Sources In Microgrid Research Articles

Synchrophasor based islanding detection for microgrids using moving window principal component analysis and extended mathematical morphology

Extensive deployment of non-dispatchable renewable energy sources in microgrids (MGs) has led to frequent fault events, DG and line trips and is arduous to discriminate islanding events (IEs) from other transient conditions. For enhanced grid security, time synchronised data from phasor measurement units is utilised. However, data handling at the control centre is tedious as system variables monitored often exhibit non-linear characteristics that impose a problem to the operator in discriminating between islanding and non-IEs. To cope with this, a zero non-detection zone, reliable and precise islanding detection method for data-intensive grid-connected MG, is proposed. Voltage phasors, frequency and rate of change of frequency from various locations are processed through moving window principal component analysis (MWPCA) cascaded with extended mathematical morphological filter (EMMF). MWPCA reduces data dimensionality and Q statistics obtained are passed to EMMF, which acts as a non-linear filter. Further, the islanding detecting factor identified all IEs within the prescribed time limit with minimum false alarms. Accuracy, precision and reliability demonstrated by using a case study model using DIgSILENT are encouraging. It can be adopted by operators to run MG securely. Further, testing of the proposed method on a typical utility feeder shows promising results.

Probabilistic optimal coordinated planning of molten carbonate fuel cell-CHP and renewable energy sources in microgrids considering hydrogen storage with point estimate method

The ever-growing augmentation of Renewable Energy Sources (RES) and Combined Heat and Power (CHP) units in microgrids (MG) exacerbates schedule management requirements in such systems. In this paper, a modified hybrid Bird Mating Optimization Differential Evolution (BMO-DE) algorithm is developed to address the mixed integer nonlinear programming problem of MG units’ probabilistic optimal planning. The proposed MG structure is consisted of MCFC-CHP, Wind Turbines (WT) and Photovoltaics (PV). The presented stochastic model schedules MG units coordinately, while the strategy of MCFC-CHP hydrogen storage is taken into account. The proposed solution models the uncertain parameters of electricity price, wind speed and sun irradiation using the 2m + 1 Point Estimate Method (PEM). The modeling of uncertain parameters results in more accurate planning and operation of the entire system. The proposed solution is applied on a 33-bus distribution network. In this manner, the total power loss decreased to 358.5 kW and the total operation cost is 3.1349 × 104$, which shows 18% decrease compared to MINLP method and 25% decrease compared to GA-PSCAD method of the total operation cost using the BMO-DE method. The results also justified the usage of CHPs while supplying thermal loads due to increased efficiency and profit.

IEC 61850 Modeling of UPFC and XMPP Communication for Power Management in Microgrids

Integration of distributed renewable energy sources in microgrids presents many challenges to grid such as voltage, stability and power management issues. In literature different control strategies to improve the performance of microgrids integrated with renewable energy sources proposed. FACTS based controller such as Unified Power Flow Controller (UPFC) has also been employed in microgrids to improve the power management and transient stability. Coordinated control strategies between UPFC controller and DERs have been developed. However, the underlying communication for realizing these strategies has not been discussed. This paper presents IEC 61850 and XMPP based communication for coordinating UPFC and DERs in microgrid for its stable operation. IEC 61850 information model for UPFC controller is developed. Furthermore, the XMPP protocol is utilized to provide the scalability for communication network in microgrids with high penetration of DERs. Additionally, XMPP also provides improved security along with the scalability. IEC 61850 message exchanges over XMPP communication between different components of microgrid for power management is demonstrated.

