Coordinated two-stage volt/var management in distribution networks

This paper investigates daily volt/var control in distribution networks using feeder capacitors as well as substation capacitors paired with on-load tap changers. A twostage coordinated approach is proposed. Firstly, the feeder capacitor dispatch schedule is determined based on reactive power heuristics. Then, an optimisation model is applied to determine the dispatch schedule of the substation devices taking into account the control actions of the feeder capacitors. The reference voltage of the substation secondary bus and the tap position limits of transformers are modified such that the model adapts to varying load conditions. The optimisation model is solved with a modified particle swarm optimisation algorithm. Furthermore, the proposed method is compared with conventional volt/var control strategies using a distribution network case study. It is demonstrated that the proposed approach performs better than the conventional strategies in terms of voltage deviation and energy loss minimisation

Reconfigurable low voltage direct current charging networks for plug-in electric vehicles

An emerging theme in the development of supporting facilities for plug-in electric vehicles (EVs) is the cost-effective planning and utilisation of charging networks consistent with the uptake of EVs. This paper proposes a low voltage direct current (LVDC) reconfigurable charging network for plugin electric vehicles (EVs) and presents a functional energy management system (EMS) that is capable of planning and operating the charging network to minimise charging cost and to facilitate progressive infrastructure deployment based on EV demand. The charging network is connected to the main AC grid through one or more centralised AC/DC converters that supply a high power charge to EVs connected to the DC side of the converters. The EMS accommodates multiple parking bays, charging sources, AC constraints, non-linear EV battery loads and user charging requirements with a novel approach to managing user inconvenience. The inconvenience model is founded on the presence of user flexibility i.e., an allowance on charging time or battery SOC, providing the capability to increase asset utilisation and enable access for additional network users. Through a series of case studies and a stochastic forecasting approach, the reconfigurable network and EMS demonstrate the capacity to achieve savings over fixed AC and sequential DC systems

A heuristic optimal approach for coordinated volt/var control in distribution networks

This dissertation focuses on daily volt/var control in distribution networks with feeder capacitors, substation capacitors and transformers equipped with on-load tap changers. A hybrid approach is proposed to solve the daily volt/var control problem. To reduce the computational requirements of the problem, this approach combines two methods, namely heuristic and optimal scheduling for the substation and feeder sub-problems respectively. The feeder capacitor dispatch schedule is determined based on a heuristic reactive power setpoint method. At this stage the objective is to minimize the reactive power flow through the substation bus in every time-interval. And as such, mathematical modeling of the distribution network components is adapted to suit time-varying conditions. Furthermore, an optimization model to determine a proper dispatch schedule of the substation devices is formulated. The objective of this model is to minimize the daily total energy loss and voltage deviations. Additionally, the reference voltage of the substation secondary bus and the transformer tap position limits are modified to adapt to given load profiles. The optimization model is solved with a discrete particle swarm optimization algorithm, which incorporates Newton’s method to determine the power-flow solution. The proposed method is applied to a time-varying distribution system and evaluated under different operational scenarios. It is also compared to on-line volt/var control with various settings. Simulation results show that the proposed approach minimizes both the voltage deviations and the total energy loss, while on-line control prioritizes one objective over the other depending on the specified settings.Dissertation (MEng)--University of Pretoria, 2015.Electrical, Electronic and Computer EngineeringUnrestricte

Regulated generation allocation and operation optimization for networks with new variable independent power production and self-generation

