Wind Integrated Power System Research Articles

The Economic Dispatch of Wind Integrated Power System based on an Improved Differential Evolution Algorithm

Background: As more and more renewable energy such as wind energy is connected to the power grid, the static economic dispatch in the past cannot meet its needs, so the dynamic economic dispatch of the power grid is imperative. Methods: Hence, in this paper, we proposed an Improved Differential Evolution algorithm (IDE) based on Differential Evolution algorithm (DE) and Artificial Bee Colony algorithm (ABC). Firstly, establish the dynamic economic dispatch model of wind integrated power system, in which we consider the power balance constraints as well as the generation limits of thermal units and wind farm. The minimum power generation costs are taken as the objectives of the model and the wind speed is considered to obey the Weibull distribution. After sampling from the probability distribution, the wind speed sample is converted into wind power. Secondly, we proposed the IDE algorithm which adds the local search and global search thoughts of ABC algorithm. The algorithm provides more local search opportunities for individuals with better evolution performance according to the thought of artificial bee colony algorithm to reduce the population size and improve the search performance. Results: Finally, simulations are performed by the IEEE-30 bus example containing 6 generations. By comparing the IDE with the other optimization model like ABC, DE, Particle Swarm Optimization (PSO), the experimental results show that obtained optimal objective function value and power loss are smaller than the other algorithms while the time-consuming difference is minor. The validity of the proposed method and model is also demonstrated. Conclusion: The validity of the proposed method and the proposed dispatch model is also demonstrated. The paper also provides a reference for economic dispatch integrated with wind power at the same time.

Coordinated Scheduling for Improving Uncertain Wind Power Adsorption in Electric Vehicles—Wind Integrated Power Systems by Multiobjective Optimization Approach

Electric vehicles (EVs) and renewable energy, such as wind power, have been widely utilized to meet the sustainable development of our society. To this end, research articles on the operation performance of the EV-wind integrated power system are important. This article proposes a coordinated scheduling model, which aims to improve the wind power adsorption while considering the energy conservation and emission reduction of thermal generators. Besides, to conduct a comprehensive investigation among these multiple objectives, we formulate the coordinated scheduling model as a multiobjective optimization problem. Then, a multiobjective optimization algorithm based on a parameter adaptive differential evolution is proposed to solve this problem. Simulation results based on a modified Midwestern USA power system verify that the proposed scheduling model could reveal the relationship among multiple objectives, and the integration of EVs can improve the wind power adsorption and cost effectiveness of the power system.

Multi-objective dynamic economic emission dispatch based on electric vehicles and wind power integrated system using differential evolution algorithm

Electric vehicles (EVs) are currently the most popular green transportation. Wind power has received widespread attention as a kind of renewable energy source. Their rapid development has brought new challenges for the power grid. However, the technology of vehicle to grid (V2G) can realize the peak shaving of the power grid, which is considered to be an effective method to promote the integration of EVs and wind power. Therefore, in this paper, a novel integrated framework of EVs and wind farms (WEV) is proposed to use the EVs charging and discharging to smooth the wind power penalty cost that caused by overestimated and underestimated of available wind power. While a new multi-objective dynamic economic emission dispatching model based on the WEV system (WE_DEED) is developed to consider both emission and total cost objectives. In order to solve the complex constrained WE_DEED problem, we propose a multi-objective differential evolution algorithm with the self-adaptive parameter operator and local search operator based on non-dominant sorting (SaMODE_LS). Moreover, an effective constraint handling method is applied to deal with the constraints in WE_DEED problems. Different test systems based on 10-unit are given to demonstrate the reasonability and efficiency of the proposed model and method.

Analysis and enhancement of small‐signal stability on DFIG‐based wind integrated power system through the optimal design of linear quadratic regulator

This study analyses the dynamic behaviour of a doubly fed induction generator (DFIG)-based wind integrated power system (WIPS) resulting from a major disturbance. The effects of transient disturbance on WIPS are examined without and with a controller in terms of performance and stability of the system. To enhance the performance of WIPS after a sudden disturbance, an optimally designed linear quadratic regulator (LQR) controller is applied to the system. The wind energy system is described in state-space representation, whose states and outputs are taken as feedback to the controller for improving their dynamic response. An artificial bee colony (ABC)-based swarm optimisation technique is used to evaluate the optimal weighting matrices of the LQR controller in parallel with minimising the performance index and dynamic response characteristics of the system. The effectiveness of the proposed ABC–LQR controller in WIPS is verified by comparing their simulation and numerical results with standard proportional–integral and LQR controllers. It indicates that the proposed controller provides better enhancement of dynamic response as compared with other controllers in terms of performance index and dynamic response characteristics. Moreover, the robustness and stability of various system configurations are tested by the eigenvalue analysis.

