–min model for the upper bound and a max–min model for the lower bound. Through the dual theory of convex programming, the max–min model is transformed into a max–max model, which is solved by transforming it into a one-layer optimisation model. Using correlation angles to describe the correlation of different WF output intervals and using linear transformation to decorrelate them into independent intervals, two bi-level OPF models of calculating the SVSM interval considering different WFs' correlation are established. Take the IEEE-39 bus system and an actual 964-bus provincial power grid as examples, compared with the Monte-Carlo method and the continuous power flow and affine interval integrated method, the results indicate the proposed method obtains more accurate SVSM interval and has better calculation efficiency.