The world is moving towards legally binding targets for decarbonisation, with considerable interest in cost effective energy pathways that will have positive socio-economic, environmental and health impacts. The electricity sector is progressing by adopting renewable energy as a replacement for fossil fuel-based electricity generation. As renewable energy sources (RES) in the form of independent power production (IPP) and on-site or self-generation (SG) proliferate on power networks, questions arise about their impact on the financial integrity of the traditional power distribution business. As distribution companies (DISCOs) act to protect their own financial interests, network access barriers will be presented to emerging RES. Network regulation is expected to drive DISCOs to pursue a more socially desirable outcome.;However, today's methods of network regulation are not adequate enough to remove the barriers and still ensure renewable energy goals are met. In fact there are no widely-accepted and clear mechanisms to encourage DISCOs to coordinate distributed generation, let alone SG and IPP, integration in a cost-effective manner. In terms of policy, companies can be obligated to meet a quota of RES in their energy supply. But this obligation is usually not guaranteed to align with the capabilities of power networks, which typically suffer from voltage and congestion constraints among others. To set achievable quotas there is a need for a more adaptable mechanism that takes into account capacity constraints.;The work of this thesis concerns the formulation and empirical analyses of optimisation models of structured RES allocation by a regulated DISCO, and the regulating authority's role in influencing the DISCO's planning approach and promoting socially desirable performance. The developed optimisation models uniquely: introduce combined SG and IPP allocation, which allows generation to be defined in association with on-site demand; provide generation capacity that simultaneously meets network, policy and regulatory requirements (i.e. there is no need to individually evaluate the same implications from the calculated capacity); take account of generation curtailment and its underlying restrictions for SG and IPP; demonstrate SG and IPP allocations for range of quota obligations; and benchmark the performance of the models against alternative approaches of generation allocation and regulation.;This results in a problem with a multilevel structure necessitating the computation of spatial capacity and a solution to the multi-period optimal power flow. The problem variables further depend on the perspective of stakeholders in the electricity market. From the viewpoint of the DISCO, the solution intends to provide suitably sited DG capacity and maximise profit. As for the regulating authority the results offer the most suitable reward or penalty to drive the DISCO towards a low carbon network.In response, the regulated DISCO should then carry out DG planning in line with broader goals of society. This joint SG and IPP integration problem lends itself specific and unique constraints including generation class-specific net generation and energy curtailment.;The results reported in this thesis highlight the value and performance of the DISCO and regulation optimisation models on several power networks of varying size and composition. Numerical experiments demonstrate the developed DISCO optimisation model outperforms standard models, concerned primarily with capacity maximisation, in satisfying the following binding constraints: minimum IPP capacity and SG net energy.It is further revealed that integrating SG and IPP in a benchmark system with the proposed model increases profit by up to 23.7%, adding an improvement of 8% over a feasible standard model. In a case study of a network with extremely limited capacity-insufficient for minimum IPP-it is shown using the regulation optimisation model that to maintain the required DISCO profit the incentives can range from 2% to 14% of revenue for quota obligations spanning 10% to 50% of network load. The regulation optimisation model is compared with decoupling, a familiar method for removing energy retail impacts on revenue. Results show that regulation optimisation model is able to maintain a steadier profit with increasing quota requirements.The world is moving towards legally binding targets for decarbonisation, with considerable interest in cost effective energy pathways that will have positive socio-economic, environmental and health impacts. The electricity sector is progressing by adopting renewable energy as a replacement for fossil fuel-based electricity generation. As renewable energy sources (RES) in the form of independent power production (IPP) and on-site or self-generation (SG) proliferate on power networks, questions arise about their impact on the financial integrity of the traditional power distribution business. As distribution companies (DISCOs) act to protect their own financial interests, network access barriers will be presented to emerging RES. Network regulation is expected to drive DISCOs to pursue a more socially desirable outcome.;However, today's methods of network regulation are not adequate enough to remove the barriers and still ensure renewable energy goals are met. In fact there are no widely-accepted and clear mechanisms to encourage DISCOs to coordinate distributed generation, let alone SG and IPP, integration in a cost-effective manner. In terms of policy, companies can be obligated to meet a quota of RES in their energy supply. But this obligation is usually not guaranteed to align with the capabilities of power networks, which typically suffer from voltage and congestion constraints among others. To set achievable quotas there is a need for a more adaptable mechanism that takes into account capacity constraints.;The work of this thesis concerns the formulation and empirical analyses of optimisation models of structured RES allocation by a regulated DISCO, and the regulating authority's role in influencing the DISCO's planning approach and promoting socially desirable performance. The developed optimisation models uniquely: introduce combined SG and IPP allocation, which allows generation to be defined in association with on-site demand; provide generation capacity that simultaneously meets network, policy and regulatory requirements (i.e. there is no need to individually evaluate the same implications from the calculated capacity); take account of generation curtailment and its underlying restrictions for SG and IPP; demonstrate SG and IPP allocations for range of quota obligations; and benchmark the performance of the models against alternative approaches of generation allocation and regulation.;This results in a problem with a multilevel structure necessitating the computation of spatial capacity and a solution to the multi-period optimal power flow. The problem variables further depend on the perspective of stakeholders in the electricity market. From the viewpoint of the DISCO, the solution intends to provide suitably sited DG capacity and maximise profit. As for the regulating authority the results offer the most suitable reward or penalty to drive the DISCO towards a low carbon network.In response, the regulated DISCO should then carry out DG planning in line with broader goals of society. This joint SG and IPP integration problem lends itself specific and unique constraints including generation class-specific net generation and energy curtailment.;The results reported in this thesis highlight the value and performance of the DISCO and regulation optimisation models on several power networks of varying size and composition. Numerical experiments demonstrate the developed DISCO optimisation model outperforms standard models, concerned primarily with capacity maximisation, in satisfying the following binding constraints: minimum IPP capacity and SG net energy.It is further revealed that integrating SG and IPP in a benchmark system with the proposed model increases profit by up to 23.7%, adding an improvement of 8% over a feasible standard model. In a case study of a network with extremely limited capacity-insufficient for minimum IPP-it is shown using the regulation optimisation model that to maintain the required DISCO profit the incentives can range from 2% to 14% of revenue for quota obligations spanning 10% to 50% of network load. The regulation optimisation model is compared with decoupling, a familiar method for removing energy retail impacts on revenue. Results show that regulation optimisation model is able to maintain a steadier profit with increasing quota requirements