Modelling and analysis of smart localised energy system for a sustainable future power network
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Abstract
Combating the increasing effect of climate change and averting future energy crisis resulting partly due to our continued dependence on conventional energy sources requires exploring aggressively more sustainable means of generating and utilising energy. Currently, most developed countries are transitioning slowly from a fossil fuel dominated energy system to a sustainable and renewable energy based system. However, for the results of these transitions to be impactful and reduce the global temperature rise to the expected 1.5oC, the approach must be wholistic and encompassing. Although there are a lot of ongoing research in the areas of renewable energy integration into the grid, however, there seems to be a dearth of such studies in some specific aspect of the power system application. Consequently, this thesis models and performs several analyses on a smart localised energy system with the aim of decarbonising some aspects of the future power network. The study investigated the dynamics of residential power demand in Nigeria and modelled the residential energy consumption profile. An excel-based algorithm was developed and applied to the developed model. The results of the residential energy consumption was based on the appliance energy end use methodology. This was used to develop a load profile indicative of a typical urban residential energy demand in Nigeria and employed to predict the effects of residential loads on the power system. Following the frequent use of diesel generators by municipal councils to power street lighting, several case studies demonstrating how to optimise street lighting energy consumption and improve energy efficiency were carried out using simple economic analysis indices such as Life Cycle Cost (LCC), Annualized Life Cycle Cost (ALCC), Net Present Cost (NPC), Cost of Energy (COE), and Return on Investment (ROI). The solar photovoltaic (SPV) system had the lowest LCC and ALCC, thus making it the most economically viable option. The response of the power system to Distributed Energy Resources (DERs)
integration was also investigated. Data from a real low voltage (LV)
distribution network in Nigeria was obtained and used in modelling the
network using PSCAD/EMTDC software package. Different impact studies
considering addition of distributed generation sources and increase in the
load were performed. Volt-VAr optimisation (VVO) was performed to enable
the inverter-based PV systems participate actively in voltage regulation by
the provision of flexible reactive power support. A net total of 1.359 MVAr
and 1.301 MVAr respectively are utilised from the inverter to regulate
voltage within the acceptable limits, hence reducing the substation reactive
power by 19.8% and 18.9% respectively during the controlled case study.
Also, the total active power loss did reduce from 0.437 MW to 0.172 MW
while the deviation of consumer voltages from the nominal system voltage
was reduced by 33.4% during the controlled case studies. Overall, the VVO
did enhance power quality and reliability by improving the feeder voltage
profile and reducing the active power losses in the network.
Lastly, to decarbonise some operation of the power system and improve the
system resilience, DERs integrated black start restoration (BSR) strategy
was implemented. The formulated BSR problem was implemented as a
dynamic optimisation problem and the simulation was performed on the
Nigerian 330 kV 48-bus system. The mixed-integer linear programming
(MILP) technique was adopted and modelled to suit the nature of the BSR
method developed. The black start power restoration sequence and the
development of a viable restoration strategy were actualised. The simulation
of the MILP model was achieved in MATLAB® using the IBM CPLEXTM solver. For the Nigerian 330 kV 48-bus system analysed, it was observed that most loads were optimally restored before the 30th time step for a black start operation. Both the experimental and numerical methodology were adopted in the validation of energy storage system (ESS) adopted for the proposed BSR simulated study. The optimal battery power availability for participating in restoration was reached in less than 50 minutes, with ESS optimally contributing to power restoration achieving 4.3% & 18.1% for Kaduna and Jos respectively