Unit commitment of wind integrated power system considering optimal scheduling of reserve capacity

There are multiple uncertainties in the power system with wind farms, such as wind power output, load and forced outage of units, which lead to consider the spinning reserve capacity in unit commitment, which undoubtedly increases the difficulty of problem solving. In order to solve this problem, the fuzzy parameters of wind power output and load are obtained by using the error’s fuzzy characteristics, and the mathematical model of generating unit combination is established to optimize the generator output and spinning reserve simultaneously by using the chance constraint, and the model is solved by using intelligent algorithm. The model fully analyses the cost difference of different units providing spinning reserve and the economic benefit of spinning reserve, aiming at minimizing the difference between the cost of generating reserve and the economic benefit of reserve, so as to maximize the overall economic benefit of the system. The feasibility and validity of the proposed model are verified by a 10-unit system with wind farms. The analysis shows that the model can reasonably consider reserve decision-making in unit commitment to deal with uncertainties in power system.

Coherency Identification for Wind-Integrated Power System Using Virtual Synchronous Motion Equation

This paper proposes a new model-based coherency identification method based on the virtual synchronous motion equation (VSME) of the doubly-fed induction generator (DFIG). The latter is derived by taking into account both the dynamic characteristics of the phase-locked loop (PLL) and the active power control model. The proposed VSME reveals the synchronization mechanism of the “virtual angle” and “internal voltage vector” for a wind-turbine-driven generator in mathematics and physics. This significant result allows us to treat the DFIG as a “synchronous machine” with appropriately derived equivalent inertia constant, phase-locked angle and synchronizing torque. Thanks to this formula, the slow-coherency aggregate model for the wind-integrated power system can be easily constructed. It further enables us to resort to the K-Means algorithm to identify coherent generators and investigate the impacts of control parameters on coherency properties. Comparison results with alternative measurement-based methods on the modified IEEE 39-bus and IEEE 118-bus systems demonstrate the effectiveness of the proposed method.

Frequency-Coupled Impedance Modeling and Resonance Analysis of DFIG-Based Offshore Wind Farm With HVDC Connection

Motivated by recent years' resonance incidents in wind-integrated power systems, this paper investigates the resonance-induced harmonic distortion and stability issues in doubly fed induction generator (DFIG)-based offshore wind farm (OWF) with high-voltage direct current (HVDC) grid connection. To accurately capture the dynamic characteristics of DFIG-based wind farm, a comprehensive impedance modelling considering the detailed PI control loop and DC dynamics of wind turbine as well as the cable connections of the medium-voltage (MV) collector system is conducted. Through stepwise simulation verifications, aggregated modelling of MV collector system is proved to be suitable for wideband resonance analysis. On this basis, the resonance analysis regarding grid topology change and controller parameter variation is conducted and the impact of frequency coupling on subsynchronous resonance (SSR), middle- and high-frequency resonances is analyzed using the aggregated models derived from a practical HVDC connected DFIG-based OWF. The strength or degree of the frequency coupling between the sequence impedances of wind farm, which is induced by the asymmetrical converter control of wind turbines, is found to be dependent on the impedances of all the components of the system. Moreover, case studies are conducted to demonstrate the importance of including the frequency coupling in SSR stability assessment. Simulations in MATLAB / Simulink validate the modelling and resonance analysis.

Deep Reinforcement Learning for Cybersecurity Assessment of Wind Integrated Power Systems

The integration of renewable energy sources (RES) is rapidly increasing in electric power systems (EPS). While the inclusion of intermittent RES coupled with the wide-scale deployment of communication and sensing devices is important towards a fully smart grid, it has also expanded the cyber-threat landscape, effectively making power systems vulnerable to cyberattacks. This article proposes a cybersecurity assessment approach designed to assess the cyberphysical security of EPS. The work takes into consideration the intermittent generation of RES, vulnerabilities introduced by microprocessor-based electronic information and operational technology (IT/OT) devices, and contingency analysis results. The proposed approach utilizes deep reinforcement learning (DRL) and an adapted Common Vulnerability Scoring System (CVSS) score tailored to assess vulnerabilities in EPS in order to identify the optimal attack transition policy based on $N-2$ contingency results, i.e., the simultaneous failure of two system elements. The effectiveness of the work is validated via numerical and real-time simulation experiments performed on literature-based power grid test cases. The results demonstrate how the proposed method based on deep $Q$ -network ($\text{D}Q\text{N}$ ) performs closely to a graph-search approach in terms of the number of transitions needed to find the optimal attack policy, without the need for full observation of the system. In addition, the experiments present the method's scalability by showcasing the number of transitions needed to find the optimal attack transition policy in a large system such as the Polish 2383 bus test system. The results exhibit how the proposed approach requires one order of magnitude fewer transitions when compared to a random transition policy.

