Ant colony optimisation has been tailored to suit maximum power point tracking (MPPT) in photovoltaic (PV) systems and is presented in this study. Artificial ants are deployed in the solution space and are made to forage and the ants which find better sources of food are retained while ants fail to search effectively are deleted from the population. The greedy search of potential ants for better food location leads to identification of higher power peaks in the PV system. The concept is modelled suitably and MPPT curves in a few PV configurations are simulated and found to be promising. Experiments were also conducted to show the veracity of the new method.

Head-sensitive forbidden and restricted zones of large hydropower units are challenging the automatic generation control (AGC) as admissible operating zones are discontinuous and variational. This study focuses on the AGC of such a large hydropower plant to ensure the stability, security and timeliness of power grids. A methodology is developed to solve the unit commitment (UC) and load distribution in AGC. This methodology identifies in advance all feasible unit combinations under different water heads and determines admissible operating zones using combinatorial mathematics techniques. A fast strategy that includes the accurate estimation of varying water heads helps to eliminate infeasible unit combinations. Minimising the number of units working in restricted zones and times of unit output passing through forbidden zones is used to optimise the UC, where priority orders of units are introduced to evaluate UC schemes with the same objective value. Finally, a dynamic programming based model is formulated to solve an economic load distribution among operating units. The methodology is applied to the AGC of the Nuozhadu with nine 650 MW units of two different types. Three cases indicate that the number of units working in restricted zones and times of unit output passing through forbidden zones is significantly reduced.

Increasing penetration of wind power has a negative effect on system frequency deviation due to the fast variability and uncertainty characteristics of wind. In this study, a wind power variation prediction-based automatic generation control (AGC) feedforward control method is applied within the conventional AGC framework to minimise system frequency and tie-line deviations. Firstly, the variogram function is introduced for analysing the characteristics of wind power variations. A relationship between the variogram of wind power and the trend component of wind power is found and then a three-parameter power-law model is established. Then, the generation rate constrains of AGC generators is considered as the main constraint factor that influences wind power smoothing. By predicting the wind power variations in AGC control time-scale, a coordination AGC feedforward control strategy is proposed. The control strategy makes different types of AGC generators act in advance to improve the ability of the power system, corresponding to the forecasted ramp variations in wind power generation. Finally, the performance of the proposed coordination control strategy is verified and tested using the actual data from China. Simulation results show that with this new strategy, frequency deviation under wind power variations can be effectively decreased.

High renewable penetration and inevitable data corruptions can prominently jeopardise the security of power systems and greatly challenge the conventional situation awareness (SA). This study proposes an enhanced SA model that solves two major difficulties faced by the conventional SA. The first difficulty is to accurately detect anomalies, especially the imperceptible variation of renewable power output. This is addressed by a novel aggregation of random matrix and long short-term memory network. The model's high accuracy and alertness in real-time anomaly detection are achieved by a newly proposed perceptual indicator. The second difficulty is to be robust against multiple data corruptions. In this connection, a dedicated workflow is designed to mitigate the impact of data corruptions from two stages, which ensures the robustness of the enhanced SA model. By comparing with several existing conventional SA models, the proposed enhanced SA model has shown its prominent superiority in several practical scenarios. In addition, a fast security check is also achieved by the enhanced SA model to indicate the security margin of the system on different renewable penetration levels. The enhanced SA model can reinforce the system operators' observability on insecure risks and hedge them against potential data manipulations or cyber attacks.

The photovoltaic (PV) system contemplated in the study displays multiple peaks on power–voltage (P–V) curve under partial shading condition (PSC) results in a complicated maximum power point tracking (MPPT) process. Conventional MPPT algorithms work in an effective manner under uniform irradiance conditions. However, these algorithms are unable to track the global peak effectively under different irradiance conditions. In this study, a velocity of particle swarm optimisation-based Levy flight (VPSO-LF) for Global MPPT of PV system under PSCs is proposed. For the changes in irradiance, when verified with VPSO-LF, tracking time and a number of iterations are fewer to reach the global peak of PV array. It also minimises the number of tuning parameters of the velocity of particle swarm optimisation (PSO). The proposed technique is simulated in MATLAB/SIMULINK as well as experimentally validated. It is observed that the results obtained using VPSO-LF is superior to conventional PSO and hill-climbing algorithm under different patterns of PV array.

