High Wind Penetration Levels Research Articles

Look-Ahead Rolling Economic Dispatch Approach for Wind-Thermal-Bundled Power System Considering Dynamic Ramping and Flexible Load Transfer Strategy

With a wind-thermal-bundled power system (WTBPS) under high wind penetration levels, the sharp power fluctuations of tie-lines for interconnected grids trigger a significant challenge of security-constrained power system operation. Smoothing power fluctuations with economic dispatch is widely concerned against this challenge. In this paper, an appropriate look-ahead economic dispatch framework for WTBPS considering the variable ramp rate of retrofitted coal-fired units and the flexible load transfer strategy (LTS) in high voltage distribution networks (HVDNs) is proposed. To cope with this issue, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</i> ) we derive a new family of tightened ramping constraints of retrofitted coal-fired units in the linear and second-order conic (SOC) forms, respectively. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ii</i> ) Using graph characterization of typical HVDNs, the simplified voltage-constrained LTS via topological structures can be developed. This proposed look-ahead economic dispatch model is cast as a mixed-integer second-order cone programming (MISOCP) problem, which can be reformulated by Multi-cut Generalized Benders Decomposition (MGBD). This MGBD enables multiple sub-problems can be solved in parallel and accelerates the solving process. Finally, simulation results of a large-scale practical system validate the computational accuracy and efficiency of the proposed approach.

A frequency-responsive power-smoothing scheme of a doubly-fed induction generator for enhancing the energy-absorbing capability

Continuous wind speed variations fluctuate the active power of a wind turbine generator (WTG), thereby causing grid frequency fluctuations. Difficulty arises in alleviating the frequency fluctuations during normal operation, if WTGs continue to operate maximum power point tracking even for a high wind penetration level. This paper proposes a novel frequency-responsive power-smoothing scheme for a doubly-fed induction generator (DFIG) that can maintain the frequency deviations within a narrow range during normal operation of a power grid. To decrease the frequency in the overfrequency section, the proposed scheme decreases the DFIG active power, thereby absorbing energy into the rotating masses of a DFIG. To increase the frequency in the underfrequency section, the proposed scheme increases the active power, thereby releasing energy from the rotating masses. In the medium and high rotor speed regions, to improve the frequency-regulating capability, the proposed control gain increases as a fourth-order polynomial of the rotor speed. To avoid overdeceleration in the low rotor speed region, the control gain decreases as a sixth-order polynomial of the rotor speed as the rotor speed decreases. The simulation results clearly demonstrate that the proposed scheme significantly mitigates the frequency fluctuations under various wind conditions even in high wind penetration levels.

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.

High-Resolution Electricity Spot Price Forecast for the Danish Power Market

Energy markets with a high penetration of renewables are more likely to be challenged by price variations or volatility, which is partly due to the stochastic nature of renewable energy. The Danish electricity market (DK1) is a great example of such a market, as 49% of the power production in DK1 is based on wind power, conclusively challenging the electricity spot price forecast for the Danish power market. The energy industry and academia have tried to find the best practices for spot price forecasting in Denmark, by introducing everything from linear models to sophisticated machine-learning approaches. This paper presents a linear model for price forecasting—based on electricity consumption, thermal power production, wind production and previous electricity prices—to estimate long-term electricity prices in electricity markets with a high wind penetration levels, to help utilities and asset owners to develop risk management strategies and for asset valuation.

Steady State and Transient Analysis of FSIG and DFIG Integration to Grid for Different Penetration Levels using VSC-HVDC

Among all the Renewable Energy Sources Wind energy is the fastest growing energy source over the last decade mainly due to crucial developments of technology in wind energy. Nowadays, the penetration of wind energy is increasing in many countries in the world including India. The power system stability with large penetration of wind power is a concern for many electrical utilities. The common technical issues with increased penetration of wind energy are voltage and reactive power control, frequency control and Low Voltage Ride Through (LVRT) capability. The VSC-HVDC system with its benefit of independent control of active and reactive power promises to enhance the system stability at high penetration levels. The maximum wind penetration levels in to the grid is analysed for Fixed Speed Induction Generator (FSIG) &amp; Doubly Fed Induction Generator (DFIG). The penetration levels are further enhanced by considering the evacuation of wind power with VSC-HVDC system without losing system stability. Different controllers for VSC-HVDC system are used to improve the stability and LVRT capability. Standard Benchmark System is considered, and the simulations are performed by using power system simulation software SIMPOW. Results shows that wind power evacuated through VSC-HVDC system has better stability and LVRT Capability compared to AC system at high wind penetration levels.