Random-Fuzzy Chance-Constrained Programming Optimal Power Flow of Wind Integrated Power Considering Voltage Stability

Considering the random and fuzzy nature of wind speed, this paper proposes a multi-objective random-fuzzy chance-constrained programming optimal power flow (OPF) for wind integrated power systems. The proposed method is based on random-fuzzy chance-constrained programming. The optimization model aims at minimizing generation cost, carbon dioxide (CO2) emission, and system functional power loss, and P-Q-V steady-state voltage stability is included in the constraints. Based on random-fuzzy chance-constrained programming, the corresponding solution process of the proposed multi-objective OPF is proposed, which is a hybrid of random-fuzzy simulation, non-dominated sorting genetic algorithm-II (NSGA-II), and fuzzy satisfaction-maximizing decision-making method. The proposed approach is simulated on the IEEE 30-bus system to provide an example of its application. The simulation results demonstrate that the proposed random-fuzzy chance-constrained programming OPF has higher security and more economy than dynamic stochastic optimal power flow (DSOPF) and dynamic fuzzy optimal power flow (DFOPF).

Data-driven Operation Risk Assessment of Wind-integrated Power Systems via Mixture Models and Importance Sampling

The increasing penetration of highly intermittent wind generation could seriously jeopardize the operation reliability of power systems and increase the risk of electricity outages. To this end, this paper proposes a novel data-driven method for operation risk assessment of wind-integrated power systems. Firstly, a new approach is presented to model the uncertainty of wind power in lead time. The proposed approach employs k-means clustering and mixture models (MMs) to construct time-dependent probability distributions of wind power. The proposed approach can also capture the complicated statistical features of wind power such as multimodality. Then, a non-sequential Monte Carlo simulation (NSMCS) technique is adopted to evaluate the operation risk indices. To improve the computation performance of NSMCS, a cross-entropy based importance sampling (CE-IS) technique is applied. The CE-IS technique is modified to include the proposed model of wind power. The method is validated on a modified IEEE 24-bus reliability test system (RTS) and a modified IEEE 3-area RTS while employing the historical data of wind generation. The simulation results verify the importance of accurate modeling of short-term uncertainty of wind power for operation risk assessment. Further case studies have been performed to analyze the impact of transmission systems on operation risk indices. The computational performance of the framework is also examined.

Energy dissipation of MMC‐HVDC based onshore wind power integration system with FB‐DBS and DCCB

With the development of high-voltage direct current (HVDC), modular multilevel converter (MMC) is seeking its application in onshore wind power integration. AC and DC faults are important issues for the wind power integration system, during which the wind generation system continuously provides wind power and the surplus power may cause overvoltage to sub-modules of MMC. This study focuses on the energy dissipation during AC and DC faults for the overhead-line MMC-HVDC system integrating large-scale wind power. A two-terminal MMC-HVDC system with permanent magnet synchronous generator based wind farm is studied. Hybrid DC circuit breakers (DCCBs) are employed to interrupt DC fault current and the method based on measuring the rate of change of DC line voltage is adopted to trip DCCBs. Also a full-bridge sub-module based dynamic braking system (FB-DBS) is implemented at the DC link to absorb the surplus wind power in case of AC or DC faults in the HVDC grid. To ride-through AC and DC faults without blocking IGBTs, the control of hybrid DCCB and the system fault ride-through strategies are properly designed. PSCAD/EMTDC simulations are shown to demonstrate theoretical analysis.

Impedance Modeling and Analysis of MMC-HVDC for Offshore Wind Farm Integration

The offshore ac side impedance model of the modular multilevel converter (MMC) based high voltage direct current (HVdc) system is essential for analyzing the interaction stability between MMC-HVdc and the offshore wind power plants. This paper develops the offshore ac side impedance model of an MMC-HVdc system for wind power integration taking the effects of offshore station, dc cable and onshore station into consideration. The dc impedance model of the onshore station is first derived which includes the effects of dual closed loop dc bus voltage control and circulating current control. Then, the dc impedance of the onshore station and dc cable impedance are used to derive the ac side impedance of the offshore station under open loop control. In addition, the influence of the dual closed loop based ac bus voltage and frequency (VF) control on the offshore ac impedance is analytically derived. As a result, the proposed model can be used to reveal the coupling between offshore offshore ac system and dc system as well as to investigate the influence of the dc system and VF controller in the offshore ac impedance of the MMC-HVdc system. Furthermore, the proposed model overcomes the deficiencies in harmonic resonance analysis of MMC-HVdc based offshore wind power integration system. The results of the simulation in PSCAD/EMTDC validate the proposed models and analyses.

