Optimal management of energy sharing in a community of buildings using a model predictive control

Vand, Behrang; Ruusu, Reino; Hasan, Ala; Delgado, Benjamin Manrique

doi:10.1016/j.enconman.2021.114178

Cited by 41 publications

(12 citation statements)

References 49 publications

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“…Building simulation tools are mature techniques to analyze the building performance under different targets; for example, energy consumption and thermal comfort. Several building simulation tools (e.g., TRNSYS, En-ergyPlus, IDA-ICE) are widely developed to provide a precise model for the buildings and technologies [11,[28][29][30][31]. However, all building simulation tools face a similar situation when integrated with an EMS: they are only able to account for the modeling of buildings (and sometimes also a few standard equipment), but they cannot be merged in a seamless way with the EMS based on different control strategies.…”

Section: Research Motivation: Integrationmentioning

confidence: 99%

“…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. This strategy to undertake the simulation tools for building modeling and the programming tools for executing EMS strategies separately brings difficulties and challenges in setting up a framework, which increases the run time and may cause inaccuracies through the final results.…”

Section: Research Motivation: Integrationmentioning

confidence: 99%

“…Different energy technologies can be integrated with it. The energy balance equation in each layer is expressed as follows: The size and configuration of this tank is similar to that presented in [11]. The top layer provides DHW for the occupants, and the lower layer is connected to Heating, Ventilation and Air Conditioning (HVAC) for space heating.…”

Section: Hot Water Storage Tankmentioning

confidence: 99%

“…The factors that influence the COP of a GSHP system include the type of ground heat exchangers (horizontal or vertical), soil condition, local climate, building load characteristics and system design and control optimization [65]. Again, the COP has been modeled as a constant [11], or dependent on meteorological information, such as solar radiation and the ambient temperature [127]. A field study conducted in hot summer and cold winter areas in China [128] indicated that the COP ranges from 1.95 to 4.35 depending on various outside conditions.…”

Section: Ground Source Heat Pumpmentioning

confidence: 99%

“…Environmentally friendly technologies with a high Coefficient of Performance (COP)for example, heat pumps and Combined Heating and Power (CHP)-have also been increasingly studied and developed [11,12]. These devices can be combined with waterbased energy distribution systems that allow for low-temperature heating [13] and hightemperature cooling [14] to cover the heating and cooling demand of the buildings.…”

Section: Introductionmentioning

confidence: 99%

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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%

Section: Research Motivation: Integrationmentioning

confidence: 99%

Section: Hot Water Storage Tankmentioning

confidence: 99%

Section: Ground Source Heat Pumpmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

2022

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Overview of the Optimal Operation of Heat and Electricity Incorporated Networks

Dorahaki

Mobasheri

Zadsar

et al. 2022

Coordinated Operation and Planning of Modern Heat and Electricity Incorporated Networks

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Energy‐Sharing Economy with Renewable Integration and Management in Communities—a State‐of‐the‐Art Review

Zhou

2024

Adv Energy and Sustain Res

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Climate change and extreme weather events impose urgent necessities on distributed energy systems with energy flexibility and resilience to survive the district power supply systems. Compared to centralized energy systems, distributed energy systems show more superiorities in power shifting, fast demand response, regional energy allocations, and so on. However, electrification transformation‐ enabled flexible energy sharing, smart energy integration, and advanced management are still in their infancy stages, with unsolved but urgent issues, like large‐scale energy system planning and optimization, energy trading and pricing mechanisms, so on. In this study, energy‐sharing economy with renewable integration and management in communities has been comprehensively reviewed. The “source–grid–load–storage” framework has been implemented on district energy systems with complex relationships among the energy supply–storage–transmission–distribution chain. Roles of energy sharing, integration, and management on energy system sustainability have been provided. Considering widely installed large‐scale renewable energy systems, planning and optimization platforms and tools are provided to guide the distributed/centralized system planning and accurate capacity sizing. Results showed that, multi‐directional power interactions with electrification in buildings and E‐mobility spatiotemporal energy sharing and smart grids enable high renewable penetration, fast power response, energy supply reliability, etc. Unlike traditional fossil fuel‐based power plants, distributed renewable‐supported energy systems (like BIPVs, electric vehicles, etc.) enable emerging energy sharing, integration, and management for energy flexibility and resilience with fast response and energy survivals. Roles of advanced energy include power shifting, fast demand response, regional energy allocations, and so on. Electricity market liberalization can incentivize multi‐stakeholders’ proactivity and market vitality for distributed renewable energy spatiotemporal microgrids. Dynamic energy pricing for the shared power is dependent on the supply–demand relationship, and cost–benefit allocations among different stakeholders need to be investigated for justice and fairness. To avoid performance over or underestimations, advanced approaches are highly necessary for large‐scale energy system planning and optimization. Research results can pave paths for upcoming studies in urban energy system planning, design, and optimization with high energy efficiency and low carbon emissions through joint collaborations from highly economically incentivized participators.

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Optimal management of energy sharing in a community of buildings using a model predictive control

Cited by 41 publications

References 49 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

Overview of the Optimal Operation of Heat and Electricity Incorporated Networks

Energy‐Sharing Economy with Renewable Integration and Management in Communities—a State‐of‐the‐Art Review

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