An integrated framework of agent-based modelling and robust optimization for microgrid energy management

Kuznetsova, Elizaveta; Li, Yan‐Fu; Ruiz, Carlos; Zio, Enrico

doi:10.1016/j.apenergy.2014.04.024

Cited by 191 publications

(94 citation statements)

References 67 publications

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“…A la fecha, los estudios de confiabilidad en los transformadores a nivel mundial se han centrado en temas puntuales como el análisis de gas disuelto en transformadores Wang(2012), (Pereira, 2012a), (Zhan, Member, Goulart, Falahi, & Rondla, 2015), entrenamiento de herramientas como redes neuronales Zhang(1996), (Kuznetsova, Li, Ruiz, & Zio, 2014), sistemas expertos con información limitada del comportamiento ciertos transformadores (Lin, Ling, & Huang, 1993), identificación variables de mantenimiento mediante lógica difusa (Arshad, Islam, & Khaliq, 2014), minería de datos para calidad de eventos (M. Guder 2014), falla de transformadores y métodos estadísticos (Soto, 2015), (Youssef, 2003), (Mkandawire, Ijumba, & Saha, 2015), (Mago, Valles, & Olaya, 2012), (Georgilakis & Kagiannas, 2014), (Ridwan & Talib, 2014), (Zompakis, Bartzas, & Soudris, 2015), (Zompakis et al, 2015), (Henao, Amaya, & Jaramillo, 2014), entre otros. La siguiente figura permite dimensionar el estudio de transformadores utilizando herramientas que permitan analizar grandes volúmenes de datos y alguna técnica inteligente para este fin.…”

Section: Introductionunclassified

Análisis De Eventos Sobre Transformadores De Distribución en Una Empresa Del Sector Eléctrico en Colombia

Guayasamin

Castrillón

Cano

2017

RCTA

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Section: Introductionunclassified

Análisis De Eventos Sobre Transformadores De Distribución en Una Empresa Del Sector Eléctrico en Colombia

Guayasamin

Castrillón

Cano

2017

RCTA

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“…Aziz's [20] studies showed that the application of EVs and used EV batteries in supporting certain small-scale energy management systems is feasible. From this perspective, storage facilities must be provided to reduce the possibility of abandoned electricity given that EVs can provide storage capacity [21]. Tang et al [22] analyzed the feasibility of PV-powered EVs (PV-EV) by considering their technological and economic aspects.…”

Section: Literature Reviewmentioning

confidence: 99%

Feasibility Study of a Solar-Powered Electric Vehicle Charging Station Model

Jiang

Liu

et al. 2015

Energies

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In China, the power sector is currently the largest carbon emitter and the transportation sector is the fastest-growing carbon emitter. This paper proposes a model of solar-powered charging stations for electric vehicles to mitigate problems encountered in China's renewable energy utilization processes and to cope with the increasing power demand by electric vehicles for the near future. This study applies the proposed model to Shenzhen City to verify its technical and economic feasibility. Modeling results showed that the total net present value of a photovoltaic power charging station that meets the daily electricity demand of 4500 kWh is $3,579,236 and that the cost of energy of the combined energy system is $0.098/kWh. In addition, the photovoltaic powered electric vehicle model has pollutant reduction potentials of 99.8%, 99.7% and 100% for carbon dioxide, sulfur dioxide, and nitrogen oxides, respectively, compared with a traditional gasoline-fueled car. Sensitivity analysis results indicated that interest rate has a relatively strong influence on COE (Cost of Energy). An increase in the interest rate from 0% to 6% increases COE from $0.027/kWh to $0.097/kWh. This analysis also suggests that carbon pricing promotes renewable energy only when the price of carbon is above $20/t.

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“…Some formulations simplify the modeling so that the problem can be formulated as a linear or a convex optimization problem, e.g., [12,17,23,25,26]. Others formulate a nonlinear optimization problem, e.g., [10, 11, 13-16, 18, 19, 21, 22, 24, 27, 28] and provide heuristic solutions to the non-convex problem, e.g., teachinglearning-based optimization [28], multi-agent optimization [10], multi-objective mesh adaptive direct search [14], quantum evolutionary algorithm [15], or particle swarm optimization [27]. The advantage of linear formulations lies in their scalability and guarantee of finding the optimum solution.…”

Section: The Distributed Energy Resource Customer Adoption Modelmentioning

confidence: 99%

“…Depending on the types of energy systems included in the problem, these formulations can be classified into two groups. Some of these algorithms only focus on electrical energy flow and neglect the thermal energy flow, e.g., [10][11][12][13][14][15][16][17][18][19][20][21][22]. However, in microgrids, optimal dispatch of thermal resources is as important as electrical resources, and simultaneous optimization of thermal and electrical resources is of great importance, especially when the two are linked through CHP-enabled technologies [23].…”

Section: The Distributed Energy Resource Customer Adoption Modelmentioning

confidence: 99%

Distributed energy systems integration and demand optimization for autonomous operations and electric grid transactions

et al. 2016

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Distributed power systems in the U.S. and globally are evolving to provide reliable and clean energy to consumers. In California, existing regulations require significant increases in renewable generation, as well as identification of customer-side distributed energy resources (DER) controls, communication technologies, and standards for interconnection with the electric grid systems. As DER deployment expands, customer-side DER control and optimization will be critical for system flexibility and demand response (DR) participation, which improves the economic viability of DER systems. Current DER systems integration and communication challenges include leveraging the existing DER and DR technology and systems infrastructure, and enabling optimized cost, energy and carbon choices for customers to deploy interoperable grid transactions and renewable energy systems at scale. This paper presents a cost-effective solution to these challenges by exploring communication technologies and information models for DER system integration and interoperability. This system uses open standards and optimization models for resource planning based on dynamic-pricing notifications and autonomous operations within various domains of the smart grid energy system. It identifies architectures and customer engagement strategies in dynamic DR pricing transactions to generate feedback information models for load flexibility, load profiles, and participation schedules. The models are tested at a real site in California-Fort Hunter Liggett (FHL). The results for FHL show that the model fits within the existing and new DR business models and networked systems for transactive energy concepts. Integrated energy systems, communication networks, and modeling tools that coordinate supply-side networks and DER will enable electric grid system operators to use DER for grid transactions in an integrated system.

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An integrated framework of agent-based modelling and robust optimization for microgrid energy management

Cited by 191 publications

References 67 publications

Análisis De Eventos Sobre Transformadores De Distribución en Una Empresa Del Sector Eléctrico en Colombia

Análisis De Eventos Sobre Transformadores De Distribución en Una Empresa Del Sector Eléctrico en Colombia

Feasibility Study of a Solar-Powered Electric Vehicle Charging Station Model

Distributed energy systems integration and demand optimization for autonomous operations and electric grid transactions

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