Robust non-fragile power system stabilizer

This paper presents a step towards the design of robust non-fragile power system stabilizers (PSSs) for single-machine infinite-bus systems. To ensure resiliency of a robust PSS, the proposed approach presents a characterization of all stabilizers that can guarantee robust stability (RS) over wide range of operating conditions. A three-term controller (x₁ + x₂s)/(1 + x₃s) is considered to accomplish the design. Necessary and sufficient stability constraints for existing of such controller at certain operating point are derived via Routh–Hurwitz criterion. Continuous variation in the operating point is tackled by an interval plant model where RS problem is reduced to simultaneous stabilization of finite number of plants according to Kharitonov theorem. Controller triplets that can robustly stabilize vertex plants are characterized in a similar manner. The most resilient controller is computed at the center of maximum-area inscribed rectangle. Simulation results confirm robustness and resiliency of the proposed stabilizer.     

Effect of varying concentration and temperature on steady and dynamic parameters of low concentration photovoltaic energy system

Low-concentration photovoltaic (LCPV) system has huge potential for further cost reduction of solar photovoltaic (PV) power as compared to flat panel PV. The dependence of steady state and dynamic parameters on concentration and temperature is crucial to extract maximum power from solar photovoltaic system. This article aims to present the effect of varying concentration and temperature on steady state and dynamic parameters of LCPV system under actual test conditions (ATC). The rate of change in I_SC with solar irradiation i.e., dI_SC/dG is found as 0.25 A/W assuming ≈±1 °C change in module temperature. The effect of temperature on inherent material properties responsible for photo-conversion efficiency is studied using impedance spectroscopy technique. A linear response of series resistance of LCPV module is observed with respect to change in module temperature, i.e. dR_S/dT from 297 to 333 K is in the range of 1.15–1.20 Ω with a rate of 1 mΩ/K. From real-time analysis of LCPV system open-circuit voltage found decreasing from 21 to 20.6 V with temperature coefficient of voltage ≈−0.061 V/K. The dynamic resistance has a positive coefficient of module temperature i.e., dr_d/dT given by 0.49 Ω/K.     

An online power system static security assessment module using multi-layer perceptron and radial basis function network

Efficient contingency screening and ranking method has gained importance in modern power systems for its secure operation. This paper proposes two artificial neural networks namely multi-layer feed forward neural network (MFNN) and radial basis function network (RBFN) to realize the online power system static security assessment (PSSSA) module. To assess the severity of the system, two indices have been used, namely active power performance index and voltage performance index, which are computed using Newton–Raphson load flow (NRLF) analysis for variable loading conditions under N − 1 line outage contingencies. The proposed MFNN and RBFN models based PSSSA module, are fed with power system operating states, load conditions and N − 1 line outage contingencies as input features to train the neural network models, to predict the performance indices for unseen network conditions and rank them in descending order based on performance indices for security assessment. The proposed approaches are tested on standard IEEE 30-bus test system, where the simulation results prove its performance and robustness for power system static security assessment. The comparison of severity obtained by the neural network models and the NRLF analysis in terms of time and accuracy, signifies that the proposed model is quick, accurate and robust for power system static security evaluation for unseen network conditions. Thus, the proposed PSSSA module implemented using MFNN and RBFN models are found to be feasible for online implementation.     

Stochastic mid-term generation scheduling incorporated with wind power

A challenge now facing system operator is how to schedule optimally the generation units in a wind integrated power system over a one year time horizon considering the effects of wind forecasting and variability; also, regarding the effects of load uncertainty. By the same token, this paper first develops a new formulation for Stochastic Mid-term Generation Scheduling (SMGS). In the formulation, 2m + 1 point estimate method is developed to accurately estimate the output variables of Mid-term Generation Scheduling (MGS) problem. Then, the formulation is combined with adaptive modified gravitational search algorithm and a novel self-adaptive wavelet mutation strategy for the establishment of new robust algorithm for the present problem. It is noteworthy to say that the classical methods considered certain wind information in the deterministic solution of the MGS problem which is not the realistic approach. However, this study improves modeling of wind–thermal system in the MGS problem by considering possible uncertainties when scheduling the generators of power system. The proposed model is capable of taking uncertainty of load and wind into account. The proposed method is applied on two test cases and the numerical results confirmed the efficiency and stability of the proposed algorithm.     