With the increasing penetration of renewable energy sources in the power system, the power electronic inverters are widely used to interface with the grid, which will reduce the inertia of the power system. This study proposes ancillary inertial service from single-phase rooftop solar photovoltaic (PV) based inverter to the grid. The inertia emulation control technique transforms the behaviour of inverter like a synchronous generator under power imbalances. A hybrid energy storage system consisting of battery and supercapacitor (SC) has been connected at the DC bus to take care of the variability in PV output power and load fluctuations. The SC absorbs/injects the fast-varying power and provides the inertial response to arrest the frequency deviation and battery charges/discharges to bring back the frequency to the nominal value. Real-time simulation is carried out to test the system behaviour for different operating conditions using OPAL-RT 5700.

Renewable energy support schemes implementation increases the significance of renewable energy power plants (REPPs) in studying power market characteristics. In this study, an analytical approach is presented to investigate the impact of REPPs on transmission lines congestion. For this purpose, considering REPPs, social welfare maximisation problem corresponding to the spot electricity market should be solved by the independent system operator. A closed-form expression of the Lagrange multiplier (LM) of each congested line is presented to analytically demonstrate the role of the power system structure and strategic behaviour of conventional generation companies (GenCos) on the network congestion. The structural part of LM expression is decomposed into four components to distinguish the impact of GenCos from the impact of REPPs. The GenCos' strategic behaviour in the spot market bidding problem is simulated using well-known Q-Learning algorithm. The results confirm that REPPs deployment can remarkably affect both the structural and behavioural parts of the LM and emphasise the significance of the GenCos strategic behaviour on the occurrence of congestion. The results illustrate that since renewable energy support schemes may increase the possibility of congestion and GenCos' strategic behaviour, it is essential to take power system characteristics into account in their design.

During the last two decades, the use of residential photovoltaic (PV) systems has been widely promoted by governments through various support mechanisms such as feed-in-tariffs, net-metering, net-billing, etc. These support schemes have developed a secure investment environment, increasing the penetration level of PVs in low-voltage distribution grids. Nonetheless, increased PV integration may introduce several technical problems regarding the secure operation of distribution grids. Battery energy storage (BES) systems can mitigate such challenges, but the high capital cost is one of the most important limiting factors towards the widespread use of these systems. In fact, the financial viability of integrated PV and BES systems under different support schemes remains an open issue. In this study, the profitability of PV and BES systems is evaluated through an advanced techno-economic model, that provides the optimal size of PV-BES system in terms of net present value, based on the electricity production and consumption profile of the installation, PV and BES systems costs, and electricity charges. The proposed model may be a useful tool for prosumers, grid operators and policymakers, to assess the impact of various incentive policy schemes and different BES operation strategies on the economic viability of PV-BES systems.

High power rated modern wind generators are demanding immaculate performance and greater reliability from the power electronics interface. In order to keep up to the challenges, advanced multilevel front-end rectifiers and parallel operation of rectifiers are researched. A higher number of semiconductor switches make reliability estimation and feasibility of converters a factor of industrial interrogation. This study focuses on the operation, reliability, and economic feasibility analysis of a parallel unity power factor rectifier (PUPFR). Each branch of the PUPFR has a three-phase diode rectifier and each phase of which is equipped with bidirectional switching blocks. Suitability of uninterrupted operation with lower down-time for instances of one branch failure, the system discussed provides higher feasibility, reliability, and options of modularity. The reliability is assessed by quantifying the failure rate of each component of the converter topology. The feasibility analysis of the PUPFR focuses on quantitative evaluation based on component pricing for initial cost, maintenance, power-loss calculation, operational cost, and capacity factor. The PUPFR is comparatively assessed with respect to its single branch topology, i.e. the unity power factor rectifier. Both the topologies are simulated in MATLAB^®/Simulink and the system is experimentally validated on a 1 kW hardware setup.

Challenges of microgrids (MGs) energy management have gained more relevance with the presence of uncertainties in power generation and local loads. These problems significantly increase when related to network of smart MGs (NSMG). To address these challenges, this study presents a stochastic constrained control problem for the optimal management of a cooperative NSMG with interconnections allowing power exchanges. In this model, each MG can exchange power locally among each other as well as with the main electric grid. The proposed control approach is based on a linear-quadratic Gaussian problem definition for the optimal control of power flows under quadratic constraints limiting the variability of the power exchange as well as of the stored energy in each MG. The developed framework is applied to a cooperative network of four smart MGs to test and validate its effectiveness and performance. The network is connected to the main electric grid allowing power exchanges. The results demonstrate that the role of energy storage systems is undoubtedly becoming more and more relevant in the context of reacting to the stochastic behaviour of the balance between produced and consumed powers in MGs.

