A survey on residential Demand Side Management architecture, approaches, optimization models and methods

Esther, B. Priya; Kumar, Kaushal

doi:10.1016/j.rser.2015.12.282

Cited by 237 publications

(126 citation statements)

References 55 publications

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“…A smart home can be composed of a storage system, sensors such as temperature or presence sensors, and switches used to turn on/off appliances [15][16][17][18]. Moreover, smart plugs are used to control the AC loads.…”

Section: System Modelingmentioning

confidence: 99%

The Fuzzy Logic Method to Efficiently Optimize Electricity Consumption in Individual Housing

2017

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Electricity demand shifting and reduction still raise a huge interest for end-users at the household level, especially because of the ongoing design of a dynamic pricing approach. In particular, end-users must act as the starting point for decreasing their consumption during peak hours to prevent the need to extend the grid and thus save considerable costs. This article points out the relevance of a fuzzy logic algorithm to efficiently predict short term load consumption (STLC). This approach is the cornerstone of a new home energy management (HEM) algorithm which is able to optimize the cost of electricity consumption, while smoothing the peak demand. The fuzzy logic modeling involves a strong reliance on a complete database of real consumption data from many instrumented show houses. The proposed HEM algorithm enables any end-user to manage his electricity consumption with a high degree of flexibility and transparency, and "reshape" the load profile. For example, this can be mainly achieved using smart control of a storage system coupled with remote management of the electric appliances. The simulation results demonstrate that an accurate prediction of STLC gives the possibility of achieving optimal planning and operation of the HEM system.

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Section: System Modelingmentioning

confidence: 99%

The Fuzzy Logic Method to Efficiently Optimize Electricity Consumption in Individual Housing

2017

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“…Consequently, the storage unit is charged (P B < 0, bold black time trend in Figure 5b) with the PV surplus (when the red line overpasses the blue line in Figure 5a) until the maximum admitted SoC threshold SoC M is reached (Figure 5c) and according to the admitted charging rate P Cmax evaluated as in Equation (12) and graphically reported in Figure 5b (dotted line). Similarly, the BESS discharges during the evening and the night to supply the load up to the minimum SoC value SoC m and taking into account the maximum discharging rate P Dmax (dashed line in Figure 5b) evaluated in Equation (11). In the case of charge, stand-by, or very weak discharge, the internal temperature T B (Figure 5d) decreases according to Equation (10) and the battery heater is switched on to avoid over-cooling (Figure 5e) if T B is close to T m .…”

Section: Parameter (Unit Of Measure) Valuementioning

confidence: 99%

“…Through this temperature characterization, the minimum admitted discharging time duration T Dm (t) (h) is computed by knowing the battery internal temperature T B (t) and the maximum admitted threshold T M . Consequently, the maximum admitted discharging power P Dmax (t) at the t-th time instant is obtained as the most binding among several operational constraints, synthetically represented in Equation (11). The parameter P D,r is the BESS rated power in the discharging phase.…”

mentioning

confidence: 99%

Application of a Simplified Thermal-Electric Model of a Sodium-Nickel Chloride Battery Energy Storage System to a Real Case Residential Prosumer

Bignucolo

Coppo

Crugnola³

et al. 2017

Energies

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Abstract:Recently, power system customers have changed the way they interact with public networks, playing a more and more active role. End-users first installed local small-size generating units, and now they are being equipped with storage devices to increase the self-consumption rate. By suitably managing local resources, the provision of ancillary services and aggregations among several end-users are expected evolutions in the near future. In the upcoming market of household-sized storage devices, sodium-nickel chloride technology seems to be an interesting alternative to lead-acid and lithium-ion batteries. To accurately investigate the operation of the NaNiCl 2 battery system at the residential level, a suitable thermoelectric model has been developed by the authors, starting from the results of laboratory tests. The behavior of the battery internal temperature has been characterized. Then, the designed model has been used to evaluate the economic profitability in installing a storage system in the case that end-users are already equipped with a photovoltaic unit. To obtain realistic results, real field measurements of customer consumption and solar radiation have been considered. A concrete interest in adopting the sodium-nickel chloride technology at the residential level is confirmed, taking into account the achievable benefits in terms of economic income, back-up supply, and increased indifference to the evolution of the electricity market.

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“…The solar system is known by a reliable power during a critical periods as at night. In this regard, the integration of storage components is necessary for continuous power supply and to provide the required powerfor the electrical load [6]- [7]. To solve the problems of power demand, several configurations have been proposed and have been integrated same alternative energy sources such as fuel cells, Ultra-Capacitor, electrolyte, hydrogen tank storage [8]- [10].…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Power Management Investigation for Stand-alone Hybrid System Using Short-time Energy Storage

Sami¹

2017

IJPEDS

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Stand-alone Hybrid systems become appreciating issues that ensure the required electricity to consumers. The development of a stand-alone Hybrid system becomes a necessity for multiple applications The enhance energy security. To achieve this objective, we have proposed an accurate dynamic model using Multi-Agent System (MAS) in which a solar energy System (SES) serves as the main load supply, an energy Backup System (ERS) is based on a fuel cell and Electrolyzer for long-term energy storage and an Ultra Capacitor (UCap) storage system deployed as a short-time storage. To cooperate with all systems, an Intelligent Power Management (IPM) based on a specific MAS is included. Thus, to prove the performance of the system, we tested and simulated it using the Matlab/Simulink environment.

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A survey on residential Demand Side Management architecture, approaches, optimization models and methods

Cited by 237 publications

References 55 publications

The Fuzzy Logic Method to Efficiently Optimize Electricity Consumption in Individual Housing

The Fuzzy Logic Method to Efficiently Optimize Electricity Consumption in Individual Housing

Application of a Simplified Thermal-Electric Model of a Sodium-Nickel Chloride Battery Energy Storage System to a Real Case Residential Prosumer

An Intelligent Power Management Investigation for Stand-alone Hybrid System Using Short-time Energy Storage

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