Facilitating high levels of wind penetration in a smart grid through the optimal utilization of battery storage in microgrids: An analysis of the trade-offs between economic performance and wind generation facilitation

The aim of this paper was to investigate the trade-offs that can be achieved between optimizing the electricity costs of a building integrated microgrid, while simultaneously facilitating high levels of wind penetration in a smart grid. This study applied multi-objective optimization to obtain a daily charge and discharge schedule of a battery bank, which was used to store electricity from the microgrid and smart grid and could also provide electricity to the building and smart grid. Multi-objective optimization was employed due to the independent objectives of minimizing building operating cost and maximizing the facilitation of wind energy from the smart grid. The trade-offs between the two objectives were simulated, evaluated and analyzed. A priority weighting factor (α) was applied to each objective. The purpose of α was to vary the importance of each objective relative to the other in an inversely proportional manner. This enabled the algorithm to optimize the battery operating schedule for the economic performance of the microgrid, the facilitation of wind generation from the smart grid or for trade-offs in between. The results present a comprehensive evaluation of 96 scenarios with varying daily weather conditions, building electricity demand, electricity pricing, microgrid output and wind penetration from the smart grid. A multi-objective optimization approach was then applied for each of the 96 scenarios with 11 α values to determine optimal trade-offs in these scenarios. Generally for the 96 scenarios analyzed, when the α value was 20% or higher, the amount of extra wind generation facilitation obtained was negligible while microgrid operating costs continued to increase. The results showed that when changing from an α value of 0% to an α value of 20%, there was a large increase in wind generation facilitation compared to the corresponding increase in cost, with wind generation facilitation increasing from its minimum value to within 89% of its maximum value (10.7% to 14.3% of facilitated wind generation). The corresponding building cost increased from its minimum value to within 13% of its maximum value (€1.14/day to €1.37/day). This produced a cost of approximately €0.06 for every 1% increase in wind generation facilitation. In comparison to this, changing from an α value of 20% to an α value of 100% implied a cost of approximately €3.64 for every 1% increase in wind generation facilitation. These results indicated that smart grids with large percentages of wind penetration may be substantially aided by utilizing the storage capacity of building integrated microgrids for a relatively low monetary cost.

The effect of Demand Response and wind generation on electricity investment and operation

Abstract We present a novel method of determining the contribution of load-shifting Demand Response (DR) to energy and reserve markets. We model DR in an Mixed Complementarity Problem (MCP) framework with high levels of wind penetration. Investment, exit and operational decisions are optimized simultaneously. We examine the potential for DR to participate in both energy and reserve markets. DR participation in the energy market reduces costs and prices and gives rise to lower equilibrium levels of investment in conventional generation. DR and wind generation are strongly complementary, due to the ability of DR to mitigate against the variability of wind generation, with the highest reduction of consumer costs seen at high levels of wind penetration. The total impact of DR is highly dependent on specific system characteristics.

Modelling wind power spatial-temporal correlation in multi-interval optimal power flow: A sparse correlation matrix approach

The significantly increasing deployment of wind power necessitates that system operation considers the spatial-temporal correlation of power forecast from different wind power plants. How to model this spatial-temporal correlation in the actual system dispatch is challenging. In this paper, a sparse correlation matrix is utilized to efficiently model the spatial-temporal correlation of wind power forecast in the generation dispatch model. A novel, adjustable, and distributionally-robust chance-constrained multi-interval optimal power flow (ADRCC-MIOPF) model is proposed to obtain reliable economic dispatch (ED) solutions. The spatial-temporal correlation of wind power plants power forecasts is represented by the sparse correlation covariance matrix obtained from historical, time series wind power forecast error data. The chance constraints in the ADRCC-MIOPF model are transformed into a set of second-order-cone (SOC) constraints in which an adjustable coefficient in the chance constraints controls the robustness of the ADRCC-MIOPF model to the wind power forecast errors distribution. Case studies performed on the PJM 5-bus system and IEEE 118-bus system verify the proposed method to improve the system security and reduce the cost especially under the high wind penetration levels. All the cases can be solved within several minutes for both the small and large cases which validates the efficiency of the proposed sparse matrix model. In addition, considering the spatial-temporal correlation of wind power forecast and the distributional robustness of wind power forecast error leads to a more reliable economic dispatch with lower system violations.

