Abstracts:In this study, a methodology to develop hourly demand scenarios in a medium-term horizon for primary distribution substations is presented and applied to a case study. The main contribution of this study is that it addresses successfully the effect of saturation of distribution feeders in the medium term due to sustained growth in demand. In addition, the method is able to simulate the future necessary reconfiguration and reinforcements in the distribution feeders. A detailed comparative study of five well-known forecasting techniques, to estimate future demand, is conducted. The methodology is tested with hourly power records, measured from 2008 to 2013, in 169 feeders of the distribution company of Santiago, Chile. When the performance of the forecasting techniques is compared, results of one-year-ahead forecasting, with hourly resolution, show that multilayer perceptron neural networks outperformed the other techniques, having a MAPE lower than 9% for more than 96% of the feeders. A final evaluation for 13 feeders, using the forecasted and registered demand from 2014 to 2017, shows that the MAPE remains in a low range (9–13%), improving the method currently used by the industry. The overall results indicate that reconfiguration and reinforcement allocation are key elements for medium-term hourly demand forecasting in distribution feeders.

Abstracts:The high penetration of residential air conditioners (RACs) poses a growing concern in emerging fault-induced delayed voltage recovery (FIDVR) in power systems. FIDVR is expected to be a significant threat to the stability and reliability of future power grids. Hence, the system planners should carry out appropriate simulation studies to mitigate the severe consequences of FIDVR events. A key question to implement these studies is how to determine the worst condition which results in FIDVR. Most of the actual FIDVR events have been experienced in the hot hours of the day and this issue makes one curious to think about the relationship between the FIDVR events and the ambient temperature. In this regard, a novel temperature-dependent RAC model is presented and verified by using laboratory tests. Furthermore, two cases with different power system loading patterns, i.e. the peak temperature hour and the peak demand hour, are examined. The proposed RAC model is implemented on the IEEE 118-bus test system. Moreover, an actual FIDVR event reported in Iran has been reproduced employing the proposed RAC model. Implemented simulations reveal that to precisely reproduce the recorded FIDVR event, it is necessary to consider the ambient temperature when the fault has been occurred.

Abstracts:In order to provide a reliable service and supply the demand most of the time, all generators in a power grid should be subjected to an effective maintenance plan. The smarter the maintenance performed could result in a better performance of the system. However, a challenge is to minimise maintenance costs that do not compromise the benefits. Considering these facts, this study presents a reliability-based smart-maintenance approach of generators to compute the net-maximum economic benefit. The approach is derived from Kijima model type I to characterise the impact of maintenance over the component's virtual age, and Markov chains to model the component's lifetime. To achieve a more realistic model, generators' failure and repair rates are considered time-dependent variables. Then, the optimum preventive maintenance schedule is obtained by using an advanced algorithm named accelerated quantum particle swarm optimisation in combination with sequential Monte Carlo simulation. The effectiveness of the approach is investigated through a case study with four different scenarios: (i) no preventive maintenance plan, (ii) yearly periodic preventive maintenance, (iii) reliability-centred maintenance and (iv) smart maintenance. The results suggest that the approach is convenient for power system generators and delivers a significant knowledge contribution in the area of maintenance.

Abstracts:This study proposes a robust sub-synchronous damping controller based on fractional-order sliding mode control (FOSMC) method to mitigate sub-synchronous control interaction (SSCI) induced by DFIG-based wind park connected to series-compensated transmissions. Firstly, the nonlinearity of DFIG is cancelled through feedback linearisation. Secondly, FOSMC is designed and applied to the control loop of the DFIG rotor-side converter. During the design process, the extra degree of freedom, provided by the fractional operator, is employed to achieve fast SSCI-damping. Thirdly, a genetic algorithm is used for parameter optimisation with the aim of making system eigenvalues approach the left plane. The effectiveness of the proposed damping controller is evaluated based on the adapted IEEE first benchmark model, non-aggregated wind system model with a realistic configuration, and experimental platform. Simulation and experiment results demonstrate the superior damping performance of FOSMC under different wind speeds, compensation levels, and the number of online wind turbines. Moreover, FOSMC also shows the robustness under parameter uncertainty, control parameter perturbation, and symmetric (three-phase short circuit) fault.

Abstracts:Corona discharges require high and non-uniform field to take place. In this research, the difficulty of suggesting the required arrangement of optimum fictitious charges, their positions and values inside the conductor in charge simulation method (CSM) is solved using genetic algorithm, satin bowerbird optimisation and whale optimisation algorithm. A hybrid model based on combining CSM with proposed optimisation techniques is provided to simulate and calculate the non-uniform electric field that is created by a hyperbolic needle-to-plane configuration expressed in a dielectric medium. The accuracy of electric-field simulation results is investigated by estimating per cent potential error and the maximum deviation angle of the normal field vector at the conductor surface for each proposed optimisation algorithm, taking into account the assessment of the efficiency of all proposed optimisation algorithms. To investigate the validity and accuracy of the proposed model, a comparison is held with available previous simulation and experimental data.