Modeling of Energy Sources in Microgrid Using RSCAD/RTDS

Modeling of Energy Sources in Microgrid Using RSCAD/RTDS

The role of intelligent generation control algorithms in optimizing battery energy storage systems size in microgrids: A case study from Western Australia

Battery energy storage systems can play a substantial role in maintaining low-cost operation in microgrids, and therefore finding their optimal size is a key element of microgrids’ planning and design. This paper explores the optimal sizing options for batteries in microgrids that include wind turbines, solar photovoltaics, synchronous machines and a grid connection supply under various types of retail tariff schemes. The optimal size of batteries is hypothesized to be significantly related to the intelligent control rules applied to dispatch the microgrid sources. This problem can be formulated as a mixed linear integer problem and can be solved using linear/non-linear solvers depending on the complexity of the generation control plan. The main objective of this work is to apply online intelligent adaptation mechanism to tune the economic generation control (dispatch) rules of the microgrid. This tuning objectives are maintaining secure operation, maximizing profitable utilization of batteries and managing their charging life-cycles. While sizing options exploration has been formulated as a linear programming based optimization problem, Fuzzy-Logic is proposed to control the charging/discharging time and quantity for batteries. For the sake of performance comparison, various optimization techniques, i.e., Particle Swarm Optimization, Genetic Algorithm and Flower Pollination Algorithm are applied to perform the economic dispatch calculation. As a case study, a commercial type load connected to the 22 kV distribution network in south Western Australia was used in the testing and validation if the results of the proposed sizing method. The operation condition data was obtained from Western Power the distribution and transmission company in south Western Australia, the Australian Bureau Of Meteorology (BOM) and the Australian Energy Market Operator (AEMO). The results showed that employing intelligent batteries in operation can reduce the annual generation cost of microgrids. However, the decision on selecting the size of batteries depends heavily on the amount of upfront investment cost. The simulation results showed that the intelligence added to batteries’ control could achieve 6.5%, 7.6% and 11.5% of the annual generation cost in the Islanded, Grid-connected with no-export and Grid-connected with export operating modes respectively. Also, intelligent batteries operation control was proven to minimize their payback time to 2.8, 2.7 and 2.7 years in the Islanded, Grid-connected with no-export and Grid-connected with export operating modes respectively.

Distributed Consensus Based Algorithm for Economic Dispatch in a Microgrid

Economic dispatch problem (EDP) is a fundamental optimization problem of power systems. With the penetration of renewable energy sources in microgrids, this paper proposes a distributed algorithm based on consensus theory to solve the EDP with a quadratic cost function. The method takes advantage of the fact that incremental costs need to be equal for all buses at optimal output power values. Thus, the incremental cost of each bus is selected as a consensus variable and the local mismatch between total demand and generation is assigned as a feedback variable to meet demand constraints. Unlike the existing related works, the feedback gains for the feedback variables are different and time-varying. Using multi-parameter perturbation theory and graph theory, the convergence of the algorithm is proved. Furthermore, the upper bounds of the feedback gains are given theoretically, and we obtain that the algorithm converges to the optimal solution at a rate governed by the second largest eigenvalue of the system matrix. Meanwhile, the algorithm is a fully distributed algorithm without a leader or a virtual command node. The simulation results illustrate the effectiveness of the algorithm even though there is a demand change and generator damage. Some simulation results intuitively illustrate how the convergence speed changes with the feedback gains.

A Generalized Framework for a Cost Optimization Scheme in a MicroGrid

Objectives: To develop a generalized formulation to determine the cost optimization scheme for a MicroGrid (MG) source by implementing Artificial Bee Colony algorithm. The generating resource with microgrid is a two-objective problem which consists of pv cell (solar cell) array, Wind Turbine (WT), Micro Turbine (MT), diesel generator and Fuel Cell (FC). Methods: The generating energy sources of the microgrid units are essential to minimize the operating cost of the output power which is generated. Here, the ABC algorithm is modelled into two stages. The optimum configuration of the microgrid at a minimum fuel cost is obtained by the first stage of the ABC algorithm. Findings: By using the minimum cost function, the second stage of the ABC algorithm was attained at the reduced operating and maintenance cost. The main aim is to minimization of fuel cost, fuel consumption cost and the emission such as NOX , SO2 , and CO is reduced in these microgrid sources. Applications: For any required load demand the minimum fuel cost is obtained by using artificial bee colony algorithm. Keywords: Artificial Bee Colony Algorithm, Consumption of Fuel Cost, Emission Cost, MicroGrid (MG), Operating and Maintenance Cost