Stochastic Transmission Impedance Control for Enhanced Wind Energy Integration

In recent years, renewable energy supply in the U.S. has increased dramatically, among which wind energy has experienced the largest growth. Since the grid is not designed to handle high levels of intermittent generation, involuntary wind curtailment has been implemented commonly in many regional transmission organizations. Transmission congestion is one of the main barriers, which avoids full delivery of the produced wind energy. An obvious but extremely costly solution to this problem is building new transmission lines. Alternatively, transfer capability over the existing transmission system can be enhanced using variable-impedance flexible ac transmission system (FACTS) devices. This paper proposes a two-stage stochastic optimization model for integrating FACTS into power system operation for a system with high levels of wind penetration. The first stage identifies an optimal base dispatch, while the second stage finds the optimal deployment of FACTS flexibilities and operational reserves for each wind scenario. Using this model, the paper studies the impacts of FACTS operation on wind energy integration. The simulation studies on an RTS-96 system verify the effectiveness of the proposed method in reducing the operation cost as well as wind curtailment. The proposed model is also computationally-efficient, as a linear FACTS model is employed.

The Future of the European Electricity Grid Is Bright: Cost Minimizing Optimization Shows Solar with Storage as Dominant Technologies to Meet European Emissions Targets to 2050

The European roadmap for the power sector dictates an 80–95% cut of existing levels of carbon dioxide emissions is needed by the year 2050 to meet climate goals. This article describes results from a linear cost optimization investment model, ELIN, coupled with a solar technology model, Distributed Concentrating Solar Combined Heat and Power (DCS-CHP), using published investment costs for a comprehensive suite of renewable and conventional electricity generation technologies, to compare possible scenarios for the future electricity grid. The results of these model runs and sensitivity analyses indicate that: (1) solar photovoltaics (PV) with battery storage will likely play a very large role in meeting European targets; (2) concentrating solar power (CSP) with thermal energy storage is at a slight economic disadvantage with respect to PV to compete economically; (3) the economic potential of wind power is only comparable with solar PV if high wind penetration levels are allowed in the best wind sites in Europe; and (4) carbon capture and nuclear technologies are unlikely to compete economically with renewable technologies in creating a low-carbon future grid.

Chance-constrained Scheduling of Variable Generation and Energy Storage in a Multi-Timescale Framework

This paper presents a hybrid stochastic deterministic multi-timescale scheduling (SDMS) approach for generation scheduling of a power grid. SDMS considers flexible resource options including conventional generation flexibility in a chance-constrained day-ahead scheduling optimization (DASO). The prime objective of the DASO is the minimization of the daily production cost in power systems with high penetration scenarios of variable generation. Furthermore, energy storage is scheduled in an hourly-ahead deterministic real-time scheduling optimization (RTSO). DASO simulation results are used as the base starting-point values in the hour-ahead online rolling RTSO with a 15-minute time interval. RTSO considers energy storage as another source of grid flexibility, to balance out the deviation between predicted and actual net load demand values. Numerical simulations, on the IEEE RTS test system with high wind penetration levels, indicate the effectiveness of the proposed SDMS framework for managing the grid flexibility to meet the net load demand, in both day-ahead and real-time timescales. Results also highlight the adequacy of the framework to adjust the scheduling, in real-time, to cope with large prediction errors of wind forecasting.

