Optimizing electricity consumption of buildings in a microgrid through demand response

Gonzalez, R. Morales; Torbaghan, Shahab Shariat; Gibescu, Madeleine; Cobben, J.F.G.; Bongaerts, Martijn; Nes-Koedam, M. de; Vermeiden, W.

doi:10.1109/ptc.2017.7980983

Cited by 5 publications

(5 citation statements)

References 4 publications

(6 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The thermodynamic behavior in buildings was also optimized by applying GA [101]. This optimization aimed at controlling the heating/cooling systems operation to minimize costs, considering renewable resources and hourly costs in the small MG.…”

Section: Heuristic and Meta-heuristic Methodsmentioning

confidence: 99%

A Review of Methodologies for Managing Energy Flexibility Resources in Buildings

Pedram,

Asadi,

Chenari

et al. 2023

Energies

View full text Add to dashboard Cite

The integration of renewable energy and flexible energy sources in buildings brings numerous benefits. However, the integration of new technologies has increased the complexity and despite the progress of optimization algorithms and technologies, new research challenges emerge. With the increasing availability of data and advanced modeling tools, stakeholders in the building sector are actively seeking a more comprehensive understanding of the implementation and potential benefits of energy optimization and an extensive up-to-date survey of optimization in the context of buildings and communities is missing in the literature. This study comprehensively reviews over 180 relevant publications on the management and optimization of energy flexibility resources in buildings. The primary objective was to examine and analyze prior research, with emphasis on the used methods, objectives, and scope. The method of content analysis was used to ensure a thorough examination of the existing literature on the subject. It was concluded that multi-objective optimization is crucial to enhance the utilization of flexible resources within individual buildings and communities. Moreover, the study successfully pinpointed key challenges and opportunities for future research, such as the need for accurate data, the complexity of the optimization process, and the potential trade-offs between different objectives.

show abstract

Section: Heuristic and Meta-heuristic Methodsmentioning

confidence: 99%

A Review of Methodologies for Managing Energy Flexibility Resources in Buildings

Pedram,

Asadi,

Chenari

et al. 2023

Energies

View full text Add to dashboard Cite

show abstract

“…Various DR programs have been modeled by a large number of studies. Some of the most popular DR programs, which have been implemented on the demand side, include building energy management [13], controlling cooling and heating demands [14], implementing new tari designs [15], and designing an Incentive-Based Program (IBP) [16]. Recently, some researchers have focused on the e ects of DRAs as an active player in modern power systems to apply DR programs in a lumped volume [17,18].…”

Section: Literature Review 121 Demand Response Aggregatorsmentioning

confidence: 99%

“…In order to force the minimum and maximum levels of SOC v;t , Relation (12) must be ful lled. In Relations (13) and (14), the binary variables u ch v;t and u disch v;t denote the states of charge and discharge, respectively. Constraint (15) enforces a restriction so that each EV can only be charged or discharged.…”

Section: Pro T 0 Evmentioning

confidence: 99%

Risk-based Cooperative Scheduling of Demand Response and Electric Vehicle Aggregators

2019

View full text Add to dashboard Cite

This paper proposes a new cooperative scheduling framework for Demand Response Aggregators (DRAs) and Electric Vehicle Aggregators (EVAs) in a day-ahead market. The proposed model implements the Information-Gap Decision Theory (IGDT) to optimize the scheduling problem of the aggregators, which guarantees to obtain the predetermined pro t by the aggregators. In the proposed model, the driving pattern of electric vehicle owners and the uncertainty of day-ahead prices are simulated via scenariobased and bi-level IGDT-based methods, respectively. The DRA provides DR from two demand-side management programs including Time-Of-Use (TOU) and reward-based DR. Then, the obtained DR is o ered in day-ahead markets. Furthermore, the EVAs not only meet the EV owners' demand economically, but also participate in the day-ahead market while are willing to set DR contracts with the DRA. The objective function is to maximize the total pro t of DR and EV aggregators by pursuing two di erent strategies to deal with price uncertainty, i.e., risk-seeking strategy and risk-averse strategy. The proposed plan is formulated in a risk-based approach and its validity is evaluated with respect to a case study with realistic data of electricity markets.

show abstract

“…Instead, a bottomup approach is required with a larger involvement of the regional distribution system operators and proactive end-users [3]. This can be achieved through different processes including Demand Response (DR) and Decentralized Energy Management (DEM) [4][5][6][7]. The concept of local energy markets is a key element to ensure the success of such concepts.…”

Section: Motivation and Backgroundmentioning

confidence: 99%

A market-based framework for demand side flexibility scheduling and dispatching

Torbaghan

Blaauwbroek

Kuiken

et al. 2018

Sustainable Energy, Grids and Networks

View full text Add to dashboard Cite

The massive integration of renewable energy resources increases the uncertainty with respect to realtime operation of the electrical systems. This transition introduces new challenges and opportunities for various entities that are involved in energy generation, transmission, distribution and consumption such as system operators and market participants in the wholesale electricity market. The concept of Decentralized Energy Management or Demand Response is emerging as one of the main approaches to resolve the violations of the network operation limits and to increase the flexibility of the system. This paper introduces an interaction framework for trading flexibility among proactive end-users in an economically efficient way. It proposes new market participants with their roles and functionalities, that will operate alongside the existing ones to ensure market efficiency and to enable secure operation of distribution grids. The proposed framework consists of a main mechanism called 'ahead-markets scheduling'. The ahead-markets scheduling includes two sub-mechanisms, day-ahead and intra-day, which are operated by a local flexibility market operator. The ahead-markets scheduling provides a trading platform that allows market participants to reflect their need(s) for flexibility and to monetize flexibility services in a fair and competitive manner. It enables flexibility trades which will eventually facilitate network management for the system operator.

show abstract

Optimizing electricity consumption of buildings in a microgrid through demand response

Cited by 5 publications

References 4 publications

A Review of Methodologies for Managing Energy Flexibility Resources in Buildings

A Review of Methodologies for Managing Energy Flexibility Resources in Buildings

Risk-based Cooperative Scheduling of Demand Response and Electric Vehicle Aggregators

A market-based framework for demand side flexibility scheduling and dispatching

Contact Info

Product

Resources

About