Transmission congestion management in bilateral markets: An interruptible load auction solution

This paper demonstrates that appropriate invocation of interruptible loads by the independent system operator (ISO) can aid in relieving transmission congestion in power systems. An auction model is proposed, for an ISO operating in a bilateral contract dominated market, for real-time selection of interruptible load offers while satisfying the congestion management objective. The proposed congestion management scheme using interruptible loads can specifically identify load buses where corrective measures are needed for relieving congestion on a particular transmission corridor. The N − 1 contingency criterion has been taken into account to simulate various cases, and hence, examine the effectiveness of the proposed method. It has been shown that the method can assist the ISO to remove the overload from lines in both normal and contingency conditions in an optimal manner.     

A new optimal unified power flow controller placement and load shedding coordination approach using the Hybrid Imperialist Competitive Algorithm-Pattern Search method for voltage collapse prevention in power system

As power systems become more complex and heavily loaded, voltage collapse has become one of the most destructive events in modern power systems leading to blackouts in electric utilities worldwide. Voltage collapse is mainly caused by operating power systems at lower stability margins due to a surge in electric power demand. This paper presents an optimal unified power flow controller (UPFC) placement and load shedding coordination approach for voltage collapse prevention in N − K (K = 1, 2 and 3) contingency condition using Hybrid Imperialist Competitive Algorithm-Pattern Search (HICA-PS). ICA is the main optimizer of the proposed algorithm while pattern search is applied to further fine tune the results of the ICA. To show the effectiveness of the proposed approach in preventing voltage collapse in complex power systems, we implemented it on the New-England 39 bus power system. Its performance was also compared to that of some classical optimization techniques. Decrease in load shedding amounts, continuity of energy supply and voltage collapse prevention is the main positive features of the proposed approach.     

Optimization models based on GM (1, 1) and seasonal fluctuation for electricity demand forecasting

In this paper, a novel combined approach which combines the first-order one-variable gray differential equation (GM (1, 1)) model derived from gray system theory and seasonal fluctuation from time series method (SFGM (1, 1)) is proposed. This combined model not only takes advantage of the high predictable power of GM (1, 1) model but also the prediction power of time series method. To improve the forecasting accuracy, an adaptive parameter learning mechanism is applied to SFGM (1, 1) model to develop a new model named APL-SFGM (1, 1). As an example, the statistical electricity demand data from 2002 to 2011 sampled from South Australia of Australia are used to validate the effectiveness of the two proposed models. Simulation and graphic results indicated that both of two proposed models achieve better performance than the original GM (1, 1) model. In addition, the APL-SFGM (1, 1) model, which is actually an adaptive adjustment model, obtains a higher forecasting accuracy as compared to the SFGM (1, 1) model.     

Power and energy management of grid/PEMFC/battery/supercapacitor hybrid power sources for UPS applications

This paper presents a hybrid power and energy source supplied by a proton exchange membrane fuel cell (PEMFC) as the main power source in an uninterruptible power supply (UPS) system. To prevent the PEMFC from fuel starvation and degradation and realize their seamless linking in the hybrid UPS system, the power and energy are balanced by the battery and/or supercapacitor (SC) as two alternative auxiliary power sources. Based on the modeling and sizing of hybrid power and energy components, the power and energy management strategies and efficiency measurements of four operating modes in UPS system are proposed. To evaluate the proposed strategies, an experimental setup is implemented by a data acquisition system, a PEMFC generating system, and a UPS system including AC/DC rectifier, DC/AC inverter, DC/DC converter, AC/DC recharger and its intelligent control unit. Experimental results with the characteristics of a 300 W self-humidified air-breathing of PEMFC, 3-cell 12 V/5 Ah of batteries, and two 16-cell 120 F/2.7 V of SCs in parallel corroborate the excellent management strategies in the four operating modes of UPS system, which provides the basis for the optimal design of the UPS system with hybrid PEMFC/battery/SC power sources.     

