scholarly journals Towards Efficient Resource Utilization Exploiting Collaboration between HPF and 5G Enabled Energy Management Controllers in Smart Homes

2018 ◽  
Vol 10 (10) ◽  
pp. 3592 ◽  
Author(s):  
Rasool Bakhsh ◽  
Nadeem Javaid ◽  
Itrat Fatima ◽  
Majid Khan ◽  
Khaled. Almejalli

The influence of Information Communication and Technology (ICT) in power systems necessitates Smart Grid (SG) with monitoring and real-time control of electricity consumption. In SG, huge requests are generated from the smart homes in residential sector. Thus, researchers have proposed cloud based centralized and fog based semi-centralized computing systems for such requests. The cloud, unlike the fog system, has virtually infinite computing resources; however, in the cloud, system delay is the challenge for real-time applications. The prominent features of fog are; awareness of location, low latency, wired and wireless connectivity. In this paper, the impact of longer delay of cloud in SG applications is addressed. We proposed a cloud-fog based system for efficient processing of requests coming from the smart homes, their quick response and ultimately reduced cost. Each smart home is provided with a 5G based Home Energy Management Controller (HEMC). Then, the 5G-HEMC communicates with the High Performance Fog (HPF). The HPFs are capable of processing energy consumers’ huge requests. Virtual Machines (VMs) are installed on physical systems (HPFs) to entertain the requests using First Come First Service (FCFS) and Ant Colony Optimization (ACO) algorithms along with Optimized Response Time Policy (ORTP) for the selection of potential HPF for efficient processing of the requests with maximum resource utilization. It is analysed that size and number of virtual resources affect the performance of the computing system. In the proposed system model, micro grids are introduced in the vicinity of energy consumers for uninterrupted and cost optimized power supply. The impact of the number of VMs on the performance of HPFs is analysed with extensive simulations with three scenarios.

2014 ◽  
Vol 659 ◽  
pp. 395-400 ◽  
Author(s):  
Ciprian Lapusan ◽  
Radu Balan ◽  
Olimpiu Hancu ◽  
Ciprian Rad

The article investigates the development of home energy management systems based on real-time control algorithms and online identification. The proposed system optimizes the energy consumption for heating and cooling of a household using model predictive control strategies. The virtual prototype of the energy management system is developed, simulated and optimized using Matlab/Simulink. The simulated system is then implemented using dSpace platform and rapid control prototyping on real-time hardware and tested on a laboratory surrogate system. The system performance is evaluated by comparing the results with the response of classic systems used for heating and cooling in domestic houses. The obtained results confirmed the viability of the proposed solution in home energy management systems.


1998 ◽  
Vol 37 (1) ◽  
pp. 347-354 ◽  
Author(s):  
Ole Mark ◽  
Claes Hernebring ◽  
Peter Magnusson

The present paper describes the Helsingborg Pilot Project, a part of the Technology Validation Project: “Integrated Wastewater” (TVP) under the EU Innovation Programme. The objective of the Helsingborg Pilot Project is to demonstrate implementation of integrated tools for the simulation of the sewer system and the wastewater treatment plant (WWTP), both in the analyses and the operational phases. The paper deals with the programme for investigating the impact of real time control (RTC) on the performance of the sewer system and wastewater treatment plant. As the project still is in a very early phase, this paper focuses on the modelling of the transport of pollutants and the evaluation of the effect on the sediment deposition pattern from the implementation of real time control in the sewer system.


Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1060
Author(s):  
Md Mamun Ur Rashid ◽  
Majed A. Alotaibi ◽  
Abdul Hasib Chowdhury ◽  
Muaz Rahman ◽  
Md. Shafiul Alam ◽  
...  

