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Modeling and Optimal Tuning of Hybrid ESS Supporting Fast Active Power Regulation of Fully Decoupled Wind Power Generators

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IEEE ACCESS 2021年 9卷 46409-46421页

作者： Zhang, Chenrui Rakhshani, Elyas Veerakumar, Nidarshan Torres, Jose Luis Rueda Palensky, Peter Delft Univ Technol Dept Elect Sustainable Energy NL-2628 Delft Netherlands

The frequency stability of the power system is challenged by the high penetration of power electronic interfaced renewable energy sources (RES). This paper investigates the improvements of the frequency response of fully decoupled wind power generators (FDWG) by proposing a novel generic model implementation of ultracapacitors (UC) within a hybrid scheme in real-time simulations of wind power plants. UCs are selected as ideal power sources in fast active power-frequency control due to their high power density and fast-reacting speed. Batteries and UCs combined hybrid energy storage systems (HESS) are formed to complement their characteristics. Droop-based and frequency derivative-based control and virtual synchronous power (VSP) are the selected control strategies to support power system frequency stability. The best trade-off between frequency performance and HESS cost is found by solving a proposed optimization problem formulation. The proposed optimization problem is used to define the HESS size and the controller parameters. The optimization results show how the fast active power-frequency response is enhanced by the fast UC power injection. It also shown that VSP leads to faster frequency support than the droop-based control and the frequency derivative control.

关键词： Power system stability Frequency control Batteries Generators Frequency synchronization Frequency measurement optimization Fast active power-frequency response ultracapacitor model hybrid energy storage system fully decoupled wind power generator mean-variance mapping optimization

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Local Volt/VAR Droop Control Strategies for Wind Generators in Distribution Networks

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INTERNATIONAL JOURNAL OF RENEWABLE ENERGY RESEARCH 2020年第4期10卷 1899-1906页

作者： Nguyen, Hoa M. Pharr, Hoan, V Tra Vinh Univ Dept Elect Engn Tra Vinh Vietnam

This paper proposes a novel approach using a non-linear least squares method for fitting optimally statistical data points to estimate optimal set-points of various local Volt/var droop control schemes implemented into wind generators (WGs) in distribution networks. The approach utilizes the Monte Carlo simulation and considers the variation of wind speed, electricity demand, and outage duration of WGs as uncertainties to evaluate the effects of each local scheme regarding the resulting statistical attributes of voltage variation profiles and total active power losses. The approach's effectiveness is demonstrated on a radial distribution network in Germany with four identical 20 kV feeders.

关键词： Distribution networks loss reduction mean-variance mapping optimization

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Optimal Dispatch of Reactive Power Sources by Using MVMO^S optimization

Optimal Dispatch of Reactive Power Sources by Using MVMO<SUP...

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IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG)

作者： Rueda, Jose L. Erlich, Istvan Univ Duisburg Essen Inst Elect Power Syst Duisburg Germany

ISBN: (纸本)9781467360029

In this paper, the swarm implementation of the mean-variance mapping optimization (MVMOS) is proposed to solve the optimal reactive power dispatch problem. Apart from incorporating swarm intelligence principles, MVMOS possesses enhanced mapping and penalty schemes as compared to the classical MVMO procedure. Based on the IEEE 57- and 118- bus systems, numerical tests and comparisons with other heuristic optimization methods are carried out. Additionally, a scheme for adaptive smart optimal reactive power source coordination, which can be used online, is suggested.

关键词： Heuristic optimization mean-variance mapping optimization reactive power dispatch smart grid swarm intelligence

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Optimal Management of Reactive Power Sources in Far-offshore Wind Power Plants

Optimal Management of Reactive Power Sources in Far-offshore...

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IEEE Manchester PowerTech

作者： Theologi, A. M. Ndreko, M. Rueda, J. L. van der Meijden, M. A. M. M. Gonzalez-Longatt, F. Delft Univ Technol Delft Netherlands Aristotle Univ Thessaloniki Thessaloniki Greece TenneT TSO BV Arnhem Netherlands Loughborough Univ Loughborough Leics England

ISBN: (纸本)9781509042371

This paper introduces a new approach for the optimal management of reactive power, with emphasis on offshore wind power plants. The approach follows a predictive optimization scheme (i.e. day-ahead, intraday application). Predictive optimization is based on the principle of minimizing the real power losses, as well the number of On-load Tap Changer (OLTC) operations for daily time horizon (discretized in 24 hours). The mixed-integer nature of the problem and the restricted computing budget is tackled by using an emerging metaheuristic algorithm called mean-variance mapping optimization (MVMO). The evolutionary mechanism of MVMO is enhanced by introducing a new mapping function, which improves its global search capability. The effectiveness of MVMO to find solutions that ensure minimum losses, minimum impact on OLTC lifetime, and well as optimal grid code compliance is demonstrated by investigating the case of a real world far-offshore wind power plant with HVDC connection.