Performance of printable supercapacitors in an RF energy harvesting circuit

We report the fabrication of a supercapacitor on a plastic substrate with mass-production-compatible methods and its characterisation using galvanostatic and voltammetric methods. The supercapacitor is prepared in ambient conditions using activated carbon and an aqueous, non-acidic electrolyte. The obtained capacitances are 0.45 F and 0.21 F for device sizes of 4 cm² and 2 cm², respectively. Additionally, we demonstrate the utilisation of the supercapacitor in an autonomous energy harvesting and storage system. The RF energy harvester comprises a printed loop antenna and a half-wave organic diode rectifier operating at 13.56 MHz frequency. The harvested energy is stored in two supercapacitors connected in series to increase the maximum operating voltage. In order to power a device such as a sensor or a small indicator display, voltage regulation is needed. A voltage regulator, implemented as an application specific integrated circuit (ASIC), was designed for this purpose, and fabricated commercially. We demonstrate the ability of the harvester storage unit to power the regulator for hours with a constant regulator output voltage and power. The effect of supercapacitor charging time on the actual supercapacitor charging state is also discussed, as a slower charging rate is found to have a significant effect on the output of the supercapacitor.     

Maclaurin–Newton algorithms in 132 kV subtransmission security simulations

This paper examines how applicable approximate Jacobian inversions are when implemented in the security analysis simulations of 132 kV power subtransmission. The complete Scottish 400/275/132 kV power transmission network was simulated, including the 132 kV subtransmission network with its high r/x ratios. Both the coupled and decoupled Maclaurin–Newton load flow algorithms were tested. It was proved that high r/x ratios found in the 132 kV level, five times higher than in 400/275 kV, have an important influence on convergence and accuracy of the inversion Jacobian load flow algorithms. It was found that the decoupled inversion load flow was applicable for 132 kV, it converged regularly, but had worse convergence and accuracy characteristics, compared to 400/275 kV applications, while the coupled inversion load flow was not applicable at all for 132 kV, it always diverged.     

Study on FRT compliance of VSC-HVDC connected offshore wind plants during AC faults including requirements for the negative sequence current control

In this paper three new control modules are introduced for offshore wind power plants with VSC-HVDC transmission. The goal is to enhance the Fault Ride Thought (FRT) capability of the HVDC system and the connected offshore wind power plant during balanced and unbalanced AC faults. Firstly, a positive-sequence-voltage-dependent (PSVD) active current reduction control loop is introduced to the offshore wind turbines. The method enhances the performance of the offshore AC voltage drop FRT compliance strategy. Secondly, an adaptive current limiting control strategy which operates simultaneously on the positive and the negative sequence current is discussed. It enables negative sequence current injection, while at the same time respecting the maximum fault current capacity of the HVDC converter station. Finally, a state machine is proposed for the VSC-HVDC system and for the offshore wind turbines respectively. It coordinates the fault and the post-fault response during balanced as well as unbalanced faults, ensuring a smooth shift from the normal operating point towards the fault and the post-fault period. The test system consists of a two level VSC-HVDC link, rated at ±250 kV, connecting an offshore wind power plant with 700 MW generation capacity. Simulation results with a detailed EMT type model in PSCAD/EMTDC environment are presented.     

Particle swarm optimization algorithm for capacitor allocation problem in distribution systems with wind turbine generators

This paper aims at adopting the Particle Swarm Optimization (PSO) technique to find the near-optimal solutions for the capacitor allocation problem in distribution systems for the modified IEEE 16-bus distribution system connected to wind energy generation based on a cost function. The proper allocation and the optimized number of capacitors have led to adequate power losses reduction and voltage profile enhancement. Because of the wind power generation variations due to the nature of wind speed intermittency and the lack of reactive power compensation, the problem under study have been presented involving a nonlinear fitness function. In order to solve it, the corresponding mathematical tools have to be used. The formulated fitness cost function has consisted of four terms: cost of real power loss, capacitor installation cost, voltage constraint penalty, and capacitor constraint penalty. PSO technique has been used to obtain the near-optimum solution to the proposed problem. Simulation results demonstrate the efficiency of the proposed fitness cost function when applied to the system under study. Furthermore, the application of PSO to the modified IEEE 16-bus system has shown better results in terms of power losses cost and voltage profile enhancement compared to Genetic Algorithm (GA). In order to verify the successful adaptation of PSO toward attaining adequate near-optimal capacitor allocations in distribution systems, this metaheuristic technique has been employed to the large-scale IEEE 30-bus system. The proposed PSO technique has provided adequate results while modifying the objective function and constraints to include the power factor and transmission line capacities for normal and contingency (N-1) operating conditions.     