Improving Microgrid Frequency Regulation Based on the Virtual Inertia Concept while Considering Communication System Delay

Frequency stability is an important issue for the operation of islanded microgrids. Since the upstream grid does not support the islanded microgrids, the power control and frequency regulation encounter serious problems. By increasing the penetration of the renewable energy sources in microgrids, optimizing the parameters of the load frequency controller plays a great role in frequency stability, which is currently being investigated by researchers. The status of loads and generation sources are received by the control center of a microgrid via a communication system and the control center can regulate the output power of renewable energy sources and/or power storage devices. An inherent delay in the communication system or other parts like sensors sampling rates may lead microgrids to have unstable operation states. Reducing the delay in the communication system, as one of the main delay origins, can play an important role in improving fluctuation mitigation, which on the other hand increases the cost of communication system operation. In addition, application of ultra-capacitor banks, as a virtual inertial tool, can be considered as an effective solution to damp frequency oscillations. However, when the ultra-capacitor size is increased, the virtual inertia also increases, which in turn increases the costs. Therefore, it is essential to use a suitable optimization algorithm to determine the optimum parameters. In this paper, the communication system delay and ultra-capacitor size along with the parameters of the secondary controller are obtained by using a Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm as well as by considering the costs. To cover frequency oscillations and the cost of microgrid operation, two fitness functions are defined. The frequency oscillations of the case study are investigated considering the stochastic behavior of the load and the output of the renewable energy sources.

Distributed Control System With Aperiodic Sampled Time-Delayed Data for Batteries and Renewable Energy Sources in Microgrid

This paper proposes an aperiodic sampled and time delayed data based distributed control system for frequency restoration, state of charge balancing and voltage restoration in a microgrid with distributed batteries and PV systems. Lyapunov–Krasovskii functionals and linear matrix inequalities are used to calculate the control system parameters and ensure its stability. The proposed control method is scalable since the stability depends only on the largest and smallest/second smallest eigenvalues of the communication graph Laplacian matrices. Real-time digital simulator is used to verify the proposed control method on an IEEE 13 node test feeder with variable loads.

Placement of phasor measurement unit for complete observability of an isolated microgrid system

The role of the microgrid to meet up the localized power demand is of immense importance considering the growing power demand as well as grid inadequacy in Indian power scenario. Apart from meeting localized power demand with various distributed generating sources microgrid can render support to the adjacent main grid or similar localized grid as when needed. This paper presents the techniques for identifying placement sites for Phasor Measurement Units (PMUs) in a microgrid system based on complete observability of the system. The main objective of optimal placement of PMU problem is to determine a minimal set of PMUs such that the whole system is observable. This study has been done on a 14 bus test model with the help of PSAT.

Efficient Energy Management Control of Renewable Sources in Micro Grid with Power Quality Improvement Using Active Power Filter

In this paper an energy management central control is integrated with a feedback from the source power rather than renewable energy power feedback in conventional schemes. The proposed energy management scheme reacts faster to the load changes as compared to traditional algorithms. The energy management control generates a trip signal for tripping the circuit breakers of renewable sources battery and fuel cell. The other two renewable sources (PVA and wind farm) are always connected to the micro grid. In order to reduce the THD caused by the power electronic devices an active power filter is connected at the Point of common coupling (PCC). Active power filter control structure is introduced with feedback control from PCC voltage and current. Due to the feedback from PCC the active power filter only operates during harmonic generation which don’t happen in passive filters. All the comparisons and modelling are designed in MATLAB Simulink environment with graphical representation with respect to time.

Cascading Collapse of a Large-Scale Mixed Source Microgrid Caused by Fast-Acting Inverter-Based Distributed Energy Resources

Power electronic converter-interfaced distributed energy resources (DERs) are being increasingly deployed for achieving high energy efficiency, power quality, and flexibility of power system operation and controls. They facilitate access to a wide array of energy sources, including renewables, fuel cells, microturbines, variable speed engine-generator sets, etc. However, recent tests carried out at the Consortium for Electric Reliability Technology Solutions (CERTS) Microgrid have indicated that their deployment in the mixed source microgrid can cause a cascading collapse during extreme events. To investigate the problem, simulation models of two types of DERs are developed in PSCAD/EMTDC software and validated with the experimental test results. Furthermore, the validated models are used to study a cascading collapse problem in a large-scale mixed source microgrid on the benchmark IEEE 33-bus test system. In this paper, three alternative techniques are evaluated to prevent the cascading collapse in the large-scale microgrid caused by fast-acting inverter-based DERs.

