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Hybrid bilevel optimization-based interaction between the distribution grid and PV microgrids with differentiated demand response

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FRONTIERS IN ENERGY RESEARCH 2023年 11卷

作者： Shao, Zhimin Liu, Chunxiu Yao, Rui Wang, Cong Li, Longtan Liu, Zhen Liu, Yimin Zhou, Zaiyan State Grid Shandong Elect Power Co Jinan Peoples R China State Grid Shandong Dezhou Power Supply Co Dezhou Peoples R China State Grid Shandong Yucheng Power Supply Co Dezhou Peoples R China State Grid Shandong Pingyuan Cty Power Supply Co Dezhou Peoples R China

Demand response plays an important role in improving the balance of power generation and consumption between the distribution grid and photovoltaic (PV) microgrids. However, due to the uncertainty and volatility of PV output, as well as the different operation goals of PV microgrids, a conventional single-tier optimization approach is infeasible to realize the coordinated interaction between the distribution grid and PV microgrids. To address these challenges, we propose a second-order cone and improved consensus algorithm-based hybrid bilevel optimization algorithm for the interaction between the distribution grid and PV microgrids. First, we construct price-based and incentive-based differentiated demand response models to deal with various supply and demand dynamics of the distribution grid and PV microgrids. Building upon this foundation, we construct a hybrid bilevel optimization model. In the lower level, distributed optimization is adopted, and an improved consensus algorithm is used to optimize power output of PV microgrids to maximize the revenue based on output power of upper-level generator sets. In the upper level, centralized optimization is adopted, and second-order cone programming is employed to minimize the grid loss in the distribution grid based on the power output of lower-level PV microgrids. Hybrid bilevel optimization is iterated until the convergence condition is satisfied. Simulation results verify the proposed algorithm for achieving a coordinated interaction between the distribution grid and PV microgrids.

关键词： hybrid bilevel optimization differentiated demand response distribution grid PV microgrid improved consensus algorithm power flow optimization

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Otimização do problema de reconfiguração de sistemas de distribuição de energia elétrica por meio das Meta-Heurísticas Busca Tabu, GRASP e Path Relinking

Otimização do problema de reconfiguração de sistemas de ...

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作者： Marinho, Max Robert Universidade Estadual Paulista

O problema de reconfiguração de sistemas de distribuição de energia elétrica consiste em encontrar uma configuração radial por meio da permutação do estado das chaves (aber... 详细信息

O problema de reconfiguração de sistemas de distribuição de energia elétrica consiste em encontrar uma configuração radial por meio da permutação do estado das chaves (abertura ou fechamento) dos ramos de um sistema elétrico. O objetivo é de se alcançar a minimização das perdas elétricas. Cada configuração radial só é considerada factível se respeitar certas restrições operacionais como o limite de tensão nas barras e os limites de correntes nos circuitos. O modelo tratado neste trabalho apresenta explosão combinatória e difícil tratabilidade por meio de métodos convencionais de otimização. O problema, computacionalmente falando, é considerado Não-Polinomial Completo (NPC), pois não possui uma resposta em tempo polinomial a partir de uma entrada definida. Neste trabalho são apresentadas três técnicas meta-heurísticas para se tratar o problema de reconfiguração de sistemas de distribuição de energia elétrica, totalmente diferentes entre uma e outra, atuando em conjunto, para somente um nível de demanda, no intuito de se encontrar a topologia ótima, com o objetivo de se minimizar as perdas elétricas ativas. Além disso, propôs-se modificar o paradigma clássico de implementação estático deste tipo de problema para o paradigma de programação dinâmica por meio de árvores com filhos variados a fim de que a estrutura de dados utilizada representasse fielmente um sistema de distribuição de energia elétrica na memória do computador. As meta-heurísticas implementadas foram a Greedy Randomized Adaptive Search Procedure (GRASP) como estratégia de obtenção de uma configuração inicial de boa qualidade; a Busca Tabu (BT) como procedimento de busca local; e a técnica de Path Relinking (PR) como mecanismo de pós-otimização. Todo o programa foi implementado em linguagem C com uso da IDE Code Blocks 17.12. Os testes foram realizados com sistemas de pequeno, médio e grande porte de 14, 33, 84, 136 e 415 barras. As técnicas comparativas envolveram resultados da literatura especializada e

关键词： Busca Tabu Path Relinking GRASP Reconfiguração de sistemas de distribuição de energia elétrica Otimização de fluxo de potência Tabu Search Distribution network reconfiguration power flow optimization Tese de doutorado

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Autonomous reactive power support for smart photovoltaic inverter based on real-time grid-impedance measurements of a weak grid

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ELECTRIC power SYSTEMS RESEARCH 2020年第0期182卷 106207-000页

作者： Alenius, Henrik Luhtala, Roni Messo, Tuomas Roinila, Tomi Tampere Univ Fac Informat Technol & Commun Sci Tampere Finland Tampere Univ Fac Engn & Nat Sci Tampere Finland