Model of distribution system total supply capability considering feeder and substation transformer contingencies

This paper proposes a model for calculating the total supply capability (TSC) for distribution system considering both feeder and substation transformer contingencies. Existing models and methods for TSC only consider substation transformer contingencies and ignore feeder contingencies. However, the feeder contingencies occur much more frequently than substation transformer contingencies in practice. Moreover, some operation state fail the feeder contingencies N − 1 verification even they pass the transformer contingencies N − 1 verification. In this paper, a TSC model is firstly proposed in which feeder and transformer N − 1 contingencies are fully considered. This model is designed in feeder level, which means the topology of interconnection among feeders is accurately modeled. Secondly, a supplementary model for load balancing is set up for a better load distribution solution on feeders and transformers at TSC loading. Finally, the method is tested in a test distribution system and a real partial distribution network and the results are verified by the traditional N − 1 simulation.     

Direct power control of a multilevel inverter based active power filter

A cascaded H-bridge multilevel inverter based active power filter with a novel direct power control is proposed in this paper. It can be directly connected to medium/high voltage power line without using the bulky transformer or passive filter. Due to the limited switching frequency (typically below 1 kHz) of high-power solid-state devices (GTO/IGCT), multiple synchronous/stationary reference frame current controllers are reviewed and derived. Based on this, a novel current controller is proposed for harmonic current elimination and system power factor compensation. Furthermore, a synchronous/stationary hybrid structure can be derived with fundamental de-coupling control. The instantaneous reactive power theory and synchronous reference frame based control are compared based on mathematical models. A direct power control concept is then derived and proposed. It is equivalent as the hybrid synchronous/stationary frame current controller, but has a simpler implementation. It has clear physical meaning and can be considered as a simplified version of the hybrid frame current controller. Simulations on a 4160 V/1.2 MVA system and experimental results on a 208 V/6 kVA laboratory prototype are presented to validate the proposed active power filter design.     

Analysis and comparison of current control methods on bridgeless converter to improve power quality

In this paper, the performance analysis of power factor correction (PFC) current control methods is presented for a bridgeless converter operating under continuous conduction mode (CCM). The bridgeless converter has been proposed using proportional-integral control (PIC), average sliding control (ASC) and predictive current control (PCC) methods to obtain unity power factor (PF) and lower total harmonic distortion (THD) of input current. Several PFC methods have been developed to satisfy the international standards such as IEC 61000-3-2 and IEEE 519-1992. The detailed steady-state theoretical analysis of the bridgeless converter is presented, which is verified by simulations and experiments carried out on 600 W and 50 kHz. The performance of the current control methods for the bridgeless converter is investigated by a Matlab/Simulink program. The experiments performed in the laboratory under input voltage and load variation ranges verify the theoretical and simulation studies. The control methods are programmed by the TMS320F2812 DSP microprocessor.     

Multi-objective optimization operation with corrective control actions for meshed AC/DC grids including multi-terminal VSC-HVDC

This paper presents a multi-objective optimal operation of meshed AC/DC power grids including multi-terminal voltage-source-converter-based high-voltage direct current (VSC-MTDC) systems. The proposed approach is modeled as a corrective security-constrained optimal power flow (CSC-OPF) problem, with the minimization of both the operation cost and power loss as the objectives. Moreover, it provides a cost-effective solution to assist in decision-making, and improves the system security during operation. The N − 1 contingency security criterion is enforced for both AC and DC transmission networks, and corrective control is used to eliminate or alleviate post-contingency security violations. The corrective control actions used in this paper include not only secure operation control actions, but also economical post-contingency corrective control of the multi-terminal VSC-HVDC. To increase the computation speed, a contingency screening technique is applied to CSC-OPF by efficiently selecting the most severe case of the N − 1 contingency, as obtained using a voltage security index (VSI). The proposed approach uses the non-dominated sorting genetic algorithm (NSGA-II) to find multi-objective OPF solutions by checking the post-contingency state feasibility while taking into account post-contingency corrective actions. Simulation results confirm the validity and effectiveness of this approach.     

