A model for renewable energy symbiosis networks in eco-industrial parks

Butturi, Maria Angela; Sellitto, Miguel Afonso; Lolli, Francesco; Balugani, Elia; Neri, Alessandro

doi:10.1016/j.ifacol.2020.12.2504

Cited by 11 publications

(7 citation statements)

References 4 publications

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“…Industrial symbiosis has been defined by Chertow et al [7] as a collective commitment including physical exchanges of materials, energy, and products between factories that have geographical proximity. In this context, Butturi et al [8] proposed a multi-objective optimization to evaluate energy symbiosis, that includes the integration of renewable energy sources within an eco-industrial park and considering both economic and environmental issues. They discuss three scenarios that provide individual company and park managers with relevant information, which support the decision-making regarding the economic sustainability and environmental impacts of energy symbiosis.…”

Section: Related Workmentioning

confidence: 99%

“…Among the works that have been published after this research [13], we find Jiang et al [9], which discuss in their paper the exchange of renewable energy between four parks with the integration of a storage system. Butturi et al [8] treat the case of renewable energy exchange between factories. In another study, Pedredro et al [12] deal with the case of collective self-consumption with the option of selling the surplus energy between 3 factories that share a photovoltaic installation.…”

Section: Related Workmentioning

confidence: 99%

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A New Strategy for Collective Energy Self-consumption in the Eco-Industrial Park: Mathematical Modeling and Economic Evaluation

Gribiss

Aghelinejad

Yalaoui

2022

Metaheuristics and Nature Inspired Computing

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Renewable energies are increasingly used around the world to replace fossil energy resources such as gas, coal, and oil sources in order to reduce greenhouse gases. Ecoindustrial parks promote the use and sharing of renewable energy sources between factories in a collective self-consumption framework. This article presents a new strategy of photovoltaic self-consumption in an eco-industrial park, that combines collective and individual self-consumption. This strategy has been compared with the classical configuration of self-consumption, in which factories do not share a common photovoltaic installation. Two mathematical models have been proposed and solved for these two configurations, the results show that the new strategy is more efficient than the classical configuration of individual self-consumption.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A New Strategy for Collective Energy Self-consumption in the Eco-Industrial Park: Mathematical Modeling and Economic Evaluation

Gribiss

Aghelinejad

Yalaoui

2022

Metaheuristics and Nature Inspired Computing

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“…It mimics the material cycle in ecosystem, which enables a symbiotic combination of industries sharing resources and exchanging by-products between different enterprises [12]. So, the waste generated in the upstream production process becomes the raw material for the downstream production [13], and the optimal allocation of resources is achieved. The approval of the construction of Guangxi Guigang National Demonstration Eco-industrial (Sugar) Park in August 2001 marked the official start of the construction of China's EIPs.…”

Section: Introductionmentioning

confidence: 99%

“…The whole process forms a collaborative chain network for the efficient transfer and use of energy and materials within or between companies. Consequently, the overall resource and energy use efficiency of the entire production process is improved, and the amount of waste and pollutants generated is reduced [13,21,22].…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Effects of Eco-Industrial Parks on Sulfur Dioxide and Carbon Dioxide Emissions—Estimation Based on Nonlinear DID

Cao

Dai

et al. 2023

Sustainability

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Eco-industrial parks (EIPs) promote the coordination of economic development and environmental protection. This paper uses the nonlinear DID method, with the data of 288 cities spanning from 2003–2019, to study the nonlinear effects of EIPs on SO2 and CO2 emissions, aiming to portray the nonlinear and heterogeneous characteristics of EIP’s effects. Meanwhile, this paper examines the effects of EIPs more accurately and completely. The main results are as follows: 1. EIPs can significantly reduce CO2 and SO2 emissions, but there is significant heterogeneity between the effects. 2. The effect of EIPs on SO2 and CO2 emissions is nonlinear. In addition, it shows significant nonlinear characteristics as the change of foreign investment and population density in cities. Therefore, it is important to consider these nonlinear characteristics when establishing and evaluating EIPs. This paper accurately identifies the nonlinear effects of EIPs and provides some suggestions for the future development of EIPs.

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“…Future works should focus more on the ability to capture sudden sharp increments of the load, as it is quite challenging work and there is still no literature on this area, and the prediction of negative energy consumption, such as in eco-parks where buildings receive and deliver energy to factories [45].…”

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confidence: 99%

A Novel Interval Energy-Forecasting Method for Sustainable Building Management Based on Deep Learning

Duan

2022

Sustainability

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Energy conservation in buildings has increasingly become a hot issue for the Chinese government. Compared to deterministic load prediction, probabilistic load forecasting is more suitable for long-term planning and management of building energy consumption. In this study, we propose a probabilistic load-forecasting method for daily and weekly indoor load. The methodology is based on the long short-term memory (LSTM) model and penalized quantile regression (PQR). A comprehensive analysis for a time period of a year is conducted using the proposed method, and back propagation neural networks (BPNN), support vector machine (SVM), and random forest are applied as reference models. Point prediction as well as interval prediction are adopted to roundly test the prediction performance of the proposed model. Results show that LSTM-PQR has superior performance over the other three models and has improvements ranging from 6.4% to 20.9% for PICP compared with other models. This work indicates that the proposed method fits well with probabilistic load forecasting, which could promise to guide the management of building sustainability in a future carbon neutral scenario.

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A model for renewable energy symbiosis networks in eco-industrial parks

Cited by 11 publications

References 4 publications

A New Strategy for Collective Energy Self-consumption in the Eco-Industrial Park: Mathematical Modeling and Economic Evaluation

A New Strategy for Collective Energy Self-consumption in the Eco-Industrial Park: Mathematical Modeling and Economic Evaluation

Nonlinear Effects of Eco-Industrial Parks on Sulfur Dioxide and Carbon Dioxide Emissions—Estimation Based on Nonlinear DID

A Novel Interval Energy-Forecasting Method for Sustainable Building Management Based on Deep Learning

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