关键词： optimal reactive power management mean-variance mapping optimization on-load tap changer

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Optimal Dispatch of Reactive Sources in Wind Farms

Optimal Dispatch of Reactive Sources in Wind Farms

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General Meeting of the IEEE-Power-and-Energy-Society (PES)

作者： Erlich, I. Nakawiro, W. Martinez, M. Univ Duisburg Inst Elect Power Syst D-47057 Duisburg Germany

ISBN: (纸本)9781457710018

This paper suggests three different approaches for online reactive power dispatch in wind farms by using a new heuristic optimization algorithm called mean-variance mapping optimization (MVMO). optimization for any given operating point will result in minimum losses but doesn't allow the consideration of the cost of on-load tap changer (OLTC) movements. To solve this problem the authors propose a predictive optimization where the objective is extended by the number of OLTC tap changes. Besides several time steps ahead are optimized simultaneously by using the information provided by a short term power forecast. In addition the authors suggest a method for incorporating the reactive power optimization into the wind farm control loop so that it can be used online to determine the optimal distribution of reactive power generation by each wind turbine. The proposed methods are demonstrated in a representative offshore wind farm.

关键词： Reactive power dispatch offshore wind farms mean-variance mapping optimization heuristic optimization

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Assessment Method for Incentives and their optimization considering Demand Response of Consumers

Assessment Method for Incentives and their Optimization cons...

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3rd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies Europe (ISGT Europe)

作者： Holtschneider, T. Erlich, I. Univ Duisburg Essen D-47057 Duisburg Germany

ISBN: (纸本)9781467325950;9781467325967

In a smart grid, communication technology allows short-term application of incentives in monetary form and thus dynamic pricing to the consumers. Incentives can help to reduce critical situations in grids, but for cost efficient application, they have to be optimized before the most suitable incentive is provided to the consumers. This paper introduces an assessment method for incentives taking into account demand response and the participation of individual consumers. Thereby, a model describing rational decision of individuals to incentives is presented. As the model uses adaptive neuro-fuzzy inference system (ANFIS) it can easily be trained. The assessment method includes heuristic optimization, namely the mean-variance mapping optimization (MVMO), which provides excellent performance in terms of convergence behavior and accuracy. MVMO can be used within the method to optimize the incentive with respects to the defined objective and given constraints. Structure of the model and procedure of the assessment method are illustrated, and performance of the method is demonstrated based on examples.

关键词： demand response demand side management demand side participation incentives dynamic pricing heuristic optimization mean-variance mapping optimization

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Hybrid Single Parent-Offspring MVMO for Solving CEC2018 Computationally Expensive Problems

Hybrid Single Parent-Offspring MVMO for Solving CEC2018 Comp...

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IEEE Congress on Evolutionary Computation (IEEE CEC) as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Rueda, Jose L. Erlich, Istvan Delft Univ Technol Dept Elect Sustainable Energy Delft Netherlands Univ Duisburg Essen Inst Elect Power Syst Duisburg Germany

ISBN: (纸本)9781509060177

mean-variance mapping optimization (MVMO) belongs to the family of evolutionary algorithms, and has proven to be competitive in solving computationally expensive problems proposed in the Icompetitions CEC2014, CEC2015, and CEC2016. MVMO can tackle such problems by evolving a set of solutions (population based approach) or a single solution (single parent-offspring approach). The evolutionary mechanism of MVMO performs within a normalized search space in the range [0, 1]. The power of MVMO stems from its ability based on statistical analysis of the evolving solution based on a mapping function- to adaptively shift the search priority from exploration to exploitation. This paper introduces a newly defined mapping function as well as a new rule for using an embedded local search strategy, and presents several tests conducted by using the test bed of the CEC2018 competition. Numerical results indicate significant improvements on the results obtained in CEC2016 competition.

