Providing energy management of a fuel cell–battery–wind turbine–solar panel hybrid off grid smart home system

Arabul, Fatma Keskin; Arabul, Ahmet Yiğit; Kumru, Celal Fadıl; Boynueğri, Ali Rıfat

doi:10.1016/j.ijhydene.2017.02.204

Cited by 68 publications

(9 citation statements)

References 22 publications

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“…Currently, RESs are integrated into smart homes including solar photovoltaic (PV) [66], wind [67], biomass [68], geothermal energy [69], and so on [70]. In addition, hybrid energy systems such as solar-wind energy [49] and solarwind-diesel energy [71] have also been complemented to provide a reliable and sustainable power supply for a family with a full set of modern home appliances and complete basic residential functions.…”

Section: Energy Generation and Storage Devicesmentioning

confidence: 99%

Home Energy Management Systems: A Review of the Concept, Architecture, and Scheduling Strategies

et al. 2023

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Growing electricity demand, the deployment of renewable energy sources and the widespread use of smart home appliances provide new opportunities for home energy management systems (HEMSs), which can be defined as systems that improve the overall energy production and consumption of residential buildings by controlling and scheduling the use of household equipment. By saving energy, reducing residential electricity costs, optimizing the utilization rate and reliability of utility companies' power systems, and reducing air pollution for society, HEMSs lead to an enhancement in the socioeconomic development of low-carbon economies. This review aims to systematically analyze and summarize the development trends and challenges of HEMSs in recent years. This paper reviews the development history of the HEMS architecture and discusses the characteristics of several major communication technologies in the current HEMS infrastructure. In addition, the common objectives and constraints related to scheduling optimization are classified, and several optimization methods in the literature, including various intelligent algorithms, have been introduced, compared, and critically analyzed. Furthermore, experimental studies and challenges in the real world are also summarized and recommendations are given. This paper reveals the trend from simple to complex in the architecture and functionality of HEMSs, discusses the challenges for future improvements in modeling and scheduling, and shows the development of various modeling and scheduling methods. Based on this review, researchers can gain a comprehensive understanding of current research trends in HEMSs and open up ideas for developing new modeling and scheduling approaches by gaining insight into the trade-offs between optimum solutions and computational complexity.INDEX TERMS Demand response, home appliances, home energy management system, optimization, renewable energy resources, smart grid.

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Section: Energy Generation and Storage Devicesmentioning

confidence: 99%

Home Energy Management Systems: A Review of the Concept, Architecture, and Scheduling Strategies

et al. 2023

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“…As a consequence, operations research studies of residential energy management generally consider hydrogen technology as a short-time storage for partly self-sufficiency. Under good solar and wind potential, complete off-grid operation can be achieved via a combination of a PV array, a wind turbine, an electric battery, a fuel cell continuously supplied from a hydrogen station, and possible load shifting [36]. HHS of [37,38] can support a stand-alone RES, allowing residential districts to achieve eight days of autonomy in the absence of solar insolation.…”

Section: Photovoltaic Arraymentioning

confidence: 99%

Prosumers and energy pricing policies: When, where, and under which conditions will prosumers emerge? A case study for Ontario (Canada)

Kuznetsova

Anjos

2021

Energy Policy

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“…By shifting and load scheduling using a fuzzy logic controller with energy management algorithm (EMA), renewable energy generation from wind is increased by 2.5% and solar is increased by 2%. In addition, the fuel cell fuel consumption is reduced up to 4% annually [29]. Based on the operational history of industrial air separation units, the author in [30] presents a dynamic optimisation-based DR scheduling framework.…”

Section: Related Workmentioning

confidence: 99%

Closed-Loop Elastic Demand Control under Dynamic Pricing Program in Smart Microgrid Using Super Twisting Sliding Mode Controller

Khan

Ullah

Hafeez

et al. 2020

Sensors

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Electricity demand is rising due to industrialisation, population growth and economic development. To meet this rising electricity demand, towns are renovated by smart cities, where the internet of things enabled devices, communication technologies, dynamic pricing servers and renewable energy sources are integrated. Internet of things (IoT) refers to scenarios where network connectivity and computing capability is extended to objects, sensors and other items not normally considered computers. IoT allows these devices to generate, exchange and consume data without or with minimum human intervention. This integrated environment of smart cities maintains a balance between demand and supply. In this work, we proposed a closed-loop super twisting sliding mode controller (STSMC) to handle the uncertain and fluctuating load to maintain the balance between demand and supply persistently. Demand-side load management (DSLM) consists of agents-based demand response (DR) programs that are designed to control, change and shift the load usage pattern according to the price of the energy of a smart grid community. In smart grids, evolved DR programs are implemented which facilitate controlling of consumer demand by effective regulation services. The DSLM under price-based DR programs perform load shifting, peak clipping and valley filling to maintain the balance between demand and supply. We demonstrate a theoretical control approach for persistent demand control by dynamic price-based closed-loop STSMC. A renewable energy integrated microgrid scenario is discussed numerically to show that the demand of consumers can be controlled through STSMC, which regulates the electricity price to the DSLM agents of the smart grid community. The overall demand elasticity of the current study is represented by a first-order dynamic price generation model having a piece-wise linear price-based DR program. The simulation environment for this whole scenario is developed in MATLAB/Simulink. The simulations validate that the closed-loop price-based elastic demand control technique can trace down the generation of a renewable energy integrated microgrid.

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Providing energy management of a fuel cell–battery–wind turbine–solar panel hybrid off grid smart home system

Cited by 68 publications

References 22 publications

Home Energy Management Systems: A Review of the Concept, Architecture, and Scheduling Strategies

Home Energy Management Systems: A Review of the Concept, Architecture, and Scheduling Strategies

Prosumers and energy pricing policies: When, where, and under which conditions will prosumers emerge? A case study for Ontario (Canada)

Closed-Loop Elastic Demand Control under Dynamic Pricing Program in Smart Microgrid Using Super Twisting Sliding Mode Controller

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