Mapping the energy flexibility potential of single buildings equipped with optimally-controlled heat pump, gas boilers and thermal storage

D’Ettorre, Francesco; Роса, Маттиа Де; Conti, Paolo; Testi, Daniele; Finn, Donal

doi:10.1016/j.scs.2019.101689

Cited by 59 publications

(23 citation statements)

References 42 publications

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“…Further, the author conducts a brief review of various heat pump systems [10], analyzes their advantages and disadvantages, and proposes an acceptable option for effective use in the climate of the Moscow region.…”

Section: Methodsmentioning

confidence: 99%

Creation of an energy-efficient and comfortable country house using “passive” energy sources

Снежко

2019

E3S Web Conf.

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In the article the author considers one of the most important factors of life support – the creation of an energy-efficient and healthy microclimate country house through the use of complex engineering systems including the use of “passive” energy sources. Based on the results of the foreign and Russian market analysis of energy-efficient houses, the reasons for the low construction pace of such houses in Russia are estimated. A constructive engineering solution is proposed that can increase the efficiency using the modern heating, conditioning and humidification systems, thereby making them economically feasible and affordable for mass use.

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Section: Methodsmentioning

confidence: 99%

Creation of an energy-efficient and comfortable country house using “passive” energy sources

Снежко

2019

E3S Web Conf.

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“…However, cheaper and reliable storage devices, such as PCMs (Phase-change Materials), pressurized gas vessels, batteries and the electro-fuels injection into NG pipelines, have to be effectively embedded within the existing energy scenarios [17]. On the other hand, the recent literature, dealing with how to conveniently store heat in the residential sector, is strongly oriented to analyse the widespread electric heat pumps application for serving the end users in terms of Domestic Hot Water production (DHW as well [18]).…”

Section: Introductionmentioning

confidence: 99%

Implementation and Simulation of Real Load Shifting Scenarios Based on a Flexibility Price Market Strategy—The Italian Residential Sector as a Case Study

et al. 2021

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This work aims to evaluate the Flexibility Potential that a residential household can effectively provide to the public grid for participating in a Demand Response activity. In detail, by using 14 dwellings electrical data collection, an algorithm to simulate the Load Shifting activity over the daytime is implemented. That algorithm is applied to different scenarios having considered the addition of several technical constraints on the end users’ devices. In such a way, more realistic demand-side management actions are implemented in order to assess the Flexibility Potential deriving from the loads shifting. Basically, by performing simulations it is possible to investigate how the household appliances real operating conditions can reduce the theoretical Flexibility Potential extent. Starting from a Flexibility Price-Market-based Strategy, this work simulates the shifting over the day and night-time of some flexible loads, i.e., the shiftable and the storable ones. Specifically, all instants where load curtailments and enhancements occur over the typical day, the flexibility strategy effectiveness in terms of percentage, the power and energy that are potentially flexible, are evaluated. All the simulations are performed only for residential consumers to evaluate the actual dwellings Flexibility Potential in the absence of any electrical storage and production systems. The outcomes of these simulations show an average Theoretical Flexibility reduction, which is calculated as the fraction of appliances’ cycles shifting over the total ones, equal to 53%, instead of 66%; in a single dwelling, a maximum variation equal to 29% has been registered. In the end, the monthly average shifted energy per dwellings decreases from 27 to 18 kWh, entailing 32.5% off.

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“…The advent of electricity markets and the progress in Renewable Energy Sources (RES) have changed the nature of electricity production and consumption [1]. In order to increase the RES share and to use energy more effectively, energy system flexibility needs to be improved, for example, by means of enabling the demand-side management [2]. In this framework, electricity load prediction is required as an essential part in the energy industry to manage load fluctuations and aleatory RES [3].…”

Section: Introductionmentioning

confidence: 99%

Learning Curves: A Novel Approach for Robustness Improvement of Load Forecasting

Giola¹,

Danti²,

Magnani³

2021

The 7th International Conference on Time Series and Forecasting

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In the age of AI, companies strive to extract benefits from data. In the first steps of data analysis, an arduous dilemma scientists have to cope with is the definition of the ’right’ quantity of data needed for a certain task. In particular, when dealing with energy management, one of the most thriving application of AI is the consumption’s optimization of energy plant generators. When designing a strategy to improve the generators’ schedule, a piece of essential information is the future energy load requested by the plant. This topic, in the literature it is referred to as load forecasting, has lately gained great popularity; in this paper authors underline the problem of estimating the correct size of data to train prediction algorithms and propose a suitable methodology. The main characters of this methodology are the Learning Curves, a powerful tool to track algorithms performance whilst data training-set size varies. At first, a brief review of the state of the art and a shallow analysis of eligible machine learning techniques are offered. Furthermore, the hypothesis and constraints of the work are explained, presenting the dataset and the goal of the analysis. Finally, the methodology is elucidated and the results are discussed.

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Mapping the energy flexibility potential of single buildings equipped with optimally-controlled heat pump, gas boilers and thermal storage

Cited by 59 publications

References 42 publications

Creation of an energy-efficient and comfortable country house using “passive” energy sources

Creation of an energy-efficient and comfortable country house using “passive” energy sources

Implementation and Simulation of Real Load Shifting Scenarios Based on a Flexibility Price Market Strategy—The Italian Residential Sector as a Case Study

Learning Curves: A Novel Approach for Robustness Improvement of Load Forecasting

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