High penetrations of domestic electric vehicles (EVs) in U.K. low voltage (LV) networks may result in significant technical problems. This paper proposes an implementable, centralized control algorithm, currently being trialed in 9 U.K. residential LV networks, that uses limited information to manage EV charging points to mitigate these technical problems. Two real U.K. LV networks are used to quantify the potential impacts of different EV penetration levels and to demonstrate the effectiveness of the control algorithm (using different control cycles) for simultaneous thermal and voltage management. Monte Carlo simulations (adopting 1-min resolution data) are undertaken to cater for domestic and EV demand uncertainties. Results for these LV networks show that problems may occur for EV penetrations higher than 20%. More importantly, they highlight that even for a 100% penetration and control cycles of up to 10 min, the control algorithm successfully mitigates problems on the examined LV networks. Crucially, to determine effects on the comfort of EV users, a metric is introduced and discussed. The results of different control settings are presented to analyze potential adaptations of the control strategy. Finally, a comparison with an optimization framework highlights that the proposed algorithm is as effective while using limited information.

This paper presents a planning framework to find the minimum storage sizes (power and energy) at multiple locations in distribution networks to reduce curtailment from renewable distributed generation (DG), specifically wind farms, while managing congestion and voltages. A two-stage iterative process is adopted in this framework. The first stage uses a multi-period AC optimal power flow (OPF) across the studied horizon to obtain initial storage sizes considering hourly wind and load profiles. The second stage adopts a high granularity minute-by-minute control driven by a mono-period bi-level AC OPF to tune the first-stage storage sizes according to the actual curtailment. Congestion and voltages are managed through the optimal control of storage (active and reactive power), on-load tap changers (OLTCs), DG power factor, and DG curtailment as last resort. The proposed storage planning framework is applied to a real 33-kV network from the North West of England over one week. The results highlight that by embedding high granularity control aspects into planning, it is possible to more accurately size storage facilities. Moreover, intelligent management of further flexibility (i.e., OLTCs, storage, and DG power factor control) can lead to much smaller storage capacities. This, however, depends on the required level of curtailment.

This paper presents a risk-based advanced distribution network management system (NMS) aimed at maximizing wind energy harvesting while simultaneously managing congestion and voltages. The NMS allows the adoption of multi-minute control cycles so the volume of actions from on-load tap changers (OLTCs) and distributed generation (DG) plants can be reduced while effectively catering for the effects of wind power uncertainties. This work presents the quantification of benefits and impacts from adopting different control cycles as well a comparison with a deterministic approach. The risk-based approach is implemented by adapting and expanding an AC optimal power flow. A risk level is used to determine the extent to which congestion and voltage rise could exist during a control cycle. The proposed NMS is applied to a real-life U.K. MV network from the North West of England to assess its effectiveness in managing high penetration of wind power considering minute-by-minute simulations for one week. The results show that the risk-based approach can effectively manage network constraints better than the deterministic approach, particularly for multi-minute control cycles, reducing also the number of control actions but at the expense of higher levels of curtailment.

Balancing electricity demand and supply remains a significant challenge for the power systems in developing countries, such as Nigeria. In Nigeria, there is a shortage of adequate power supply, and demand-side management (DSM) plays a minor role in the power balancing mechanism with load shedding being widely used. The paper aims to review and compare various existing and emerging DSM strategies in developing countries. An extensive and systematic review was conducted to evaluate potential solutions using DSM to increase the overall energy efficiency in the Nigerian electricity market. This study found that, although the technical and economic potentials of DSM vary in developed countries, the uptakes of DSM have been severely hampered hence preventing the full exploitation and utilisation of the full potential of DSM. The initiatives of a DSM model in Nigeria and other developing countries can play a significant role in addressing demand and supply challenges but an upgrade of the energy infrastructures, a reform of the market structure and the provision of financial incentives are required to allow for wide implementations of DSM strategies in developing countries.

Nowadays, the Overcurrent (OC) and Earth Fault (EF) relays coordination problem is one of the most complex and challenging concerns of power protection and network operators due to the high and volatile generation capacity of renewable energy sources in the grid. In this article, a new and dynamic optimal coordination scheme based on a novel hybrid tripping characteristic has been designed and developed for Over Current Relays (OCRs). Considering the impact of renewable energy sources such as the photovoltaic (PV) system on fault characteristic, this work presents and verifies a novel dynamic and hybrid tripping to achieve minimum tripping time and improve the OCR and EF relays coordination performance in terms of security, sensitivity, and selectivity. The proposed dynamic and hybrid scheme will help the OCRs to cover the EF events, and it has been tested under different fault scenarios compared to the literature. The IEEE-9 and IEEE-33 bus systems are implemented in the ETAP package to validate the effectiveness of the proposed hybrid characteristics against traditionally well-established IEC characteristics. Furthermore, the performance of the proposed advance and dynamic protection approach which doesn’t require a communication infrastructure is investigated for a power network with PV plants under different grid operation modes and topology to provide more robustness protection system. The results, as presented using Industrial software (ETAP), showed that the novel dynamic and hybrid tripping scheme improved the speed of the total time tripping different fault scenarios and location by more than 50% and covers all EF events compared to traditional OCR schemes from the literature. The proposed novel dynamic approach has superior performance in detecting high-impedance faults and significantly reducing the tripping time on the IEEE 33 bus network by 47%.