Multi-objective optimization of multi-energy complementary integrated energy systems considering load prediction and renewable energy production uncertainties

Liu, Zhiqiang; Cui, Yanping; Wang, Jiaqiang; Yue, Chang; Agbodjan, Yawovi Souley; Yang, Yu

doi:10.1016/j.energy.2022.124399

Cited by 83 publications

(18 citation statements)

References 27 publications

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“…Our work is also related to the literature on multi-objective optimization. Hong et al, 2013 andLiu et al, 2022 took multiple objectives, such as the economy and environment of the system, into account and used a genetic algorithm to solve the optimization problem. However, the results obtained by the meta-heuristic are not optimal, and the calculation process is complicated.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-energy dispatching for uncertainty EV demand: A simulation approach

Dai²,

Zhang³

et al. 2022

Front. Energy Res.

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Uncertainty and randomness in demand and supply bring significant challenges to the stable operation of the grid and the scheduling planning of multi-energy sources. To solve these challenges, we propose and analyze a multi-energy dispatching model which minimizes the total cost and enhances the efficiency of supplying power. Specifically, we design matching algorithms that simulate an appropriately scaled sequence of stochastic EV demand. We also analyze four different energy dispatching scenarios proving that the scheduling model and the multi-energy synergistic microgrid structure can bring higher efficiency and lower costs. Our main contribution is using a simulation approach to take EVs into account for demand-side uncertainty, which significantly improves the efficiency of grid dispatch.

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Section: Literature Reviewmentioning

confidence: 99%

Multi-energy dispatching for uncertainty EV demand: A simulation approach

Dai²,

Zhang³

et al. 2022

Front. Energy Res.

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“…Connections with outdoor recreation • designing multifunctional areas for climate resilience and recreation [27] • the role of NBSs in shaping multifunctional land use [28] • multifunctional outdoor recreation and flood management in flood-prone areas [29] Sustainability • ways in which water management can improve sustainability [30] • using ecosystem services for greater sustainability [31] • using NBSs for economic sustainability in cities [32] Ecosystem services • using technology to expand ecosystem services [20] • using ecosystem services to support nutrient cycling food supply and resource allocation [33] • ways in which ecosystem services can contribute to sustainability [31] • using ecosystem services for cultural purposes and nature recreation [34] • using ecosystem services for wastewater management [35] • using technology to improve ecosystem services and resilience [36] • using urban and spatial planning to improve or extend the resilience of urban ecosystems (how can we improve ecosystem resilience through urban and spatial planning strategies?) [37] Water management • improving wastewater treatment by using the functions of NBSs [38] • forecasting the quantity of refuse and developing an intelligent system within water treatment facilities to facilitate immediate anticipatory management of sewage treatment [39] • creating an intelligent microgrid for waste management [40] • leveraging the Internet of Things (IoT) for the purpose of effectively handling domestic waste [41] • using ecosystem services for wastewater treatment [42] Mitigate and absorb carbon dioxide • investigating crucial elements in the cultivation of algal biomass and lipids for the generation of sustainable energy sources [43] • predicting future biomass yields of crops [44] • investigating the impact of climate change on carbon flux as a major driver of algal biofuel production [45] • technology potential for carbon uptake from the air and other resources [46] • prediction of renewable energy production [47] • accurate prediction of CO2 emissions [48] Flooding • the floating city and the use of NBSs to improve performance [49] • the role of ecosystem services in mitigating or preventing flooding…”

Section: Research Gap Connectionsmentioning

confidence: 99%

Nature-Based Solutions and Climate Resilience: A Bibliographic Perspective through Science Mapping Analysis

Vazin,

Chan,

Hanaee

et al. 2024

Buildings

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Currently, urban areas are confronting considerable challenges stemming from climate change. These challenges possess the potential to have profound implications for the well-being of residents, their means of making a living, and their own assets. Consequently, it is imperative to identify effective solutions that mitigate these effects on the urban environment. Nature-based solutions (NBSs), involving the utilization of natural resources and ecosystem services to alleviate the effects of climate change, have the potential of enhancing our capacity to develop cities that are more resistant to these challenges. To this end, this paper aims to extract some bibliographic data from available research articles on NBSs and climate resilience sought from the common search engines of Scopus, Web of Science, and Lens Base, and then the RStudio version 2022.12.00+353, VoSviewer version 1.6.20, and Biblioshiny-Bibliometrics version 2017 software tools were adopted to collate and analyze the literature data through science mapping analysis. In doing so, it was advocated that these two topics have not been extensively studied in their relationship to each other and that there is a large extent of existing knowledge gaps, the filling of which can foster the development of these ideas and thus help develop our cities in combating against climate change. Exploring the effectiveness of NBSs in boosting climate resilience is a critical research gap. More empirical studies are envisaged to assess the scalability and transferability of those effective NBSs in various regions or countries. Another research gap exists in comprehending the long-term effects on ecosystem services and community welfare. Research on socio-economic advantages, trade-offs, and unintended outcomes is essential for making well-informed decisions when applying various NBSs worldwide.

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“…With the development of the economy and the improvement in living standards, people have a higher and higher demand for indoor air environments [ 4 , 5 ]. The application of HVAC systems in buildings is also becoming increasingly widespread [ 6 , 7 , 8 ]. Many data-driven techniques have been proposed in order to improve the performance of HVAC systems [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Study on Sensor Fault-Tolerant Control for Central Air-Conditioning Systems Using Bayesian Inference with Data Increments

Li,

Wang,

Liu

et al. 2024

Sensors

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A lack of available information on heating, ventilation, and air-conditioning (HVAC) systems can affect the performance of data-driven fault-tolerant control (FTC) models. This study proposed an in situ selective incremental calibration (ISIC) strategy. Faults were introduced into the indoor air (Ttz1) thermostat and supply air temperature (Tsa) and chilled water supply air temperature (Tchws) sensors of a central air-conditioning system. The changes in the system performance after FTC were evaluated. Then, we considered the effects of the data quality, data volume, and variable number on the FTC results. For the Ttz1 thermostat and Tsa sensor, the system energy consumption was reduced by 2.98% and 3.72% with ISIC, respectively, and the predicted percentage dissatisfaction was reduced by 0.67% and 0.63%, respectively. Better FTC results were obtained using ISIC when the Ttz1 thermostat had low noise, a 7-day data volume, or sufficient variables and when the Tsa and Tchws sensors had low noise, a 14-day data volume, or limited variables.

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Multi-objective optimization of multi-energy complementary integrated energy systems considering load prediction and renewable energy production uncertainties

Cited by 83 publications

References 27 publications

Multi-energy dispatching for uncertainty EV demand: A simulation approach

Multi-energy dispatching for uncertainty EV demand: A simulation approach

Nature-Based Solutions and Climate Resilience: A Bibliographic Perspective through Science Mapping Analysis

Study on Sensor Fault-Tolerant Control for Central Air-Conditioning Systems Using Bayesian Inference with Data Increments

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