关键词： Computationally expensive optimization heuristic optimization mean-variance mapping optimization single objective optimization

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Hybrid MVMO based Controller for Energy Management in a Grid Connected DC Microgrid

Hybrid MVMO based Controller for Energy Management in a Grid...

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IEEE Power, Communication and Information Technology Conference (PCITC)

作者： Mishra, Sukumar Sahoo, Subham Dugar, Aakanksha Indian Inst Technol Delhi Dept Elect Engn New Delhi 110016 India Crompton Greaves Ltd Dept High Voltage Engn Bombay Maharashtra India

ISBN: (纸本)9781479974559

This paper deals with a grid connected DC microgrid. The DC microgrid which consists of a PV array and DC loads has been integrated into the main grid through a 3-phase inverter to take power from the grid during low generation and feed the grid during high generation. A control scheme to manage the power flow in DC microgrid by tuning the conventional proportional-integral (PI) controllers in the grid side converter using a swarm variant of hybrid mean variance mapping optimization (MVMO-SH) algorithm has been proposed and tested under critical disturbances such as insolation drop and load change. The designed controller has been tuned using two strategic methods - sequential tuning and simultaneous tuning. Additionally, MVMO-SH has been compared with genetic algorithm (GA) to validate better performance owing to the multi-parent crossover strategy of MVMO-SH. The optimal gains have further been tuned to develop a faster inverter control. The results confirm that the designed controller significantly reduces the DC voltage deviations as well as incorporates faster tracking of current during various disturbances.

关键词： DC microgrid mean-variance mapping optimization inverter control energy management

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Multi-Agent System Based Solution of the Optimal Reactive Power Dispatch Problem in Autonomously Operated Multi-Area Systems

Multi-Agent System Based Solution of the Optimal Reactive Po...

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PowerTech, 2015 IEEE Eindhoven

作者： Pham, Hoan V. Ahmed, Sultan N. Erlich, I. Can Tho Univ Dept Elect Engn Can Tho Vietnam Univ Duisburg Essen Dept Elect Power Syst D-47057 Duisburg Germany

ISBN: (纸本)9781479976959

Cooperation of regional operators in solving optimal reactive power dispatch (ORPD) problems in large systems is beneficial despite of many challenges. One major challenge is the fact that each regional operator is typically not willing to reveal the local system data. To deal with such challenge and to try to attain a dispatch resulting in overall optimum, this paper proposes a control scheme in which a large area is partitioned into multi-agent based system where each operator is considered as a control agent and uses a model of its local system and communication links with its neighboring control agents to come to agreement on the evolution of interconnections and to determine optimal local control actions and states. At each agent, a linearized objective function enforced with constraints has to be solved to determine control variables, which are transformer tap positions and reactive power injections. Calculation procedure at each agent based on sensitivity coefficients, thus impact of change magnitudes of control variables on control performance would be significant and hence is fully analyzed. The proposed algorithm is applied to the modified IEEE 30-bus system and numerical results are presented.

关键词： mean-variance mapping optimization online adaptive control reactive power management wind power plant

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MVMO^S-based Approach for Identification of Dynamic Equivalents from PMU Measurements

MVMO<SUP>S</SUP>-based Approach for Identification of Dynami...

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IEEE Grenoble PowerTech (POWERTECH) Conference

作者： Cepeda, Jaime C. Rueda, Jose L. Erlich, Istvan Univ Nacl San Juan Inst Energia Elect San Juan Argentina Univ Duisburg Essen Inst Elect Power Syst Duisburg Germany

ISBN: (纸本)9781467356688

Accurate estimation of dynamic equivalent parameters from phasor measurement unit (PMU) signal records is crucial to achieve high confidence levels on the underlying simplified models, which should facilitate performing dynamic studies for large-interconnected power systems in near real-time. This paper introduces an alternative approach to this issue based on the swarm implementation of mean-variance mapping optimization (MVMOS). Its feasibility and effectiveness are verified using the Ecuadorian-Colombian interconnected system and a test wind power plant. Performance comparisons with other heuristic optimization tools demonstrate the MVMOS enhanced search capability, reflected in its outstanding convergence behavior and the accuracy of the identified models.

关键词： Dynamic equivalent mean-variance mapping optimization phasor measurement unit power system dynamic performance smart grid

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