Development of a self-adapting intelligent system for building energy saving and context-aware smart services

Byun, Jinsung; Park, Sehyun

doi:10.1109/tce.2011.5735486

Cited by 84 publications

(14 citation statements)

References 18 publications

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“…Therefore, the last two terms in the Lagrangian function (16) are constant which would be dropped. The community-aggregated load can be replaced by residential and communal loads using (14).…”

Section: Community-aggregated Model For Optimal Load Schedulingmentioning

confidence: 99%

“…In the optimal load case, the utility load at hours 6-23 is reduced by the adjustable loads, storage systems, and local generation. The residential and community storage systems are charged at hours 1-4 and discharged at hours [16][17][18][19]. The charging of storage systems increases the utility load at low price hours 1-4.…”

Section: Community-aggregated Loadmentioning

confidence: 99%

“…The community storage is charged at hours 3-6 instead of 1-4 which reduces the utility load. The storage is discharged at hours [16][17][18][19]. In addition, 75 residential storage systems are charged at hours 3-6 instead of 1-4 to reduce the utility load which was originally violated at hours 1 and 2.…”

Section: Community-aggregated Loadmentioning

confidence: 99%

“…Compared to purely data-driven methods, this paper introduced a prior-knowledge-based modeldriven framework. In [16], a self-adapting intelligent system was used for providing building control and energy saving services. This system consists of a gateway (selfadapting intelligent gateway) and a sensor (self-adapting intelligent sensor).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Optimal Hourly Scheduling of Community-Aggregated Electricity Consumption

Khodaei¹,

Shahidehpour²,

Choi³

2013

Journal of Electrical Engineering and Technology

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-This paper presents the optimal scheduling of hourly consumption in a residential community (community, neighborhood, etc.) based on real-time electricity price. The residential community encompasses individual residential loads, communal (shared) loads, and local generation. Community-aggregated loads, which include residential and communal loads, are modeled as fixed, adjustable, shiftable, and storage loads. The objective of the optimal load scheduling problem is to minimize the community-aggregated electricity payment considering the convenience of individual residents and hourly community load characteristics. Limitations are included on the hourly utility load (defined as community-aggregated load minus the local generation) that is imported from the utility grid. Lagrangian relaxation (LR) is applied to decouple the utility constraint and provide tractable subproblems. The decomposed subproblems are formulated as mixed-integer programming (MIP) problems. The proposed model would be used by community master controllers to optimize the utility load schedule and minimize the community-aggregated electricity payment. Illustrative optimal load scheduling examples of a single resident as well as an aggregated community including 200 residents are presented to show the efficiency of the proposed method based on real-time electricity price. Keywords

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Section: Community-aggregated Model For Optimal Load Schedulingmentioning

confidence: 99%

Section: Community-aggregated Loadmentioning

confidence: 99%

Section: Community-aggregated Loadmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal Hourly Scheduling of Community-Aggregated Electricity Consumption

Khodaei¹,

Shahidehpour²,

Choi³

2013

Journal of Electrical Engineering and Technology

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“…스마트 조명은 인공조명의 자동제어를 통해 사용자의 편의 및 작업능률 을 향상시키는데 그 목적을 두고 있다 [9][10][11]. 스마트 조명 의 제어방식은 사용자 입력에 의한 스케줄 기반의 제어 방식과 센서를 통해 사용자 위치 및 행위 등의 상황을 판 별한 후 이에 따라 적합한 조명환경을 제공하는 방식으 로 구분된다 [12][13]. 그 중 스케줄 기반의 스마트 조명은 사용자의 생활패턴이 항시 일정한 경우 적용 가능한 반 면, 예외 상황이 빈번이 발생되는 생활환경에는 적합하지 않다 [1].…”

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An Implementation of Lighting Control System using Interpretation of Context Conflict based on Priority

Seo¹,

Kwon²,

Lim³

2016

Journal of Internet Computing and Services

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The current smart lighting is shaped to offer the lighting environment suitable for current context, after identifying user's action and location through a sensor. The sensor-based context awareness technology just considers a single user, and the studies to interpret many users' various context occurrences and conflicts lack. In existing studies, a fuzzy theory and algorithm including ReBa have been used as the methodology to solve context conflict. The fuzzy theory and algorithm including ReBa just avoid an opportunity of context conflict that may occur by providing services by each area, after the spaces where users are located are classified into many areas. Therefore, they actually cannot be regarded as customized service type that can offer personal preference-based context conflict. This paper proposes a priority-based LED lighting control system interpreting multiple context conflicts, which decides services, based on the granted priority according to context type, when service conflict is faced with, due to simultaneous occurrence of various contexts to many users. This study classifies the residential environment into such five areas as living room, 'bed room, study room, kitchen and bath room, and the contexts that may occur within each area are defined as 20 contexts such as exercising, doing makeup, reading, dining and entering, targeting several users. The proposed system defines various contexts of users using an ontology-based model and gives service of user oriented lighting environment through rule based on standard and context reasoning engine. To solve the issue of various context conflicts among users in the same space and at the same time point, the context in which user concentration is required is set in the highest priority. Also, visual comfort is offered as the best alternative priority in the case of the same priority. In this manner, they are utilized as the criteria for service selection upon conflict occurrence.

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A control and decision system for smart buildings using wireless sensor and actuator networks

Farias

Soares

Pìrmez

et al. 2014

Trans. Emerging Tel. Tech.

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A research field that makes use of information and communication technologies to provide solutions to contemporaneous environmental challenges such as greenhouse gas emissions and global warming is the 'smart building' field. The use of wireless sensor and actuator networks (WSANs) emerges as an alternative for the use of information and communication technologies in the smart buildings. However, most of smart building applications make use of centralised architectures with sensing nodes transmitting messages to a base station wherein, effectively, the control and decision processes happen. In this context, we present CONDE, a decentralised CONtrol and DEcision-making system for smart building applications using WSANs. CONDE main contributions are as follows: (i) the decentralisation of the control and decision-making processes among WSAN nodes, saving energy of both the WSAN and the building; (ii) the integration of applications through sharing the sensed data and chaining decisions between applications within the WSAN, also saving energy of both the WSAN and the building; and (iii) the provision of a consensual multilevel decision that takes into account the cooperation among nodes to have a broader view of the monitored building. Performed experiments have shown CONDE gains in terms of the following: (i) response time; (ii) system efficiency; and (iii) energy savings from the network and the building.

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Development of a self-adapting intelligent system for building energy saving and context-aware smart services

Cited by 84 publications

References 18 publications

Optimal Hourly Scheduling of Community-Aggregated Electricity Consumption

Optimal Hourly Scheduling of Community-Aggregated Electricity Consumption

An Implementation of Lighting Control System using Interpretation of Context Conflict based on Priority

A control and decision system for smart buildings using wireless sensor and actuator networks

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