• Energy Research

Blackouts in Power system are rare in occurrence. However, it is very important to have plans and systems in place to handle any eventuality even if it is remote. After any power blackout, it is necessary to bring power back to normalcy as quickly and reliably as possible. An effective system restoration plan reduces the impact of an outage on customers and on the economy of the affected area while reducing the probability of damage to equipment. This paper deals with the initial restoration process and the concept of bottom up approach of restoration is presented. Simulations are carried out on a test network with hydropower plant developed in DIgSILENT PowerFactory. The simulations mainly focus on parameters such as load pick up, system frequency and voltage and its effects on the load size, time and distance. Using these analyses, a set of guidelines is formulated for a safe and efficient blackstart procedure of a system.

Concern over the transportation sector’s greenhouse gas (GHG) emissions, which make up around 23% of all energy-related CO2 emissions, has grown in recent years. The widespread use of electric vehicles will be the primary strategy for tackling this issue. About 30% of the world’s passenger vehicle fleet is anticipated to be electrified by the year 2040. Moreover, the existing power distribution assets are already operating near their nominal capacities, and most of them have been in service for more than 25 years. Replacement of these assets will be very costly and disruptive to the power distribution network. Ergo, the main challenge with high penetration levels of electric vehicles (EVs) will be the ability of the existing power grid to support the extra unpredictable charging load from EVs without jeopardising the power supply and quality of power. The main bottleneck in integrating EVs into the grid is due to the limitation of the maximum operating temperature of the transformer. Hence, this research proposes a new Time of Use (ToU) pricing mechanism based on the transformers’ thermal loading is proposed. Battery energy storage systems (BESS), which serve as a buffer between supply and demand, present an opportunity to find a solution to this problem. Therefore, the purpose of this research is also to provide a novel technique for optimally sizing BESS systems based on the thermal loading of transformers. This research also explores challenges related to high penetration levels of rooftop photovoltaics (PVs), assessing the synergy between electric vehicle charging load and battery energy storage systems (BESS). Finally, this study investigates and proposes a solution to harmonic distortions. It is proposed that the demand-side control processes as a whole also take into account the impact of harmonics produced by nonlinear loads. Extensive simulation findings demonstrate that, even under harmonics injection by EVs, with the suggested demand response technique with a new ToU price signal based on the thermal loading of transformers, the accelerated ageing of distribution transformers may be significantly decreased without the need for additional grid infrastructure. Overall, in this research, the impacts of high penetration levels of EVs on power distribution assets have been investigated and a solution is proposed to minimise their negative impact.

Transportation systems are one of the leading sectors that contribute to greenhouse gas emissions that lead to enhance global warming. The electrification of vehicles is a promising solution to this widespread problem; however, integrating electric vehicles (EVs) into existing grid systems on a large scale creates several problems, both for consumers and for utilities. Accelerated aging of expensive grid assets, such as power transformers, is one of the primary issues that these utilities are facing. This problem can be addressed with battery energy storage systems (BESS), which acts as buffer between demand and supply. Accordingly, this paper proposes a novel strategy for optimal sizing of BESS based on thermal loading of transformers. This paper also investigates issues associated with high penetration levels of rooftop photovoltaics (PVs), determining the synergy between EV charging load and BESS. The proposed solution is treated as an optimization problem, in which a new time of use (ToU) tariff is utilized as a demand response signal to reduce the accelerated aging of transformers. Extensive simulation results show that the size of BESS can be considerably reduced based on the proposed methodology, thereby avoiding accelerated aging of transformers without the need to augment existing grids.

New government regulations and incentives promote the deployment of commercial electric vehicles to reduce carbon emissions from gasoline-fueled vehicles. For commercial electric vehicles (CEVs) operating in a fleet, charging processes are often performed at the depot where they begin and end their daily driving cycles, as well as at public stations on their routes. With the large penetration of CEVs in depots, simultaneous charging increases peak demand, which in turn impacts the electric network and increases the demand cost of a facility. These depot charging conditions influence the charging schedules of CEVs along their routes and the total service cost of logistic companies. This paper investigates optimal charging problems for CEVs that are supported by charging stations at depot and on-route public charging stations. The optimal charging and routing problems of CEVs are modelled as an optimization problem and relevant solutions are provided. The charging variants considered in the optimization model are peak demand of depot charging, time of use tariffs during the day, partial recharging, waiting times and characteristics of public stations. The results indicate the effectiveness of the developed algorithm in achieving optimal routes that maximize the benefits of logistics companies provided all constraints are satisfied.

This article investigates the effects of high penetration levels of Electric Vehicle (EV) charging on power distribution transformers and proposes a new solution to minimize its negative impacts. There has been growing concern over Greenhouse Gas (GHG) emissions within the transportation sector, which accounts for about 23% of total energy-related carbon-dioxide emissions. The main solution to this problem is the electrification of vehicles. However, large scale integration of EVs into existing grid systems poses some challenges. One major challenge is the accelerated aging of expensive grid assets such as transformers. In this article, a demand response mechanism based on the thermal loading of transformers, is proposed. The proposed solution is modeled as an optimization problem, where a new time of use (ToU) tariff is used to shift the EV load considering the thermal loading of transformers, thereby minimizing their accelerated aging. The simulation results show that the accelerated aging of transformers can be reduced without augmenting the existing grid.