Optimal management of the automatic generation control service in smart user grids including electric vehicles and distributed resources

Battistelli, Claudia; Conejo, Antonio J.

doi:10.1016/j.epsr.2014.01.008

Cited by 37 publications

(29 citation statements)

References 12 publications

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“…1. The development of this system follows the paradigm of "smart user grid" [21], [22] where a complex MG can be seen as a grouping of several sub-MGs with suitable interfaces. In this framework, an AC sub-MG is connected to a DC sub-MG through an interlinking converter, so as to form a hybrid MG structure.…”

Section: A Hybrid Microgrid Frameworkmentioning

confidence: 99%

“…In the case of controllable loads such as thermal appliances, a certain temperature range cannot be violated, whereas for vehicles there are restrictions imposed by the desired state of charge of EV batteries for transportation purposes. For EVs, equipping the EV station for battery swapping service -which ensures the replacement of discharged batteries with fresh ones -can best suit the implementation of energy demand management [22]. In fact, the EV customers can contract the battery swapping service alongside the charging service, and the EV station operator can arrange a recharge-controlled battery stock as a local reserve, to be kept as an offer of lease to the EV customers if the energy demand management actions call for adjustments in their battery charging schedule.…”

Section: B Energy Management Criteriamentioning

confidence: 99%

“…These bands are set up by agreement between the hybrid MG operator and the electricity customers [22].…”

Section: F) Energy Demand Managementmentioning

confidence: 99%

“…The contracted bands of load reduction are mainly constrained by the aggregated rated power and the customers' requirements [22], [37]. Accordingly, the contracted bands for the curtailment of the controllable loads are formulated as follows:…”

Section:  Energy Demand Management On Controllable Loadsmentioning

confidence: 99%

“…Following the work in [17], [21] and [22], this paper proposes an EM scheme embedding battery energy storage and energy demand management for ensuring -even in uncertain conditions related to the fluctuations of certain parameters -a reliable power supply at the minimum operation cost of the hybrid MG. Then, the proposed optimization modeling approach is based on an economic dispatch (ED) problem formulation, where the objective is minimizing the costs of controllable generators and battery storage operation, as well as of energy demand management carried out on controllable loads, such as thermal loads or electric vehicles (EVs). Operating limits of controllable generators and interlinking converter, battery charge and discharge behavior, demand controllability limits, etc., are mathematically modeled and represented as constraints in the ED framework.…”

mentioning

confidence: 99%

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Probabilistic Dispatch of Remote Hybrid Microgrids Including Battery Storage and Load Management

Battistelli

Agalgaonkar

Pal

2017

IEEE Trans. Smart Grid

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-This work presents a probabilistic economic dispatch tool for energy management (EM) studies in the context of remote hybrid AC/DC microgrids (MGs). An EM approach is proposed to ensure a reliable power supply at the minimum cost of the hybrid MG operation. A comprehensive operational framework is presented, which considers topological features of the hybrid MG and the interlinking converter between AC and DC subsections. Approach and models are tested using several operating scenarios referred to a test hybrid MG system. In the analyses, the opportunity of integrating battery energy storage and energy demand management in the EM scheme is investigated. The results of the analyses demonstrate the effectiveness and practicality of the optimization tool in different operation contexts. -represent a more likely architecture. Hybrid MGs can be a cost-effective solution to supply affordable and reliable electricity to rural and remote communities, given their unique feature of using locally available generation resources (such as solar, wind, water stream and biomass) to supply the specific demand needs. IndexDespite combining the advantages of AC and DC, operating a hybrid MG brings challenges in power quality, reliability, efficiency and control. There have been several publications addressing dynamics and control of hybrid . Schemes and techniques for the control of AC and DC subsections of a hybrid MG, as well as of their power electronics interface, are examined in [6]-[9], for both grid-connected and islanded modes of operation. Focusing on the interlinking converter between AC bus and DC bus, authors in [9] propose a DC-side hierarchical control scheme to analyze both standalone and grid-connected DC operation. Interaction dynamics in hybrid AC/DC distribution systems are investigated in [10], alongside strategies for their mitigation; in this case, small-signal analysis is used to model the input/output DC-side admittance of the system components. Harmonics analysis and harmonics mitigation methods are studied in [12]-[14] for standalone and grid-connected hybrid systems. Authors in [13] propose, in particular, a reduction method for the zero-sequence circulating currents between parallel AC/DC interlinking inverters, whereas [14] presents a DC bus voltage control scheme to suppress the transient fluctuations of DC-bus voltage and improve power. Finally, [15] presents a back-to-back converter structure for grid-connected hybrid MGs, which can provide isolated and reliable system connection with improved power flow management. Outside this research, what is still missing in the literature is a comprehensive energy management (EM) framework that can incorporate and address the aforementioned issues in a robust manner [5].Optimization-based EM has been well explored in AC MGs or DC . In hybrid MGs, the EM becomes more challenging because of the interconnection between DC side