Following the high penetration of synchronous generators (SGs) in the power network, optimal overcurrent coordination improvement under faulty conditions has become a crucial problem. To reduce the overcurrent relay operating time, a new overcurrent relay curve is proposed in this study. Then, the overcurrent coordination problem is overcome by using a robust combinatorial optimisation method. Additionally, SG sizing and location is performed to verify the merits of both the proposed relay curve and the applied optimisation algorithm. The proposed relay curve performance is compared with other non-standard relays characteristic available in the literature for a standard microgrid. Then, the proposed relay curve is applied to both the 8-bus transmission and the 33 kV distribution portion of the 30-bus IEEE standard power test systems. Then, the SG transient stability for different fault locations is analysed. Finally, an accurate comparison between the proposed relay curve and standard/non-standard curves available in the literature is provided by applying the same optimisation method and network topology. The simulation results confirm the superiority of the proposed relay curve.

Hydropower takes on many tasks such as peak regulation and frequency modulation in the power system. In the actual operation process of the hydro-turbine governing system, there is a certain degree of pressure pulsation in the draft tube. When the system is under unrated operating conditions, the draft tube pressure pulsation is more intense, and its dynamic behaviour becomes more complicated. In this study, the draft tube pressure pulsation is introduced into the dynamic model of the hydro-turbine governing system, and its influences on the transient characteristics of the system are analysed under unrated conditions and rated conditions. The authors find that compared with the rated conditions, the draft tube pressure pulsation under unrated conditions has more significant effects on the transient characteristics of the system. A damped frequency of pressure pulsation is proposed in this study which provides an efficient method of regulating the dynamic behaviour of the system in real operation. All these findings are expected to be helpful for further study of the influence of pressure pulsation on transient characteristics of hydropower systems and improving their dynamic characteristics under operating conditions.

In wind turbine systems, pitch angle controllers are employed to reduce the aerodynamic power gained during high wind speeds. On the other hand, passive filters are usually used to mitigate disturbances in grid-connected voltage source converters (VSCs). To avoid the risk of instability in the grid-connected VSC, as a result of resonance in the capacitive and inductive components, it is necessary to consider damping. In this study, the low pass filter timing constant of the pitch angle controller of the doubly-fed induction generator (DFIG) wind turbine was varied considering different time constants. The best timing response of the low pass filter was further used to analyse different filter topologies, in addition to a new control strategy that uses two trap passive filters with shunt resistor–capacitor as an active damper, in augmenting the DFIG wind turbine during grid fault. Simulation studies in PSCAD/EMTDC were carried out to compare the performance of the proposed scheme with some other conventional filter solutions for the DFIG wind generator, during a severe bolted three-phase to ground fault. The simulation results demonstrate the improved performance and faster recovery of the wind generator variables after the fault considering the proposed filter scheme.

The increasing contribution of wind turbine generators (WTGs) in power grids requires the control of wind generators and their impacts on the load frequency control (LFC). In this study, a detailed strategy for the control of WTGs in a smart power grid for LFC is presented. The WTGs are controlled by applying fuzzy logic controller with three inputs from wind velocity, frequency deviations, and wind velocity changes per second. The control takes into account for each WTG, an improved pitch angle controller to assist in fast damping of frequency deviations due to sudden high wind. Also, a feedback signal from frequency deviations, with the participation factor determined by a smart learning-based intelligent controller (BELBIC) is used to determine rotor speed deviations. The controller facilitates frequency stability, and lower variations in the output power of conventional units. Simulation results, performed on a test system with three interconnected zones, validate the effectiveness of the proposed control strategy.

Minimising emissions and operational costs are essential during energy production. To address this, a rational emission conversion factor-based optimal economic emission dispatch model is proposed to allocate generators in a dispatch fleet optimally. Additionally, the role of renewable energy (RE) generators in enhancing the decarbonised operation of power systems is investigated. A multi-objective function – consisting of fuel cost, RE forecasting deviation cost, and emission cost – is solved using the flower pollination algorithm, and the proposed scheme is successfully tested on the IEEE 30-bus and Indian utility 30-bus systems. The need for exact quantification of emissions and minimising the RE forecasting error, which offsets the benefits of RE, is demonstrated through various case studies.