Multi-objective optimization of a multiregional electricity system in an archipelagic state: The role of renewable energy in energy system sustainability

Pratama, Yoga Wienda; Purwanto, Widodo Wahyu; Tezuka, T.; McLellan, Benjamin; Hartono, Djoni; Hidayatno, Akhmad; Daud, Yunus

doi:10.1016/j.rser.2017.04.021

Cited by 48 publications

(20 citation statements)

References 48 publications

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“…Investigaciones recientes muestran que los indicadores ambientales presentan datos y comparaciones útiles para contribuir en la sostenibilidad de la naturaleza, en la toma de decisiones y formulación de políticas ambientales (Alphan, 2017;Neher et al, 2017;Nowak y Schneider, 2017;Pratama et al, 2017) y constituyen una herramienta básica de información y seguimiento de los procesos que se originan en el medio natural, social y económico (Xu y Zhang, 2013;Asumadu-Sarkodie y Owusu, 2017;Sinha et al, 2017).…”

Section: Indicadores Ambientales Espacio Temporalesunclassified

“…Un indicador describe situaciones de un espacio en un momento dado, es decir son indicadores espacio-temporales (Nowak y Schneider, 2017;Pratama et al, 2017;Bao y Zou, 2018) que proveen, condesan, sistematiza y ordenan información cuantitativa o cualitativa (Schindler et al, 2015;Li et al, 2016;Bao y Zou, 2018). Los indicadores ambientales presentan directrices, estadísticas, categorías clasificatorias y situaciones predictivas, que brindan señales de posibles escenarios futuros (Rodríguez et al, 2013;Wen et al, 2017) los cuales deben ser prácticos y realistas (Walz, 2015;Turner et al, 2016).…”

Section: Introductionunclassified

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Análisis de indicadores ambientales espacio-temporales de agua, suelo y vegetación

Jiménez-Moreno

Rodríguez-Laguna

Maurice

et al. 2019

Remexca

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Los indicadores ambientales son de suma importancia porque proveen información cuantitativa y cualitativa para evaluar el uso, disponibilidad y alteración de los recursos naturales. El presente ensayo tuvo como objetivo revisar del año 2006 a 2018 indicadores ambientales con un enfoque espacial y temporal, utilizados para evaluar la condición del ambiente. Posteriormente, se clasificó la información consultada en tres grupos principales de indicadores de agua, suelo y vegetación. Después se determinó las potencialidades de los diferentes métodos de indicadores ambientales, dentro de estos hallazgos relevantes se observó que cada metodología depende de la calidad de la información y de los objetivos de cada estudio. Dentro de las metodologías analizadas las de mayor relevancia por la precisión de sus resultados obtenidos, fueron los índices de vegetación y análisis multicriterio, ya que permite percibir explícitamente los parámetros de la zona que han sido modificados por actividades humanas. Se concluye que las metodologías de indicadores ambientales dependen del aspecto espacio-temporales y la calidad de los datos, así como del recurso natural a evaluar.

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Section: Indicadores Ambientales Espacio Temporalesunclassified

Section: Introductionunclassified

Análisis de indicadores ambientales espacio-temporales de agua, suelo y vegetación

Jiménez-Moreno

Rodríguez-Laguna

Maurice

et al. 2019

Remexca

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“…Meanwhile, the operation or control problem could be formulated as an optimization one. The optimal variables are obtained by minimizing the objective function, such as robust control, linear quadratic control and model predictive control (MPC) [23,24]. Ref.…”

Section: Introductionmentioning

confidence: 99%

Coordinated mechanical loads and power optimization of wind energy conversion systems with variable-weight model predictive control strategy

et al. 2019

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“…Applying non-linear multi-objective optimization, levelized cost of energy, unmet load fraction, wasted renewable energy and fuel consumption were considered as objectives and by applying TOPSIS the obtained Pareto frontier was assessed for optimal solutions. More recently, Pratama et al (2017) developed a bi-objective optimization model to find the best scenarios for electricity generation in Indonesia for 2050. The results were assessed through a simple normalization aggregation process considering eleven economic, environmental and social criteria to select the best possible solution.…”

Section: Introductionmentioning

confidence: 99%

Sustainable resource allocation for power generation: The role of big data in enabling interindustry architectural innovation

Chalvatzis

Malekpoor

Mishra

et al. 2019

Technological Forecasting and Social Change

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Economic, social and environmental requirements make planning for a sustainable electricity generation mix a demanding endeavour. Technological innovation offers a range of renewable generation and energy management options which require fine tuning and accurate control to be successful, which calls for the use of large-scale, detailed datasets. In this paper, we focus on the UK and use Multi-Criteria Decision Making (MCDM) to evaluate electricity generation options against technical, environmental and social criteria. Data incompleteness and redundancy, usual in large-scale datasets, as well as expert opinion ambiguity are dealt with using a comprehensive grey TOPSIS model. We used evaluation scores to develop a multi-objective optimization model to maximize the technical, environmental and social utility of the electricity generation mix and to enable a larger role for innovative technologies. Demand uncertainty was handled with an interval range and we developed our problem with multi-objective grey linear programming (MOGLP). Solving the mathematical model provided us with the electricity generation mix for every 5 minutes of the period under study. Our results indicate that nuclear and renewable energy options, specifically wind, solar, and hydro, but not biomass energy, perform better against all criteria indicating that interindustry architectural innovation in the power generation mix is key to sustainable UK electricity production and supply.

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Multi-objective optimization of a multiregional electricity system in an archipelagic state: The role of renewable energy in energy system sustainability

Cited by 48 publications

References 48 publications

Análisis de indicadores ambientales espacio-temporales de agua, suelo y vegetación

Análisis de indicadores ambientales espacio-temporales de agua, suelo y vegetación

Coordinated mechanical loads and power optimization of wind energy conversion systems with variable-weight model predictive control strategy

Sustainable resource allocation for power generation: The role of big data in enabling interindustry architectural innovation

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