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Section: A Hybrid Microgrid Frameworkmentioning

confidence: 99%

Section: B Energy Management Criteriamentioning

confidence: 99%

“…These bands are set up by agreement between the hybrid MG operator and the electricity customers [22].…”

Section: F) Energy Demand Managementmentioning

confidence: 99%

Section:  Energy Demand Management On Controllable Loadsmentioning

confidence: 99%

mentioning

confidence: 99%

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Probabilistic Dispatch of Remote Hybrid Microgrids Including Battery Storage and Load Management

Battistelli

Agalgaonkar

Pal

2017

IEEE Trans. Smart Grid

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Polygeneration Microgrids for Residential Applications

Kyriakarakos

Papadakis

2015

Handbook of Clean Energy Systems

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Considerable research is taking place globally concerning the energy consumption in residential buildings. The effort is aimed toward the creation of zero energy buildings or even positive energy ones. In order to accomplish this, energy production is needed at the building level. Electrical energy, thermal energy for space heating and cooling, and domestic hot water production are common needs globally, whereas water pumping, water desalination, and onsite fuel production are also of rising interest. The polygeneration microgrid topology aims at unifying all the energy systems in a building and through advanced energy management approaches to optimize the energy flows in the building managing to provide optimum indoor comfort, meeting of all the energy needs of the residents and minimizing the environmental impact of the building. This article presents this topology in detail and also proposes a methodology for the design and sizing of such systems.

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A power balancing method of distributed generation and electric vehicle charging for minimizing operation cost of distribution systems with uncertainties

Jiekang

et al. 2017

Energy Science & Engineering

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The output power of distributed generation depends on the wind speed, solar light intensity, and other climatic factors, which have intermittent and uncertain characteristics [4]. Because of the difference in energy state of battery, the expected driving distance in a day, the charging power, the expected charging time, and so on, electric vehicle charging also has uncertain characteristics. The uncertainties of distributed generation and electric vehicle charging may bring a great impact on distribution systems. The randomness and uncertainties of distributed MODELING AND ANALYSISA power balancing method of distributed generation and electric vehicle charging for minimizing operation cost of distribution systems with uncertainties AbstractA power balancing method of distributed generation (DG) and electric vehicle charging is presented for minimizing operation costs of distribution systems with uncertainties, which includes the uncertainties in output power of DG and the randomness of charging power of electric vehicles (EV). A probability model is established for the uncertain characteristics of DG and electric vehicle charging. A multi-state optimization coordination method for DG of renewable energy systems and electric vehicle charging in distribution systems based on quadratic rotation cone programming is presented to minimize the expected generation cost of generators in the main power grid, the expected operation cost of DG systems in distribution systems, and the expected social outage loss. An objective function maximizing the operation efficiency of distribution systems with DGs and EVs is proposed. Using quadratic rotated conic programming, the nonlinear objective function and constraint functions are transformed into a linear form. An IEEE 14-node distribution system is used as a study example to illustrate adaptability of the proposed model and the feasibility of the proposed method. The simulation results show that the proposed method simplifies the original problem of the optimization problem and makes its solution faster, more stable, and better. 168

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Optimal management of the automatic generation control service in smart user grids including electric vehicles and distributed resources

Cited by 37 publications

References 12 publications

Probabilistic Dispatch of Remote Hybrid Microgrids Including Battery Storage and Load Management

Probabilistic Dispatch of Remote Hybrid Microgrids Including Battery Storage and Load Management

Polygeneration Microgrids for Residential Applications

A power balancing method of distributed generation and electric vehicle charging for minimizing operation cost of distribution systems with uncertainties

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