Reliability modelling of compressed air energy storage for adequacy assessment of wind integrated power system

There are rising opportunities and prospects for integration of a large-scale energy storage system in the electric power system to mitigate the challenges arising from wide-spread growth in variable and uncertain sources of renewable energy generation. Compressed air energy storage (CAES) is one of the promising large-scale energy storage technologies that is being explored. This study presents a novel probabilistic framework to evaluate the reliability benefit of CAES in the wind integrated power system. The developed framework is based on a hybrid approach which is a combination of Monte Carlo simulation (MCS) based state of charge model and analytical method based reliability evaluation. An equivalent average model is developed within the hybrid framework to assess the adequacy benefit of CAES operated to seasonally accumulate and transfer energy. This hybrid method brings together advantages of both MCS and analytical method in reliability evaluation resulting in a comprehensive and computationally efficient framework. A detailed Markov model for CAES component reliability is developed and integrated into the hybrid framework. Case studies are conducted to demonstrate the effectiveness of the proposed framework. The results presented quantify the reliability benefit from diurnal and seasonal energy management in CAES in addition to the environmental and financial benefits.

Flexible Operation of Retrofitted Coal-Fired Power Plants to Reduce Wind Curtailment Considering Thermal Energy Storage

The rapid expansion of wind power has triggered significant wind curtailment because the power system lacks flexibility to deal with the uncertainty and variability of wind power. The operational flexibility of coal-fired power plants is limited by the minimum stable firing rate in the boiler. Steam extraction and thermal energy storage could enable power output adjustment without changing the firing rate in the boiler. Thus, retrofitting existing coal-fired power plants with steam extraction and thermal energy storage is a promising option to accommodate the high penetration of wind power in the power system, especially in coal-dominated power system. This study investigated the operational flexibility of coal-fired power plants retrofitted with steam extraction and thermal energy storage. First, a linear operation model is proposed for retrofitted coal-fired power plants considering new characteristics and technical constraints. Second, a simulation framework based on stochastic unit commitment and rolling economic dispatch is developed to explore the benefits of steam extraction and thermal energy storage in wind-integrated power systems. The forecasted wind power data is used in stochastic unit commitment to evaluate start-up and shut-down cost, while real wind power data is adopted in rolling economic dispatch to calculate the actual production cost. The simulation results on the modified IEEE 24-bus system demonstrate the effectiveness of retrofitting coal-fired power plants with steam extraction and thermal energy storage for mitigating wind curtailment.

Robust LFC Strategy for Wind Integrated Time-Delay Power System Using EID Compensation

This paper presents an active disturbance rejection control (ADRC) technique for load frequency control of a wind integrated power system when communication delays are considered. To improve the stability of frequency control, equivalent input disturbances (EID) compensation is used to eliminate the influence of the load variation. In wind integrated power systems, two area controllers are designed to guarantee the stability of the overall closed-loop system. First, a simplified frequency response model of the wind integrated time-delay power system was established. Then the state-space model of the closed-loop system was built by employing state observers. The system stability conditions and controller parameters can be solved by some linear matrix inequalities (LMIs) forms. Finally, the case studies were tested using MATLAB/SIMULINK software and the simulation results show its robustness and effectiveness to maintain power-system stability.

Overview of mechanism and mitigation measures on multi-frequency oscillation caused by large-scale integration of wind power

In recent years, the large-scale integration of renewable energy sources represented by wind power and the widespread application of power electronic devices in power systems have led to the emergence of multi-frequency oscillation problems covering multiple frequency segments, which seriously threaten system stability and restrict the accommodation of renewable energy. The oscillation problems related to renewable energy integration have become one of the most popular topics in the field of wind power integration and power system stability research. It has received extensive attention from both academia and industries with many promising research results achieved to date. This paper first analyzes several typical multi-frequency oscillation events caused by large-scale wind power integration in domestic and foreign projects, then studies the multi-frequency oscillation problems, including wind turbine's shafting torsional oscillation, sub/super-synchronous oscillation and high frequency resonance. The state of the art is systematically summarized from the aspects of oscillation mechanism, analysis methods and mitigation measures, and the future research directions are explored.