Spatial smoothing of onshore wind: Implications for strategic development in Scotland

High levels of wind penetration is widely accepted as presenting problems for energy security. With increasing wind deployment this issue is well recognised in Scotland. Spatial smoothing of generation is seen as one method to enhance energy security in a high wind penetration system. This requires wind farms to be developed in a way to take advantage of this smoothing; however, this is not part of the UK/Scottish government wind deployment strategy – which is instead developer led.This research seeks to contribute to a strategic approach to wind development in Scotland, taking into account spatial smoothing – which is shown in this study to be statistically significant within Scotland. Providing quantification of which pre-existing areas of large-scale wind development in Scotland should be the focus of further development and which are of least benefit. Wind farms in southern Scotland offer least in terms of energy security, due to over-concentration of deployment in this area, further development here should be in part considered in terms of export value, rather than utilization within Scotland. The two island areas modelled are shown to have high spatial smoothing value. This work should help inform current political discourse over grid connections to these areas.

Characterisation of long‐term voltage stability with variable‐speed wind power generation

Voltage stability in general is of paramount importance with increasing penetration levels of variable-speed wind power generators (VSWGs) in power systems. Limited knowledge exists considering the impact of VSWGs on long-term voltage stability (LTVS) of power systems, focusing on doubly fed induction generators and full-converter wind generators. This paper presents the results of a comprehensive study on the impact of VSWGs on LTVS. Integration of wind generators while operating the existing synchronous generators improves the LTVS. However, it is unlikely that power systems will retain all existing synchronous generators operating, with high wind penetration levels. Therefore, this study compares the capability of the synchronous generators and VSWGs on LTVS by considering the dynamic reactive power capabilities. The significance of overload capability of synchronous generators on LTVS is highlighted. It is also illustrated that integrating wind farms at remote and local locations from load centres has distinct impacts on LTVS. Replacement of synchronous generators located in close proximity to load centres has a detrimental effect on LTVS. Furthermore, this study demonstrates the impact of different wind generator loading levels on LTVS. The study outcomes highlight several distinct factors which influence the LTVS of power systems with high wind penetration levels.

Integration of power-to-hydrogen in day-ahead security-constrained unit commitment with high wind penetration

The increasing integration of variable wind generation has aggravated the imbalance between electricity supply and demand. Power-to-hydrogen (P2H) is a promising solution to balance supply and demand in a variable power grid, in which excess wind power is converted into hydrogen via electrolysis and stored for later use. In this study, an energy hub (EH) with both a P2H facility (electrolyzer) and a gas-to-power (G2P) facility (hydrogen gas turbine) is proposed to accommodate a high penetration of wind power. The EH is modeled and integrated into a security-constrained unit commitment (SCUC) problem, and this optimization problem is solved by a mixed-integer linear programming (MILP) method with the Benders decomposition technique. Case studies are presented to validate the proposed model and elaborate on the technological potential of integrating P2H into a power system with a high level of wind penetration (HWP).

Adaptive Neuro-Fuzzy Synchronization in Isolated Power Systems with High Wind Penetration

Isolated power systems (IPSs) worldwide are traditionally powered by diesel generators that are very expensive to run and produce harmful emissions. In order to mitigate these problems, wind turbines are being introduced into existing IPSs. Although this integration has been reasonably effective at reducing running costs and emissions, high levels of wind penetration cause large system frequency variations, resulting in a prolonged synchronization process for newly dispatched diesel generators. Long synchronization can compromise the stability of a small IPS. This paper examines the diesel synchronization problem using a real IPS as a case study and offers a solution by introducing the concept of predictive synchronization based on adaptive neuro-fuzzy systems. Simulation results demonstrate a significant reduction in diesel generator synchronization times.

Stepwise inertial control of a wind turbine generator to minimize a second frequency dip

AbstractWind turbine generators (WTGs) in power systems with high wind penetration levels are encouraged or forced to participate in frequency control. A stepwise inertial control (SIC) scheme instantly increases WTG output to arrest the frequency drop for a preset period upon detecting a disturbance. After arresting the frequency drop, the output is rapidly reduced to recover the rotor speed. The reduction could cause a power deficit to the power system, which in turn results in a second frequency dip (SFD). This paper proposes an SIC scheme that can improve the frequency nadir (FN) and maximum rate of change of frequency (ROCOF) while minimizing an SFD. To achieve this, a reference function is separately defined prior to and after the FN. To improve the FN and maximum ROCOF, the output is instantly increased by adding a constant, which is proportional to the rotor speed, and maintaining it until the FN is reached. To minimize an SFD, the output is slowly reduced with the rotor speed. This reduction ensu...