A large share of renewable energy production is connected to a weak grid with significant grid impedance. The transmission impedance causes unintended flow of reactive power to grid, coupling the grid reactive power to the active power fed from the inverter. The reactive power causes transmission losses, strains the grid with reactive power requirements, and can even compromise system stability. Requirements on reactive power support were recently imposed on new photovoltaic inverters, which are often implemented with proportional power factor control or droop control for local voltage regulation. The present work proposes a method for real-time compensation of the unintended reactive power, which decouples the reactive power from the active power of a photovoltaic inverter. Based on real-time measurement of the grid impedance, the unintended reactive power is estimated and autonomously compensated in the inverter. The method removes the fluctuating reactive power component, while still permitting unrestricted manual control of the reactive power. Unlike conventional methods, the proposed method requires no prior knowledge on grid impedance values or delicate tuning. The method outperforms conventional power factor control even when the conventional method is tuned optimally with known grid inductance. The method is validated with simulations and experiments on three-phase photovoltaic inverter connected to a weak grid.

关键词： power electronics Photovoltaic systems power conditioning Reactive power control power flow optimization

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Hierarchical genetic optimization of a fuzzy logic system for energy flows management in microgrids

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APPLIED SOFT COMPUTING 2017年 60卷 135-149页

作者： De Santis, Enrico Rizzi, Antonello Sadeghian, Alireza SAPIENZA Univ Rome Dept Informat Engn Elect & Telecommun Via Eudossiana 18 I-00184 Rome Italy Ryerson Univ Dept Comp Sci 350 Victoria St Toronto ON M5B 2K3 Canada

Bio-inspired algorithms like Genetic Algorithms and Fuzzy Inference Systems (FIS) are nowadays widely adopted as hybrid techniques in improving goods and services. In this paper we present an interesting application of the fuzzy-GA paradigm to the problem of energy flows management in microgrids, concerning the design, through a data driven synthesis procedure, of an Energy Management System (EMS). The main aim consists in performing decision making for power flow management tasks in the proposed microgrid model, equipped by renewable sources and an energy storage system, aiming to maximize the accounting profit in energy trading with the main-grid. In particular this study focuses on the application of a Hierarchical Genetic Algorithm (HGA) for tuning the Rule Base (RB) of a Fuzzy Inference System( FIS), trying to discover a minimal fuzzy rules set as the core inference engine of an an EMS. The HGA rationale focuses on a particular encoding scheme, based on control genes and parametric genes, applied to the optimization of the FIS parameters, allowing to perform a reduction in the structural complexity of the RB. A performance comparison is performed with a simpler approach based on a classic fuzzy GA scheme, where both FIS parameters and rule weights are tuned, while the number of fuzzy rules is fixed in advance. Experiments shows how the fuzzy-HGA approach adopted for the synthesis of the proposed controller outperforms the classic fuzzy-GA scheme, increasing the accounting profit by 67% in the considered energy trading problem, yielding at the same time a simpler RB. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Microgrid Energy Management System Battery Energy Storage power flow optimization Storage system management Fuzzy systems Evolutionary computation Hierarchical Genetic Algorithms

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Innovative Reactive Energy Management for a Photovoltaic Battery System 10th

Innovative Reactive Energy Management for a Photovoltaic Bat...

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10th International Renewable Energy Storage Conference (IRES)

作者： Boettiger, Michael Paulitschke, Martin Bocklisch, Thilo Tech Univ Dresden Chair Energy Storage Syst George Baehr Str 3c D-01069 Dresden Germany

This paper presents an optimizing model-based energy management system for an AC-coupled grid connected photovoltaic battery system. The energy management consists of a prediction module, an optimization module, and a reactive management module. The main focus of this article is to present an innovative reactive management that can handle forecast uncertainties. The so called "SOC-bound method" will be described in detail. Main idea is to combine the outputs of the dynamic programming algorithm with a simple rule-based strategy. Furthermore, the results of a start-time and start-/end-SOC sensitivity analysis concerning the six performance criteria self-sufficiency, self-consumption, grid relief factor, economic parameter, battery full cycles, and specific battery stress value will be discussed. (C) 2016 The Authors. Published by Elsevier Ltd.

关键词： energy management dynamic programming energy storage power flow optimization smart home

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Innovative Reactive Energy Management for a Photovoltaic Battery System

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Energy Procedia 2016年 99卷 341-349页

作者： Michael Böttiger Martin Paulitschke Thilo Bocklisch Technische Universität Dresden chair of Energy Storage Systems George-Baehr-Str 3c 01069 Dresden Germany

This paper presents an optimizing model-based energy management system for an AC-coupled grid connected photovoltaic battery system. The energy management consists of a prediction module, an optimization module, and a reactive management module. The main focus of this article is to present an innovative reactive management that can handle forecast uncertainties. The so called “SOC-bound method” will be described in detail. Main idea is to combine the outputs of the dynamic programming algorithm with a simple rule-based strategy. Furthermore, the results of a start-time and start-/end-SOC sensitivity analysis concerning the six performance criteria self-sufficiency, self-consumption, grid relief factor, economic parameter, battery full cycles, and specific battery stress value will be discussed.

