Ali Baniasadi | Edith Cowan University (original) (raw)

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Papers by Ali Baniasadi

Research paper thumbnail of PV Self-Consumption Enhancement with Optimal Residential Thermal Energy Management

2019 9th International Conference on Power and Energy Systems (ICPES)

Research paper thumbnail of A Cost-effective Thermal and Electrical Energy Storage Management Strategy for Smart Buildings

2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)

Research paper thumbnail of Cost–Benefit Analysis of a Virtual Power Plant Including Solar PV, Flow Battery, Heat Pump, and Demand Management: A Western Australian Case Study

Energies

Achieving the renewable energy integration target will require the extensive engagement of consum... more Achieving the renewable energy integration target will require the extensive engagement of consumers and the private sector in investment and operation of renewable-based energy systems. Virtual power plants are an efficient way to implement this engagement. In this paper, the detailed costs and benefits of implementing a realistic virtual power plant (VPP) in Western Australia, comprising 67 dwellings, are calculated. The VPP is designed to integrate and coordinate rooftop solar photovoltaic panels (PV), vanadium redox flow batteries (VRFB), heat pump hot water systems (HWSs), and demand management mechanisms. An 810-kW rooftop solar PV system is designed and located using the HelioScope software. The charging and the discharging of a 700-kWh VRFB are scheduled for everyday use over a year using an optimization algorithm, to maximize the benefit of it for the VPP owners and for the residents. The use of heat pump HWSs provides a unique opportunity for the residents to save energy a...

Research paper thumbnail of Demonstration of Peak-Load Shifting with Optimal Residential Thermal Energy Management

EasyChair Preprints

The high penetration of renewable energy resources (RES), in particular the rooftop photovoltaic ... more The high penetration of renewable energy resources (RES), in particular the rooftop photovoltaic (PV) systems in power systems, causes rapid ramps in power generation to supply load during peak-load periods. In smart residential buildings, variations in rooftop PV power causes a mismatch between generation and load demand. This paper deals with shifting heat pumps loads to either the lower electricity price period or whenever PV generation is available. A strategy is proposed for managing heat pump operation based on real-time pricing tariff to minimize the operation cost of a smart building by controlling the room temperature. Simulation results demonstrate the cost benefits and effectiveness of the proposed thermal energy management strategy.

Research paper thumbnail of Optimal sizing design and operation of electrical and thermal energy storage systems in smart buildings

Journal of Energy Storage , 2020

Photovoltaic (PV) systems in residential buildings require energy storage to enhance their produc... more Photovoltaic (PV) systems in residential buildings require energy storage to enhance their productivity; however , in present technology, battery storage systems (BSSs) are not the most cost-effective solutions. Comparatively, thermal storage systems (TSSs) can provide opportunities to enhance PV self-consumption while reducing life cycle costs. This paper proposes a new framework for optimal sizing design and real-time operation of energy storage systems in a residential building equipped with a PV system, heat pump (HP), thermal and electrical energy storage systems. For simultaneous optimal sizing of BSS and TSS, a particle swarm optimization (PSO) algorithm is applied to minimize daily electricity and life cycle costs of the smart building. A model predictive controller is then developed to manage energy flow of storage systems to minimize electricity costs for end-users. The main objective of the controller is to optimally control HP operation and battery charge/dis-charge actions based on a demand response program. The controller regulates the flow of water in the storage tank to meet designated thermal energy requirements by controlling HP operation. Furthermore, the power flow of battery is controlled to supply all loads during peak-load hours to minimize electricity costs. The results of this paper demonstrate to rooftop PV system owners that investment in combined TSS and BSS can be more profitable as this system can minimize life cycle costs. The proposed methods for optimal sizing and operation of electrical and thermal storage system can reduce the annual electricity cost by more than 80% with over 42% reduction in the life cycle cost. Simulation and experimental results are presented to validate the effectiveness of the proposed framework and controller.

Research paper thumbnail of PV Self-Consumption Enhancement with Optimal Residential Thermal Energy Management

2019 9th International Conference on Power and Energy Systems (ICPES)

Research paper thumbnail of A Cost-effective Thermal and Electrical Energy Storage Management Strategy for Smart Buildings

2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)

Research paper thumbnail of Cost–Benefit Analysis of a Virtual Power Plant Including Solar PV, Flow Battery, Heat Pump, and Demand Management: A Western Australian Case Study

Energies

Achieving the renewable energy integration target will require the extensive engagement of consum... more Achieving the renewable energy integration target will require the extensive engagement of consumers and the private sector in investment and operation of renewable-based energy systems. Virtual power plants are an efficient way to implement this engagement. In this paper, the detailed costs and benefits of implementing a realistic virtual power plant (VPP) in Western Australia, comprising 67 dwellings, are calculated. The VPP is designed to integrate and coordinate rooftop solar photovoltaic panels (PV), vanadium redox flow batteries (VRFB), heat pump hot water systems (HWSs), and demand management mechanisms. An 810-kW rooftop solar PV system is designed and located using the HelioScope software. The charging and the discharging of a 700-kWh VRFB are scheduled for everyday use over a year using an optimization algorithm, to maximize the benefit of it for the VPP owners and for the residents. The use of heat pump HWSs provides a unique opportunity for the residents to save energy a...

Research paper thumbnail of Demonstration of Peak-Load Shifting with Optimal Residential Thermal Energy Management

EasyChair Preprints

The high penetration of renewable energy resources (RES), in particular the rooftop photovoltaic ... more The high penetration of renewable energy resources (RES), in particular the rooftop photovoltaic (PV) systems in power systems, causes rapid ramps in power generation to supply load during peak-load periods. In smart residential buildings, variations in rooftop PV power causes a mismatch between generation and load demand. This paper deals with shifting heat pumps loads to either the lower electricity price period or whenever PV generation is available. A strategy is proposed for managing heat pump operation based on real-time pricing tariff to minimize the operation cost of a smart building by controlling the room temperature. Simulation results demonstrate the cost benefits and effectiveness of the proposed thermal energy management strategy.

Research paper thumbnail of Optimal sizing design and operation of electrical and thermal energy storage systems in smart buildings

Journal of Energy Storage , 2020

Photovoltaic (PV) systems in residential buildings require energy storage to enhance their produc... more Photovoltaic (PV) systems in residential buildings require energy storage to enhance their productivity; however , in present technology, battery storage systems (BSSs) are not the most cost-effective solutions. Comparatively, thermal storage systems (TSSs) can provide opportunities to enhance PV self-consumption while reducing life cycle costs. This paper proposes a new framework for optimal sizing design and real-time operation of energy storage systems in a residential building equipped with a PV system, heat pump (HP), thermal and electrical energy storage systems. For simultaneous optimal sizing of BSS and TSS, a particle swarm optimization (PSO) algorithm is applied to minimize daily electricity and life cycle costs of the smart building. A model predictive controller is then developed to manage energy flow of storage systems to minimize electricity costs for end-users. The main objective of the controller is to optimally control HP operation and battery charge/dis-charge actions based on a demand response program. The controller regulates the flow of water in the storage tank to meet designated thermal energy requirements by controlling HP operation. Furthermore, the power flow of battery is controlled to supply all loads during peak-load hours to minimize electricity costs. The results of this paper demonstrate to rooftop PV system owners that investment in combined TSS and BSS can be more profitable as this system can minimize life cycle costs. The proposed methods for optimal sizing and operation of electrical and thermal storage system can reduce the annual electricity cost by more than 80% with over 42% reduction in the life cycle cost. Simulation and experimental results are presented to validate the effectiveness of the proposed framework and controller.

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