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46. Cost-effective sizing of an AC mini-grid hybrid power system for a remote area in South Australia.

Author

Combe, Matthew, Haque, Mohammed H., Mahmoudi, Amin, and Khezri, Rahmat

Subjects
*DIESEL electric power-plants, *RENEWABLE energy sources, *ELECTRIC power distribution grids, *PARTICLE swarm optimization
Abstract

This study determines the optimal capacity of various components of an AC mini-grid hybrid power system in a remote area of South Australia. A range of generation and storage technologies, such as diesel generators, wind turbines, solar photovoltaic arrays, battery banks, and flywheels are considered. A minimum system operating reserve is maintained to ensure a certain degree of reliability. Four different configurations of hybrid power systems are analysed in hourly time-steps, over a year, using real data for system load, solar insolation, ambient temperature, and wind speed. Particle swarm optimisation approach is used to optimise the capacity of various components of each hybrid system to obtain the minimum net present cost (NPC) over a 20-year system lifespan. Suitable capital, operating, and maintenance costs in Australian context are considered in evaluating the system. Various simulation results, such as annual energy balances, NPCs, levelised cost of energy and cash flow analysis obtained for each optimised system are carefully analysed and discussed. The modelling and results confirms the feasibility and economical replacement of the diesel power system with those of hybrid power systems which use renewable energy supply. [ABSTRACT FROM AUTHOR]

Published
2019
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47. Multistage time-variant electric vehicle load modelling for capturing accurate electric vehicle behaviour and electric vehicle impact on electricity distribution grids

Author

Haidar, Ahmed M, Muttaqi, Kashem M, Haque, Mohammed H, Haidar, Ahmed M, Muttaqi, Kashem M, and Haque, Mohammed H

Abstract

Accurate electric vehicle (EV) load modelling is a daunting task because the proportion and characteristics of these extra electrical loads in the grids are continuously changing. In many recent EV studies, EV load is assumed to be a constant power load to analyse the effect of EV charging on electric network. However, such an assumption would not be effective in real-time application and can give misleading results. This study proposes a multistage timevariant EV load modelling technique based on the characteristics of EV load demand due to EV battery charging. To capture the transitions between different stages of battery charging, the EV loads are modelled with a multistage scheme and implemented ZIP model. A comparative study of energy losses and voltage profile is carried out on the IEEE 69-bus test system for the use of a traditional constant load model, conventional ZIP load model and the proposed multistage time-variant EV load model. Results show that the load models can significantly affect the energy losses and terminal voltages, and provide misrepresentation if EV load is not accurately modelled. Therefore, for proper analysis of EV loads during unidirectional charging, it is essential to have accurate models for predicting true EV behaviour.

Published
2015

49. Techno-economic modelling for energy cost optimisation of households with electric vehicles and renewable sources under export limits

Author

Yan Wu, Syed Mahfuzul Aziz, Mohammed H. Haque, Wu, Yan, Aziz, Syed Mahfuzul, and Haque, Mohammed H

Subjects
battery energy storage, energy cost optimisation, Renewable Energy, Sustainability and the Environment, electric vehicle, solar photovoltaic, renewable energy sources, particle swarm optimisation
Abstract

Refereed/Peer-reviewed With the proliferation of electric vehicles (EVs), EV charging cost will become an integral part of household energy cost. This research proposes a novel household energy cost optimisation method for grid-connected homes with EV under power export constraints. It addresses the limitations of previous studies by incorporating more realistic variable EV charging characteristics, power export limits, degradation of battery energy storage (BES) and battery salvage revenue into a comprehensive techno-economic energy system model. Cost optimisation results are presented for four system configurations using relatively new time-of-use (ToU) tariff and real load and photovoltaic (PV) generation data for South Australian households. Sensitivity analysis for annual energy cost (AEC) is conducted by varying daily household load demand, PV/BES capacity, power export limits and PV/BES cost. Power flow and peak demand analyses are presented to the impacts of PV, BES and EV on household demand. Results show that PV with BES and EV is the most economical configuration for individual households, where the AEC can be reduced by up to 39.6% compared to a normal household without EV, PV and BES. The BES can effectively reduce household power and energy demands during peak periods by up to 80.4% and 89.1%, respectively.

Published
2022
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50. Impact of Optimal Sizing of Wind Turbine and Battery Energy Storage for a Grid-Connected Household With/Without an Electric Vehicle

Author

Rahmat Khezri, Amin Mahmoudi, Mohammed H. Haque, Khezri, Rahmat, Mahmoudi, Amin, and Haque, Mohammed H

Subjects
battery energy storage, small wind turbine, Control and Systems Engineering, capacity optimization, energy management system, electric vehicle, cost of electricity, Electrical and Electronic Engineering, Computer Science Applications, Information Systems
Abstract

Refereed/Peer-reviewed This paper determines the optimal capacities of small wind turbine (SWT) and battery energy storage (BES) for a grid-connected household (GCH) with or without an electric vehicle (EV) to minimize the overall cost of electricity (COE). Rule-based home energy management systems (HEMSs) are developed for two different configurations of the GCH: (i) with only SWT, and (ii) with SWT and BES. For each configuration, the HEMSs are developed for two cases: with and without an EV in the premises of the GCH. Uncertainties are also included in the arrival time, departure time, and initial state of charge (at arrival) of the EV. The above technique is then applied to a typical household in South Australia (SA) using the yearly load profile of the household and actual yearly wind speed data at an interval of one hour. To investigate the effects of stochastic nature of household load, EV, and wind power generation on various results, the optimization process is repeated using 10-year of actual wind speed data and probabilistic load and EV uncertainties. The results of several sensitivity analyses of various system parameters are presented. It has been found that the SWT can effectively decrease the COE of the household for both cases (with and without an EV). However, the current price of battery may not be in favor of further reducing the COE of the household.

Published
2022
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