Direct quantification of multiple-source energy flexibility in a residential building using a new model predictive high-level controller

Ruusu, Reino; Cao, Sunliang; Delgado, Benjamin Manrique; Hasan, Ala

doi:10.1016/j.enconman.2018.11.026

Cited by 48 publications

(27 citation statements)

References 37 publications

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“…This difficulty becomes more apparent when the prediction is taken into account in an EMS. For example, an EMS covering energy flexibility conversion, routing and storage options was investigated in [32], where the modeling and control parts were carried out in TRNSYS and MATLAB separately. In addition, different EMSs for a community of buildings were studied in [11], sorted out into two parts: first, calculating each building heating energy demand by building simulation tools (TRNSYS or IDA ICE); then, using the data as input values into the programmed EMS in MATLAB.…”

Section: Research Motivation: Integrationmentioning

confidence: 99%

A Review of Mathematical Models of Building Physics and Energy Technologies for Environmentally Friendly Integrated Energy Management Systems

2022

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The Energy Management System (EMS) is an efficient technique to monitor, control and enhance the building performance. In the state-of-the-art, building performance analysis is separated into building simulation and control management: this may cause inaccuracies and extra operating time. Thus, a coherent framework to integrate building physics with various energy technologies and energy control management methods is highly required. This framework should be formed by simplified but accurate models of building physics and building energy technologies, and should allow for the selection of proper control strategies according to the control objectives and scenarios. Therefore, this paper reviews the fundamental mathematical modeling and control strategies to create such a framework. The mathematical models of (i) building physics and (ii) popular building energy technologies (renewable energy systems, common heating and cooling energy systems and energy distribution systems) are first presented. Then, it is shown how the collected mathematical models can be linked. Merging with two frequently used EMS strategies, namely rule-based and model predictive controls, is discussed. This work provides an extendable map to model and control buildings and intends to be a foundation for building researchers, designers and engineers.

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Section: Research Motivation: Integrationmentioning

confidence: 99%

A Review of Mathematical Models of Building Physics and Energy Technologies for Environmentally Friendly Integrated Energy Management Systems

2022

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“…The tag others applies to metrics that cannot be assigned to any of the three. For example, this category includes the flexibility [39], exergy [56], PV self-consumption [57], and carbon dioxide emissions [58] metrics.…”

Section: Key Performance Indicatorsmentioning

confidence: 99%

“…In some cases [2,57,[63][64][65][66], the energy consumption is provided as both total and partial: energy consumption is listed for the relevant components of the heating, ventilation, and air conditioning (HVAC) system or separately for space heating and cooling. Another approach is to compute the energy savings, which are quantified as a percentage (or improvement) of the consumption reduction compared to the specified reference, as in [18,36,47,58,[65][66][67][68][69][70][71][72][73]. Note that Refs.…”

Section: Energy Consumption Metricsmentioning

confidence: 99%

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Benchmarking Approaches for Assessing the Performance of Building Control Strategies: A Review

Ceccolini

Sangi

2022

Energies

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In the last few decades, researchers have shown that advanced building controllers can reduce energy consumption without negatively impacting occupants’ wellbeing and help to manage building systems, which are becoming increasingly complex. Nevertheless, the lack of benefit awareness and demonstration projects undermines stakeholders’ trust, justifying the reluctance to approve new controls in the industry. Therefore, it is necessary to support the development of controls through solid arguments testifying to the performance gain that can be achieved. However, the absence of standardized and systematic testing methods limits the generalization of results and the ability to make fair cross-study comparisons. This study presents an overview of the different benchmarking approaches used to assess control performance. Our goal is to highlight trends, limitations, and controversies through analytics to support the definition of best practices, which remains a widely discussed topic in this research area. We aim to focus on simulation-based benchmarking, which is regarded as a promising solution to overcome the time and cost requirements related to field or hardware-in-the-loop testing. We identify and investigate four key steps relating to virtual benchmarking: defining the key performance indicators, specifying the reference control, characterizing the test scenarios, and post-processing the results. This work confirmed the expected heterogeneity, underlined recurrent features with the help of analytics, and recognized limits and open challenges.

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“…The results showed that the increase in the degree of satisfaction of economic objectives led to increased CO 2 emissions. To take into account the complex relationship among energy systems in MESs, Ruusu et al [9] described a new energy management system for a variety of energy flexibility conversion technologies and storage options in buildings by means of a nonlinear optimization-based model predictive control (MPC) method.…”

Section: Introductionmentioning

confidence: 99%

Energy Flexibility as Additional Energy Source in Multi-Energy Systems with District Cooling

et al. 2021

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The integration of multi-energy systems to meet the energy demand of buildings represents one of the most promising solutions for improving the energy performance of the sector. The energy flexibility provided by the building is paramount to allowing optimal management of the different available resources. The objective of this work is to highlight the effectiveness of exploiting building energy flexibility provided by thermostatically controlled loads (TCLs) in order to manage multi-energy systems (MES) through model predictive control (MPC), such that energy flexibility can be regarded as an additional energy source in MESs. Considering the growing demand for space cooling, a case study in which the MPC is used to satisfy the cooling demand of a reference building is tested. The multi-energy sources include electricity from the power grid and photovoltaic modules (both of which are used to feed a variable-load heat pump), and a district cooling network. To evaluate the varying contributions of energy flexibility in resource management, different objective functions—namely, the minimization of the withdrawal of energy from the grid, of the total energy cost and of the total primary energy consumption—are tested in the MPC. The results highlight that using energy flexibility as an additional energy source makes it possible to achieve improvements in the energy performance of an MES building based on the objective function implemented, i.e., a reduction of 53% for the use of electricity taken from the grid, a 43% cost reduction, and a 17% primary energy reduction. This paper also reflects on the impact that the individual optimization of a building with a multi-energy system could have on other users sharing the same energy sources.

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Direct quantification of multiple-source energy flexibility in a residential building using a new model predictive high-level controller

Cited by 48 publications

References 37 publications

A Review of Mathematical Models of Building Physics and Energy Technologies for Environmentally Friendly Integrated Energy Management Systems

A Review of Mathematical Models of Building Physics and Energy Technologies for Environmentally Friendly Integrated Energy Management Systems

Benchmarking Approaches for Assessing the Performance of Building Control Strategies: A Review

Energy Flexibility as Additional Energy Source in Multi-Energy Systems with District Cooling

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