Abstracts:The investigation of the effects of demand flexibility on the pricing strategies and the profits of electricity retailers has recently emerged as a highly interesting research area. However, the state-of-the-art, bi-level optimisation modelling approach makes the unrealistic assumption that retailers treat wholesale market prices as exogenous, fixed parameters. This study proposes a tri-level optimisation model, which drops this assumption and represents the wholesale market clearing process endogenously, thus capturing the realistic implications of a retailer's pricing strategies and the resulting demand response on the wholesale market prices. The scope of the examined case studies is three-fold. First of all, they demonstrate the interactions between the retailer, the flexible consumers and the wholesale market and analyse the fundamental effects of the consumers’ time-shifting flexibility on the retailer's revenue from the consumers, its cost in the wholesale market and its overall profit. Furthermore, they analyse how these effects of demand flexibility depend on the retailer's relative size in the market and the strictness of the regulatory framework. Finally, they highlight the added value of the proposed tri-level model by comparing its outcomes against the state-of-the-art bi-level modelling approach.

Abstracts:This study proposes a new multi-agent control system (MACS) for energy management in a microgrid (MG). The latter includes photovoltaic arrays and wind turbine generators as renewable energy resources. It also has microturbines, fuel cell units, and an energy storage system (ESS). The MACS determines the optimal active and reactive powers of the dispatchable energy resources. It also identifies the ESS charging/discharging times. The MACS supervises energy management among local distributed generators (DGs), main grid, and loads to maximise profit while satisfying all operational constraints. The MG collaborates in the electricity market. It purchases/sells active and reactive powers from/to the main grid. Furthermore, MACS dynamically corrects the possible voltage violations and eliminates line congestion using the coordination of reactive power control. Agents at dispatchable DGs and ESS buses tackle the optimal economical operation. Other agents regulate the nodes voltages and remove line congestions. A parallel computing-based full dynamic simulation model of the MACS and the MG power system is implemented. Moreover, the performance comparisons between the proposed MACS and recent approaches are presented to evaluate the performance of MACS.

Abstracts:In many China's enterprise-owned power grids (EPGs), the frequently changing operation state and the poor reliability of some outdated facilities may lead to inaccuracy or even malfunctions of the traditional pre-decision-making emergency control systems, which have already caused several blackouts in EPGs. To solve this problem, a real-time decision-making emergency control system based on the detailed time-domain transient stability simulation is designed. Based on the trajectory characteristics of the stability restoration process of EPGs, the stability restoration criteria are proposed to significantly shorten the simulation time needed to judge the elimination of a certain stability problem. Fast decision-making algorithms for frequency instability, rotor angle instability and branch overload with relatively low computational cost are introduced. Control strategies can be determined within a specific time after faults are detected. The corresponding countermeasures are directly executed when the strategy is obtained. The system configuration is designed to be capable of dealing with complicated and unanticipated faults, such as cascading outages and unexpected grid splitting. The test results of a 31-node practical EPG show that the proposed algorithms and the system configuration are practical and efficient. This work is a meaningful exploration of the real-time decision-making emergency control system.

Abstracts:As known, voltage source converter-based high-voltage direct current (VSC-HVDC) transmission system is widely utilised in actual power grid. It is suitable for asynchronous networking, such as the connection of offshore wind farm to main power grid. Generally, as primary protection principle, travelling wave (TW) protection is adopted based on the technologies of ABB and SIEMENS, of which is only transient quantity based protection principle instead of true TW protection principle and has no fault direction discrimination ability. Besides, because of the large capacitances applied on converter station, the voltage TW (VTW) information cannot be detected by the protection units of two terminals. Therefore, this study proposes a novel TW directional pilot protection based on current TW (CTW) and direct current voltage. In the beginning, this study the unusual propagation characteristic of VTW or CTW along with the VSC-HVDC transmission line. Afterwards, this study proposes a novel fault direction discrimination criterion using the integral of instantaneous TW power. Eventually, using PSCAD/EMTDC, a typical <inline-formula><alternatives><tex-math notation="LaTeX">$pm 400,{rm kV}$</tex-math><mml:math overflow="scroll"><mml:mo>&#xb1;</mml:mo><mml:mn>400</mml:mn><mml:mspace width="thinmathspace" /><mml:mrow><mml:mi mathvariant="normal">kV</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="IET-GTD.2019.0394.IM1.gif" /></alternatives></inline-formula> VSC-HVDC transmission system simulation model is constructed to verify novel protection's performances.

Abstracts:To implement privacy protection and high-efficiency distributed computing of the large-scale dynamic optimal power flow (DOPF) of the multi-area interconnected power system, the regularised term (RT) and primal&#x2013;dual interior-point method (PDIPM), denoted by R-PDIPM, is proposed to distribute and parallel such DOPF solutions. First, the DOPF is transformed into a prime block-angular problem through the replication of the coupling node variables, and the multi-area decoupling of the power grid is realised. However, it is easier to develop a singular (ill-conditioned) block matrix of Newton's system under the distributed computing of PDIPM. Second, though introducing the RT into the Lagrangian function of PDIPM based on regular technology, the matrix of Newton's system becomes quasi-definite and strongly factorisable. The robustness of distributed computing of PDIPM is enhanced, and the convergence speed is also improved. Case studies on the 3012 and 3074 node systems over 2&#x2013;4 time intervals are presented. The results show that the R-PDIPM is more robust in efficiently solving the problem than PDIPM in distributed computing, which is suited for distributed calculation of DOPF in a large-scale multi-area power system.