Combined vs separate heat and power production – Primary energy comparison in high renewable share contexts

Noussan, Michel; Jarre, Matteo; Roberto, R.; Russolillo, Daniele

doi:10.1016/j.apenergy.2018.01.026

Cited by 35 publications

(10 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is not economic to operate CHP only for heat. Noussan et al [98] reported the similar conclusion for Italian context with high penetration of renewables in the electricity mix. Other heat sources, including waster heat, heat from heat pumps (using wind power), biomass boilers, and solar district heating plants, will become more and more interesting for district heating networks.…”

Section: Integration With Other Energy Technologiessupporting

confidence: 54%

Large-scale solar district heating plants in Danish smart thermal grid: Developments and recent trends

Tian

Zhang

Deng

et al. 2019

Energy Conversion and Management

145

View full text Add to dashboard Cite

Large solar collector fields are very popular in district heating system in Denmark, even though the solar radiation source is not favourable at high latitudes compared to many other regions. Business models for large solar heating plants in Denmark has attracted much attention worldwide. Denmark is not only the biggest country in both total installed capacities and numbers of large solar district heating plants, but also is the first and only country with commercial market-driven solar district heating plants. By the end of 2017, more than 1.3 million m 2 solar district heating plants are in operation in Denmark. Furthermore, more than 70 % of the large solar district heating plants worldwide are constructed in Denmark. Based on the case of Denmark, this study reviews the development of large solar district heating plants in Denmark since 2006. Success factors for Danish experiences was summarized and discussed. Novel design concepts of large solar district heating plants are also addressed to clarify the future development trend. Potential integration of large solar district heating plants with other renewable energy technologies are discussed. This paper can provide references to potential countries that want to exploit the market for solar district heating plants. Policymakers can evaluate the advantages and disadvantages of solar district heating systems in the national energy planning level based on the know-how and experiences from Denmark.

show abstract

Section: Integration With Other Energy Technologiessupporting

confidence: 54%

Large-scale solar district heating plants in Danish smart thermal grid: Developments and recent trends

Tian

Zhang

Deng

et al. 2019

Energy Conversion and Management

145

View full text Add to dashboard Cite

show abstract

“…The development of computer technology provides a more systematic data analysis model for the development of various industries, and these data analysis models can make up for the deficiencies in the traditional data analysis process, and then consider a variety of influencing factors. The improvement of the accuracy of the final analysis results provides a positive impact [5]. In this study, the author will use the current status of energy use in Guangdong Province of China as the research object, and then the author uses the DIP-REM model to predict the energy demand in Guangdong Province of China.…”

Section: Introducingmentioning

confidence: 99%

Analysis of Guangdong Energy Demand Forecast Based on DIP-REM Model

Zhang

2021

E3S Web Conf.

View full text Add to dashboard Cite

Computer data mining technology has a positive impact on the accurate prediction of China's energy demand. In order to effectively alleviate the energy crisis that China is currently facing, and further forecast the energy demand, it will provide an active driving force for the sustainable economic development of our country in the future. In this study, the authors studied the current energy use trends in China, and then the authors used the DIP-REM model to predict their future development needs based on a study of the use of energy resources in Guangdong Province. This model can accurately predict the future energy expansion value of Guangdong Province. The research aims to provide a reference for related research on China's energy demand forecast.

show abstract

“…Disregarding uncertainty effects on the system design and operation could lead to suboptimal solutions, in which the impaired economic and energy performances would not provide longstanding economic viability nor reduce financial risks. Nevertheless, most of the research about the optimal design of cogeneration and polygeneration systems still relies on deterministic approaches that cannot capture the stochastic nature of uncertain design parameters [1,2,[10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Stochastic optimization of trigeneration systems for decision-making under long-term uncertainty in energy demands and prices

Onishi

Antunes

Fraga

et al. 2019

Energy

View full text Add to dashboard Cite

Combined heating, cooling and power (CHCP) systems, so-called trigeneration, are widely accepted as more energy-efficient and environment-friendly alternatives to traditional separate energy generation. Nevertheless, the tasks of synthesis and optimization of trigeneration systems are strongly hampered by the long-term uncertainties in energy demands and prices. In this work, we introduce a new scenariobased model for the stochastic optimization of CHCP systems under uncertainty in several process design parameters. Energy generation operators are proposed to ensure the optimal sizing and operation of each equipment in each optimization scenario. Our main objective is to enhance energy efficiency by synthesizing the most cost-effective CHCP system able to operate in wide-ranging scenarios of energy demands and prices. For this purpose, uncertain design parameters are modelled as a set of loading and pricing scenarios with given probability of occurrence. The set of scenarios contains correlated energy prices described through a multivariate Normal distribution, which are generated via a Monte Carlo sampling technique with symmetric correlation matrix. The resulting stochastic multiscenario MINLP model is solved to global optimality by minimizing the expected total annualized cost. A thorough economic risk analysis underlines the effectiveness of the proposed methodology. This systematic approach represents a useful tool to support the decision-making process regarding system efficiency and robustness.

show abstract

Combined vs separate heat and power production – Primary energy comparison in high renewable share contexts

Cited by 35 publications

References 39 publications

Large-scale solar district heating plants in Danish smart thermal grid: Developments and recent trends

Large-scale solar district heating plants in Danish smart thermal grid: Developments and recent trends

Analysis of Guangdong Energy Demand Forecast Based on DIP-REM Model

Stochastic optimization of trigeneration systems for decision-making under long-term uncertainty in energy demands and prices

Contact Info

Product

Resources

About