From a residential point of view, home energy management (HEM) is an essential requirement in order to diminish peak demand and utility tariffs. The integration of renewable energy sources (RESs) together with battery energy storage systems (BESSs) and central battery storage system (CBSS) may promote energy and cost minimization. However, proper home appliance scheduling along with energy storage options is essential to significantly decrease the energy consumption profile and overall expenditure in real-time operation. This paper proposes a cost-effective HEM scheme in the microgrid framework to promote curtailing of energy usage and relevant utility tariff considering both energy storage and renewable sources integration. Usually, the household appliances have different runtime preferences and duration of operation based on user demand. This work considers a simulator designed in the C++ platform to address the domestic customer’s HEM issue based on usages priorities. The positive aspects of merging RESs, BESSs, and CBSSs with the proposed optimal power sharing algorithm (OPSA) are evaluated by considering three distinct case scenarios. Comprehensive analysis of each scenario considering the real-time scheduling of home appliances is conducted to substantiate the efficacy of the outlined energy and cost mitigation schemes. The results obtained demonstrate the effectiveness of the proposed algorithm to enable energy and cost savings up to 37.5% and 45% in comparison to the prevailing methodology.


2021 ◽  
Vol 22 (1) ◽  
pp. 85-100
Author(s):  
Suchitra Dayalan ◽  
Rajarajeswari Rathinam

Abstract Microgrid is an effective means of integrating multiple energy sources of distributed energy to improve the economy, stability and security of the energy systems. A typical microgrid consists of Renewable Energy Source (RES), Controllable Thermal Units (CTU), Energy Storage System (ESS), interruptible and uninterruptible loads. From the perspective of the generation, the microgrid should be operated at the minimum operating cost, whereas from the perspective of demand, the energy cost imposed on the consumer should be minimum. The main key in controlling the relationship of microgrid with the utility grid is managing the demand. An Energy Management System (EMS) is required to have real time control over the demand and the Distributed Energy Resources (DER). Demand Side Management (DSM) assesses the actual demand in the microgrid to integrate different energy resources distributed within the grid. With these motivations towards the operation of a microgrid and also to achieve the objective of minimizing the total expected operating cost, the DER schedules are optimized for meeting the loads. Demand Response (DR) a part of DSM is integrated with MG islanded mode operation by using Time of Use (TOU) and Real Time Pricing (RTP) procedures. Both TOU and RTP are used for shifting the controllable loads. RES is used for generator side cost reduction and load shifting using DR performs the load side control by reducing the peak to average ratio. Four different cases with and without the PV, wind uncertainties and ESS are analyzed with Demand Response and Unitcommittment (DRUC) strategy. The Strawberry (SBY) algorithm is used for obtaining the minimum operating cost and to achieve better energy management of the Microgrid.


Author(s):  
Sandeep Kakran ◽  
Saurabh Chanana

Abstract Demand response (DR) programs have become powerful tools of the smart grids, which provide opportunities for the end-use consumers to participate actively in the energy management programs. This paper investigates impact of different DR strategies in a home-energy management system having consumer with regular load, electric vehicle (EV) and battery-energy storage system (BESS) in the home. The EV is considered as a special type of load, which can also work as an electricity generation source by discharging the power in vehicle-to-home mode during high price time. BESS and a small renewable energy source in form of rooftop photovoltaic panels give a significant contribution in the energy management of the system. As the main contribution to the literature, a mixed integer linear programming based model of home energy management system is formulated to minimize the daily cost of electricity consumption under the effect of different DR programs; such as real time price based DR program, incentive based DR program and peak power limiting DR program. Finally, total electricity prices are analysed in the case studies by including different preferences of the household consumer under mentioned DR programs. A total of 26.93 % electricity cost reduction is noticed with respect to base case, without peak limiting DR and 19.93 % electricity cost reduction is noticed with respect to base case, with peak limiting DR.


2002 ◽  
Vol 45 (3) ◽  
pp. 229-237 ◽  
Author(s):  
T. Frehmann ◽  
A. Niemann ◽  
P. Ustohal ◽  
W.F. Geiger

Four individual mathematical submodels simulating different subsystems of urban drainage were intercoupled to an integral model. The submodels (for surface runoff, flow in sewer system, wastewater treatment plant and receiving water) were calibrated on the basis of field data measured in an existing urban catchment investigation. Three different strategies for controlling the discharge in the sewer network were defined and implemented in the integral model. The impact of these control measures was quantified by representative immission state-parameters of the receiving water. The results reveal that the effect of a control measure may be ambivalent, depending on the referred component of a complex drainage system. Furthermore, it is demonstrated that the drainage system in the catchment investigation can be considerably optimised towards environmental protection and operation efficiency if an appropriate real time control on the integral scale is applied.


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