Reliability and economic assessment of compressed air energy storage in transmission constrained wind integrated power system

• Benefits of storage are largely dependent on the operation strategy. • The reliability and environmental benefit obtained from storage often contradict with the objective of profit maximization. • A co-located storage with wind farms can act as an alternative to wind diversity and transmission upgrade. • Regulatory structures should develop a market and incentive mechanism for the storage to support renewable integration. Bulk-scale energy storage systems (ESS) such as compressed air energy storage (CAES) are considered as viable options to alleviate problems associated with the variability and uncertainty of wind power. The operation strategy of ESS is dictated by the existing market and regulatory structure, which in turn impacts the overall system performance in terms of quality, reliability, efficiency and environmental commitments. A CAES can be operated either independently to maximize the profit in the existing market or in coordination with wind power resources to collectively benefit from the markets while maximizing the usage of renewable energy. This work explores feasible applications and benefits of CAES in a transmission-constrained wind integrated power system. Comprehensive models for wind and CAES operating strategies are developed and potential benefits of CAES to systems are quantified in terms of their contributions to system reliability, efficiency, and environmental objectives. The results presented show the trade-off among different aspects of potential benefits obtained from CAES. The method presented, and the results analyzed can provide valuable input to utilities and policymakers for formulating effective regulatory structures to integrate bulk-scale storage to efficiently support the imminent growth of renewable energy while maintaining reliable supply to electricity consumers.

Integrated Disturbance Response Modeling of Wind-Integrated Power Systems to Quantify the Operational Reliability Benefits of Flywheel Energy Storage

Rapid growth of renewable power penetration has exposed modern power systems to high operating risks, due to intermittency and uncertainty inherent in such energy sources. It is therefore essential to assess the associated risks and explore potential resources to mitigate these risks. This paper presents a novel approach for response risk evaluation of wind-integrated power system. The proposed approach utilizes a probabilistic integrated disturbance model and introduces a new comparative risk index designated as the Response Risk Multiplication Factor to quantify the impact of increasing penetration of wind power and the contribution of flywheel energy storage system (FESS) on the power system operational reliability. The developed model incorporates the wind-power uncertainty, the specific charge/discharge, storage performance and failure characteristics of FESS and embeds the posterior probability approach to utilize the known information on time of day and FESS SOC. The developed model is applied to the IEEE Reliability Test System to illustrate its usability in assessment of the impact on power system operating risk due to large operating penetration of wind power and effectiveness of FESS in risk mitigation.

Coordinated tuning of controller-parameters using symbiotic organisms search algorithm for frequency regulation of multi-area wind integrated power system

Presently, the integration of renewable energy into existing power system to cater increasing power needs is a growing trend. Wind energy is one of the prominent utilized renewable sources. However, the generation level of integrated wind energy significantly affects the frequency characteristics of entire system. Further, if the control scheme of wind systems are not properly working then this situation may deteriorate the frequency characteristics of whole system. Therefore, it is indispensable to tune the parameters of controllers of existing and wind systems in proper coordination so as to improve the frequency characteristics of the system. Consequently, in this work, a coordinated tuning of parameters of controllers to improve frequency characteristics of a multi-area interconnected thermal system in presence of doubly-fed induction generator (DFIG) based wind generation is presented. A widely used two-area non-reheat thermal interconnected system is simulated having its one area integrated with DFIG based wind generation. The parameters of controllers of thermal and wind systems are coordinately tuned using symbiotic organisms search (SOS) algorithm. Different design objectives are framed to achieve improved frequency characteristics of entire system. The considered objectives are combined together by proper assignment of weights using analytic hierarchy process to form a single objective function. Several test cases with diverse disturbances under different wind penetration levels are conducted to test the performance of system with SOS based controllers. To further assess the effectiveness of proposed controllers, other controllers using differential evolution (DE), elephant herding optimization (EHO), particle swarm optimization (PSO) and teaching-learning-based optimization (TLBO) are also designed and comparatively tested under the considered cases.

Multi-objective dynamic optimal power flow of wind integrated power systems considering demand response

This paper studies the economic environmental energy-saving day-ahead scheduling problem of power systems considering wind generation (WG) and demand response (DR) by means of multi-objective dynamic optimal power flow (MDOPF). Within the model, fuel cost, carbon emission and active power losses are taken as objectives, and an integrated dispatch mode of conventional coal-fired generation, WG and DR is utilized. The corresponding solution process to the MDOPF is based on a hybrid of a non-dominated sorting genetic algorithm-II (NSGA-II) and fuzzy satisfaction-maximizing method, where NSGA-II obtains the Pareto frontier and the fuzzy satisfaction-maximizing method is the chosen strategy. Illustrative cases of different scenarios are performed based on an IEEE 6-units\30-nodes system, to verify the proposed model and the solution process, as well as the benefits obtained by the DR into power system.