关键词： energy management dynamic programming energy storage power flow optimization smart home

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Stochastic Model Predictive Control for Optimal Economic Operation of a Residential DC Microgrid

Stochastic Model Predictive Control for Optimal Economic Ope...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Gulin, Marko Matusko, Jadranko Vasak, Mario Univ Zagreb Fac Elect Engn & Comp Lab Renewable Energy Syst Zagreb 41000 Croatia

ISBN: (纸本)9781479978007

In this paper we present power flow optimization of a residential DC microgrid that consists of photovoltaic array, batteries stack and fuel cells stack with electrolyser, and is connected to the grid via bidirectional power converter. The optimization problem aims to minimize microgrid operating costs and is formulated using a linear program that takes into account the storages charge and discharge efficiency. To account for power predictions uncertainty, optimization problem is defined in a stochastic framework by using chance constraints. Since we assume that the error in realization of power predictions will he compensated by utility grid, chance constraints are defined for power exchange between the microgrid and the utility grid. Finally, we investigate a stochastic model predictive control for the closed-loop power management in the microgrid. Performance verification of the proposed approach is performed on simulations for two-month period.

关键词： Microgrid Stochastic Model Predictive Control Linear Program power flow optimization Chance Constraints

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Various approaches to problems of multicriterion optimization processes of electric power systems

Various approaches to problems of multicriterion optimizatio...

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Conference on International Symposium on Electromagnetic Compatibility Tokyo

作者： Nikolay, Korovkin Mikhail, Odintsov Nikolay, Belyaev Oleg, Frolov Hayakawa, Masashi St Petersburg State Polytech Univ Theoret Elect Engn Dept St Petersburg Russia Joint Stock Co Sci & Tech Ctr Unified Power Syst St Petersburg Russia Univ Electrocommun UEC Seismo Electromagnet Co Ltd Hayakawa Inst Incubat Ctr Tokyo Japan UEC Adv Wireless Commun Res Ctr Tokyo Japan UEC Res Stn Seismo Electromagnet Tokyo Japan

ISBN: (纸本)9784885522871

The efficiency of multi-criterion optimization methods for enhancing the efficiency of operating states of electric power systems (EPS) has been studied. On the example of 14-node IEEE-circuit there have been compared Pareto multitudes obtained by two methods. The first one consists in applying the traditional approach of multi-criterion problem solution. The second one creates Pareto multitude with the use of non-dominated sorting algorithm. Has been developed an approach to compare the efficiency of the multi-criterion optimization algorithms. It is shown that with the regard to time-consuming costs the first approach is 10-20 times inferior to the second one. The solution of two-criterion power flow optimization problem of Kolskaya EPS has been performed;a recommendation on the control of operating states of a given EPS has been presented.

关键词： quality vector criterion multi-criterion optimization genetic algorithm non-dominated sorting control of operating states of power systems power flow optimization

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Smart Integration of Distribution Automation Applications

Smart Integration of Distribution Automation Applications

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

作者： de Groot, R. J. W. Morren, J. Slootweg, J. G. Eindhoven Univ Technol Elect Energy Syst Grp NL-5612 AZ Eindhoven Netherlands

ISBN: (纸本)9781467325950;9781467325967

Future electricity demand will significantly increase, while flexibility in supply will decrease, due to an increase in the use of renewable energy sources. The most effective way to prepare distribution grids for this increase in loading and decrease in supply-flexibility is to apply balancing, load-shifting, peak-shaving and other smart-grid related technologies. Without the implementation of smart grid technologies in distribution networks, it is almost impossible to keep the power supply at the current reliability and quality levels. An important factor in the success of smart grids, is the implementation of distribution automation systems (DAS). The ability to reconfigure networks, divert power flows, isolate faults and prevent overloading of network components all contributes to the optimal operation of self-healing distribution grids, which is necessary for future electricity demands. In this paper, a literature research on the status of distribution automation research is presented and an outlook towards future roles of distribution automation systems is explored. Emphasis is put on the integration of different applications in order to be able to grasp the full potential of DAS. Furthermore an elaborate case study is presented, considering the effects of DAS integration into the live distribution grid.

关键词： Distribution Automation Smart Grids Future power Supply power Quality power flow optimization

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Control Tuning Analysis of Small Wind power Systems

Control Tuning Analysis of Small Wind Power Systems

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15th International power Electronics and Motion Control Conference and Exposition (EPE-PEMC ECCE Europe)

作者： Cacciato, M. Consoli, A. Scarcella, G. Scelba, G. Univ Catania Catania Italy

ISBN: (纸本)9781467319720

The paper deals with the determination of the optimal control tuning of small Vertical Axis Wind Turbines (up to 10kW), in order to maximize the energy harvesting in urban environment. Because of the highly variable wind speed profiles, it is hard to obtain an optimal set up of the parameters of the system control algorithm. A suitable model including system losses is presented in the paper then, with the aims of maximizing the aerodynamic efficiency of the wind turbine and minimizing the whole system losses, a performance comparison is performed using different control parameters arrangements. Exploiting a precise power flow analysis, the proposed model-based procedure allows us to determine the best tuning configuration of the system.

关键词： Gust tracking control wind turbine loss reduction power flow optimization

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