Optimal scheduling of time shiftable loads in a task scheduling based demand response program by symbiotic organisms search algorithm

Çakmak, Recep; Altaş, İsmail H.

doi:10.1109/sasg.2017.8356500

Cited by 12 publications

(5 citation statements)

References 24 publications

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“…The authors of Ref. [29] experimented with the symbiotic organisms search (SOS) and cuckoo search (CS) algorithms for the day-ahead forecasting of load scheduling based on consumer preferences (i.e., the time intervals commonly used for shiftable appliances) obtained after a public survey on 51 residential users and concluded that the SOS algorithm provides better results in terms of convergence and requires fewer parameters (i.e., no specific parameters are required other than maximum evaluation number and population size).…”

Section: Planning Strategiesmentioning

confidence: 99%

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Integrated Smart-Home Architecture for Supporting Monitoring and Scheduling Strategies in Residential Clusters

Stroia

Moga²,

Petreuş³

et al. 2022

Buildings

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The monitoring of power consumption and the forecasting of load profiles for residential appliances are essential aspects of the control of energy savings/exchanges at multiple hierarchical levels: house, house cluster, neighborhood, and city. External environmental factors (weather conditions) and inhabitants’ behavior influence power consumption, and their usage as part of forecasting activity may lead to added value in the estimation of daily-load profiles. This paper proposes a distributed sensing infrastructure for supporting the following tasks: the monitoring of appliances’ power consumption, the monitoring of environmental parameters, the generation of records for a database that can be used for both identifying load models and testing load-scheduling algorithms, and the real-time acquisition of consumption data. The hardware/software codesign of an integrated architecture that can combine the typical distributed sensing and control networks present in modern buildings (targeting user comfort) with energy-monitoring and management systems is presented. Methods for generating simplified piecewise linear (PWL) representations of the load profiles based on these records are introduced and their benefits compared with classic averaged representations are demonstrated for the case of peak-shaving strategies. The proposed approach is validated through implementing and testing a smart-meter node with wireless communication and other wired/wireless embedded modules, enabling the tight integration of the energy-monitoring system into smart-home/building-automation systems. The ability of this node to process power measurements with a programable granularity level (seconds/minutes/hours) at the edge level and stream the processed measurement results at the selected granularity to the cloud is identified as a valuable feature for a large range of applications (model identification, power saving, prediction).

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Section: Planning Strategiesmentioning

confidence: 99%

“…1 day [27,29] Power rate (kWh) of appliances Daily usage (hours) [28] Energy consumption for each customer (kWh) 15 min [30] Power consumption (W) of appliances 1 sec [31] Temperature, humidity, day of week Load power…”

Section: Referencementioning

confidence: 99%

Integrated Smart-Home Architecture for Supporting Monitoring and Scheduling Strategies in Residential Clusters

Stroia

Moga²,

Petreuş³

et al. 2022

Buildings

View full text Add to dashboard Cite

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“…If talking about these algorithms, the flow starts with the initial solution set and successive increments in runs with incorporation of various operators. Particle Swarm Optimization used to carried out hourly scheduling in grid [20], optimal battery energy storage schedule [21], demand response for residential consumers [22] and economic load dispatch problem [23], Cuckoo Search Optimization Algorithm used to carried out optimal scheduling of time shift-able loads [24,25], Spider Monkey Optimization (SMO) used for allocation of DGs for management of demand side [26], Bat Algorithm used to optimize the cost in home energy management system [27], Firefly Optimization used to construct the efficient DSM system [28] and in this flow, Fruit Fly Optimization used load balancing for the applications of EHR [29] and Grasshopper Optimization Algorithm [30] used to design an efficient energy management in office. Gravitational Search Algorithm used optimal scheduling of building users electricity consumption in [31] and unit commitment problem solved for electric vehicles using GSA in [32].…”

Section: Introductionmentioning

confidence: 99%

Impact of Divergence in BBO on Efficient Energy Strategy of Demand Side Management

Sharma

Saxena²,

Palwalia

2022

Technol Econ Smart Grids Sustain Energy

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Demand Response (DR) keeps up an important character in the growth of electricity generation with transmission and distribution in the phase of advanced grid automation. For future smart grid, basically two types of Demand Side Management strategies have been used with a number of shiftable or controllable devices. In this research article, two new variants of Biogeography Based Optimization (BBO) algorithm named as Iteration Control BBO and Pandemic BBO are proposed for solving the minimization problem and definitions of these variants have been made by change in migration control � ⃗ a vector. These two variants are indirectly support the principle of No Free Lunch theorem. The beauty of these variants is that they are reported the impact of divergence in BBO on efficient energy strategy of DSM. The simulation results reported in this paper claims that the used DSM techniques acquire financial savings, while lowering and shifting peak load.

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“…Thus, considering instead a continuous variable coupled with probability distribution function of actual demand, they propose a heuristic approach to manage the behavior of SLs in a micro-grid setting without employing any mathematical modelling whatsoever. The symbiotic organisms search algorithm is employed by the authors of [9] to optimally schedule the operation of SLs, though this is done for clusters, and thus no proper modelling is employed for individual behaviors. The limited additional literature that deals in some form with SLs either opts to continue using the traditional binary variables approach or employs different heuristic or clustering techniques that eliminate the need for any mathematical modelling.…”

Section: Introductionmentioning

confidence: 99%

A Tractable Approximation Approach to Deal with the Binary Nature of Shiftable Loads in Multi-Period Optimal Power Flow

Avramidis

Capitanescu

2020

2020 IEEE Texas Power and Energy Conference (TPEC)

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Distribution systems are currently in a transitional phase, as they transform from passive to active. In the coming years, customer participation is expected to drastically increase, as an additional option for maintaining reliable operation of distribution systems and for supporting the distribution and transmission system operators' growing needs. Amongst the available customer-side technologies, the shiftable load (SL) has one of the highest electricity demands and complexity levels; modelling its operation requires a multi-period optimal power flow (MP-OPF) approach. The SL is traditionally modelled in a mixed-integer nonlinear programming (MINLP) setting using many binary variables. However, for larger problem sizes, the MINLP approach lacks tractability. This work proposes a novel NLP approximation of the classic MINLP SL modelling that accurately mimics a SL at the optimum. The proposed approach is validated in a day-ahead deterministic multi-period OPF on two small distribution networks. It is demonstrated that when convergence is achieved, it occurs much faster than for the original formulation. The approach's sensitivity to the chosen level of accuracy and the initialization point are also explored in order to determine the best way to further complement it.

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Optimal scheduling of time shiftable loads in a task scheduling based demand response program by symbiotic organisms search algorithm

Cited by 12 publications

References 24 publications

Integrated Smart-Home Architecture for Supporting Monitoring and Scheduling Strategies in Residential Clusters

Integrated Smart-Home Architecture for Supporting Monitoring and Scheduling Strategies in Residential Clusters

Impact of Divergence in BBO on Efficient Energy Strategy of Demand Side Management

A Tractable Approximation Approach to Deal with the Binary Nature of Shiftable Loads in Multi-Period Optimal Power Flow

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