A demand side management strategy based on forecasting of residential renewable sources: A smart home system in Turkey

Abstract:The smart grid plays a vital role in decreasing electricity cost through Demand Side Management (DSM). Smart homes, a part of the smart grid, contribute greatly to minimizing electricity consumption cost via scheduling home appliances. However, user waiting time increases due to the scheduling of home appliances. This scheduling problem is the motivation to find an optimal solution that could minimize the electricity cost and Peak to Average Ratio (PAR) with minimum user waiting time. There are many studies on Home Energy Management (HEM) for cost minimization and peak load reduction. However, none of the systems gave sufficient attention to tackle multiple parameters (i.e., electricity cost and peak load reduction) at the same time as user waiting time was minimum for residential consumers with multiple homes. Hence, in this work, we propose an efficient HEM scheme using the well-known meta-heuristic Genetic Algorithm (GA), the recently developed Cuckoo Search Optimization Algorithm (CSOA) and the Crow Search Algorithm (CSA), which can be used for electricity cost and peak load alleviation with minimum user waiting time. The integration of a smart Electricity Storage System (ESS) is also taken into account for more efficient operation of the Home Energy Management System (HEMS). Furthermore, we took the real-time electricity consumption pattern for every residence, i.e., every home has its own living pattern. The proposed scheme is implemented in a smart building; comprised of thirty smart homes (apartments), Real-Time Pricing (RTP) and Critical Peak Pricing (CPP) signals are examined in terms of electricity cost estimation for both a single smart home and a smart building. In addition, feasible regions are presented for single and multiple smart homes, which show the relationship among the electricity cost, electricity consumption and user waiting time. Experimental results demonstrate the effectiveness of our proposed scheme for single and multiple smart homes in terms of electricity cost and PAR minimization. Moreover, there exists a tradeoff between electricity cost and user waiting.

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“…Similarly, the cost for non-deferrable appliances over an individual time slot can be computed according to Equation (9).…”

Section: Non-deferrable Appliancesmentioning

confidence: 99%

Towards Efficient Energy Management of Smart Buildings Exploiting Heuristic Optimization with Real Time and Critical Peak Pricing Schemes

et al. 2017

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“…A similar system is proposed by Tascikaraoglu et al [11] using a fuzzy logic-based controller to determine the appropriate load shifting and rescheduling operations with renewable sources. However, as in [9] a power forecasting approach was implemented, which has significant limitations.…”

Section: Review Of Existing De-centralised Dsm Unitsmentioning

confidence: 99%

Design of an Appliance Switch Responding to Solar Energy

Koshti¹,

Williams²

2024

RE&PQJ

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Abstract:Knowing the ill effects of dependence upon conventional resources for generation of energy, the world is already making an effort to harness energy from renewable energy sources. However, the use of conventional resources is not fully eliminated from daily lives of people as the renewable energy sources are limited due to their intermittent nature.The paper presents a unique technique of Demand Side Management (DSM) for a domestic consumer whose house is equipped with on-grid solar PV panel system. DSM is the management of energy needs according to its availability. The paper deals with designing of an automated switch which is an adapter and can be inserted into standard 13amp socket. The adapter is equipped with a sensor that transmits data to it. The smart solar switch can detect surplus power generated by the PV system and it controls non-priority loads in the house depending upon the amount of surplus power. The designed switch provides an automatic, fast, easy to install and safe option for customers who want to increase their use of solar energy. Its performance was tested in a lab setup as well as in real time scenario in a home.

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“…A. Tascikaraoglu et al investigate an experimental smart home with several renewable energy sources and storage systems in terms of various aspects such as appliances control, in-home energy management and power flow. Additionally, the study embodies one of the very first challenges to assess the contribution of power forecasting of renewable energy sources on the performance of smart home concepts [23]. A.R.…”

Section: Renewable Energy Management Driven Smart Homementioning

confidence: 99%

“…With the use of advanced metering and display technologies in an established smart home, the user or the system itself is capable of lowering the energy consumption or postponing the energy demanding operations concerning the present electricity price by managing the household electrical features and under the condition of ensuring a positive comfort level [23]. J.A.…”

Section: Renewable Energy Management Driven Smart Homementioning

confidence: 99%

Smart Home Communication Technologies and Applications: Wireless Protocol Assessment for Home Area Network Resources

et al. 2015

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Abstract:The paper discusses Home Area Networks (HAN) communication technologies for smart home and domestic application integration. The work is initiated by identifying the application areas that can benefit from this integration. A broad and inclusive home communication interface is analysed utilizing as a key piece a Gateway based on machine-to-machine (M2M) communications that interacts with the surrounding environment. Then, the main wireless networks are thoroughly assessed, and later, their suitability to the requirements of HAN considering the application area is analysed. Finally, a qualitative analysis is portrayed.

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A demand side management strategy based on forecasting of residential renewable sources: A smart home system in Turkey

Cited by 164 publications

References 30 publications

Towards Efficient Energy Management of Smart Buildings Exploiting Heuristic Optimization with Real Time and Critical Peak Pricing Schemes

Towards Efficient Energy Management of Smart Buildings Exploiting Heuristic Optimization with Real Time and Critical Peak Pricing Schemes

Design of an Appliance Switch Responding to Solar Energy

Smart Home Communication Technologies and Applications: Wireless Protocol Assessment for Home Area Network Resources

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