Future stability challenges for the UK network with high wind penetration levels

Offshore wind plant such as variable speed wind turbines (DFIG) will play an increasingly important role in future decades if ever-stringent requirements of energy security and low carbon emissions are to be met. Although some analysis of the impact of DFIG on system stability has previously been reported, none of it is based on a large network representing a real system, or the large network is simply not publicly available. This paper describes one such suitable equivalent dynamic network for stability studies based on the whole UK transmission system. The methodology for appropriate control system design and adjustment of the parameters under different dispatch conditions is presented. The network model is subsequently updated according to various National Grid future energy scenarios where DFIG models are appropriately added and distributed. Two important aspects contributing to future system stability are studied in detail, namely maximum value of the rate of change of frequency and transient stability. A number of detailed cases studies under varying wind penetration levels are presented which quantify the impact of key influencing factors such as the size of the largest generating unit for n-1 contingency, amount of primary system response, frequency dependency of load, and others. The study concludes that none of the individual factors can provide a complete solution and that careful cost benefit analysis is needed to determine the proper mix of services and reinforcements needed in the future.

Adaptive Robust Optimization With Dynamic Uncertainty Sets for Multi-Period Economic Dispatch Under Significant Wind

The exceptional benefits of wind power as an environmentally responsible renewable energy resource have led to an increasing penetration of wind energy in today's power systems. This trend has started to reshape the paradigms of power system operations, as dealing with uncertainty caused by the highly intermittent and uncertain wind power becomes a significant issue. Motivated by this, we present a new framework using adaptive robust optimization for the economic dispatch of power systems with high level of wind penetration. In particular, we propose an adaptive robust optimization model for multi-period economic dispatch, and introduce the concept of dynamic uncertainty sets and methods to construct such sets to model temporal and spatial correlations of uncertainty. We also develop a simulation platform which combines the proposed robust economic dispatch model with statistical prediction tools in a rolling horizon framework. We have conducted extensive computational experiments on this platform using real wind data. The results are promising and demonstrate the benefits of our approach in terms of cost and reliability over existing robust optimization models as well as recent look-ahead dispatch models.

Capacity Adequacy and Revenue Sufficiency in Electricity Markets With Wind Power

We present a computationally efficient mixed-integer program (MIP) that determines optimal generator expansion decisions, as well as periodic unit commitment and dispatch. The model is applied to analyze the impact of increasing wind power capacity on the optimal generation mix and the profitability of thermal generators. In a case study, we find that increasing wind penetration reduces energy prices while the prices for operating reserves increase. Moreover, scarcity pricing for operating reserves through reserve shortfall penalties significantly impacts the prices and profitability of thermal generators. Without scarcity pricing, no thermal units are profitable, however scarcity pricing can ensure profitability for peaking units at high wind penetration levels. Capacity payments can also ensure profitability, but the payments required for baseload units to break even increase with the amount of wind power. The results indicate that baseload units are most likely to experience revenue sufficiency problems when wind penetration increases and new baseload units are only developed when natural gas prices are high and wind penetration is low.

Investigating the effect of high level of wind penetration on voltage stability by quasi-static time-domain simulation (QSTDS)

In this paper, the impact of increasing in wind energy penetration level on voltage stability is studied by utilizing quasi-static time domain simulation (QSTDS). Connecting a squirrel cage induction generator (SCIG)-based wind farm has an undesirable effect on the voltage stability in power system, especially when this connection is accompanied with increase in the level of wind generation. Due to the asynchronous operation of induction machine, the increment of wind power generation will be possible only by absorption of more reactive power. Increasing in the power reactive consumption of induction generator leads to reduction of voltage in the bus of common connection between wind farm and the grid. Under these conditions, if the reactive power absorption of wind farm is not managed efficiently it would result in voltage instability of the grid. In this paper, it is shown that using static Var compensator (SVC) and static synchronous compensator (STATCOM) has improved the voltage stability of the system and leads to desirable performance of the wind farms.