Energy management strategy for fuel cell/battery/ultracapacitor hybrid vehicle based on fuzzy logic

In order to enhance the fuel economy of hybrid vehicle and increase the mileage of continuation of journey, a fuzzy logic control is utilized to design energy management strategies for fuel cell/battery (FC + B) hybrid vehicle and fuel cell/battery/ultra-capacitor (FC + B + UC) hybrid vehicle. The models of hybrid vehicle for FC + B and FC + B + UC structure are developed by electric vehicle simulation software ADVISOR which uses a hybrid backward/forward approach. The results demonstrate that the proposed control strategy can satisfy the power requirement for four standard driving cycles and achieve the power distribution among various power sources. The comprehensive comparisons with the power tracking control strategy which is wide adopted in ADVISOR verify that the proposed control strategy has better rationality and validity in terms of fuel economy and dynamic property in four standard driving cycles. Therefore, the proposed strategy will provide a novel approach for the advanced energy management system of hybrid vehicle.     

A new wavelet network based method to estimate the lightning-related risk of failure of power system apparatus

This paper proposes a new and fast wavelet network based method for estimating the risk of failure caused by lightning overvoltages in arrester protected networks. First, failure risks obtained by simulations are used as the training data for training the wavelet network. The trained wavelet network is then used for accurate and fast estimating of the lightning-related risk of failure of power system apparatus for all possible conditions. The accuracy of the proposed method has been tested and verified under various conditions in the 230 kV network of Sistan–Baluchestan. Performance of the new method has also been compared with several existing methods under same conditions, and the test results show better accuracy of the proposed method. The proposed method not only does not have the restriction of conventional methods, but also it does not have the limitations associated with traditional neural networks based algorithms such as convergence to local optimum points, over-fit and/or under-fit problems. The main contribution of the paper is an accurate (due to proper selection of the training data set based on the k-fold cross validation technique and using wavelet network for estimation), fast (mean calculation time for the network risk of failure computation is 54 s) and simple wavelet network-based algorithm (as compared to the conventional algorithms) for estimating the lightning-related risk of failure of power system apparatus.     

A PSO based approach for multi-stage transmission expansion planning in electricity markets

This paper presents a particle swarm optimization (PSO) based approach to solve the multi-stage transmission expansion planning problem in a competitive pool-based electricity market. It is a large-scale non-linear combinatorial problem. We have considered some aspects in our modeling including a multi-year time horizon, a number of scenarios based on the future demands of system, investment and operating costs, the N − 1 reliability criterion, and the continuous non-linear functions of market-driven generator offers and demand bids. Also the optimal expansion plan to maximize the cumulative social welfare among the multi-year horizon is searched. Our proposed PSO based approach, namely modified PSO (MPSO), uses a diversity controlled PSO to overcome the problem of premature convergence in basic PSO (BPSO) plus an initial high diversity swarm to cover the search space efficiently. The MPSO model is applied to the Garver six-bus system and to the IEEE 24-bus test system and compared to the BPSO model and a genetic algorithm based model.     

Performance investigation of linear and nonlinear controls for a fuel cell/supercapacitor hybrid power plant

In this paper, linear proportional–integral (PI) and nonlinear flatness-based controllers for dc link stabilization for fuel cell/supercapacitor hybrid power plants are compared. For high power applications, 4-phase parallel boost converters are implemented with a switching interleaving technique for a fuel cell (FC) converter, and 4-phase parallel bidirectional converters are implemented with a switching interleaving technique for a supercapacitor converter in the laboratory. As controls, mathematical models (reduced-order models) of the FC converter and the supercapacitor converter are given. The prototype small-scale power plant studied is composed of a PEMFC system (the Nexa Ballard FC power generator: 1.2 kW, 46 A) and a supercapacitor module (100 F, 32 V, based on Maxwell Technologies Company). Simulation (by Matlab/Simulink) and experimental results demonstrate that the nonlinear differential flatness-based control provides improved dc bus stabilization relative to a classical linear PI control method.