Robust Stability Region of a Microgrid Under Parametric Uncertainty Using Bialternate Sum Matrix Approach

This paper analyzes the robust stability of a mixed source microgrid comprised of a synchronous generator-based distributed energy resource (DER) and an inverter-based DER. Few studies conducted recently indicated that power system stabilizers (PSSs) are advantageous for damping local oscillations of synchronous generator-based DERs. However, stability issues may arise due to interaction of the parameters of PSS and system. This paper proposes a method to determine the stability region for the system when any two parameters are considered uncertain based on robust control theory. A sufficient condition for robust stability is presented using bialternate sum matrix of the system with uncertain parameters. The bialternate sum matrix approach is compared with a branch and bound approach presented in earlier studies. These two methods are shown to yield identical results for a single machine infinite bus system. However, the proposed bialternate sum matrix approach requires far less computational effort. Therefore, it is applied to determine the stability region for the operation of mixed source microgrid in both grid-connected and islanded modes.

Improved Frequency Regulation in an Islanded Mixed Source Microgrid Through Coordinated Operation of DERs and Smart Loads

The advent of microgrids paved the way for energy decentralization and self-sufficiency among consumers. Reciprocating engine-driven synchronous generators (also known as gensets) are one of the most commonly found distributed energy resources (DERs) installed in a microgrid. A key concern in microgrid operation is the frequency regulation, especially when it is islanded from the main grid. In recent years, the inverter-based DERs have witnessed huge growth. When fast-responding inverter-based DERs are working in parallel with the slow-acting gensets within the islanded mixed source microgrid, many challenges exist in coordinating their operation. In particular, an inverter-based DER is susceptible to collapse due to its large transient loading and this can bring down the entire system. This paper investigates load sharing and proposes new techniques for improved frequency regulation in an islanded mixed source microgrid. An improved coordination scheme between DERs is presented in this paper by accounting for their inertial and governor response characteristics. The unequal transient load sharing between gensets and inverter-based DERs is redistributed to prevent system collapse as well as achieve desired frequency regulation. For dealing with extreme scenarios, a smart load shedding scheme is integrated into the coordinated operation of DERs.

Coordination control of multiple micro sources in islanded microgrid based on differential games theory

To deal with the deviations of frequency of microgrid system composed of multiple micro sources caused by load disturbance, the load frequency control of islanded microgrid system is studied based onlinear quadratic differential games theory in this paper. Considering the operating characteristics of each micro source, different objective function weighting matrix is selected, and the control strategy of non-cooperative feedback Nash equilibrium of each micro source in microgrid system is researched. The simulation results show that the control strategy can accomplish system control targets, make full use of the various of characteristics of each micro source and balance the benefit of them. At the same time, the control strategy has good robustness to external disturbance and parameter variation of the internal unit.

Energy management systems for hybrid distributed generation sources in grid connected and stand-alone micro-grids

This paper proposes energy management systems for micro-grids. In recent years, the use of renewable energy sources in micro-grids has become an effective means of power decentralization especially in remote areas where the extension of the main power grid is an impediment. But a mixture of renewable energy sources and conventional generation poses serious challenges in the operation and control of micro-grids as a result of the uncertainty associated with renewable sources. Therefore, excellent energy management with regards to the power production, control, reliability, and consumption is needed in the power system. The main objective of the energy management system is to minimize the system cost as well as meeting the demand. In order to take into account the uncertainties of distributed generators (DGs) and load consumption, demand response participation and load shedding is taken into account. Two different types of algorithms are used to solve the smart energy management system of the micro-grid. To minimize system costs, which includes unit commitment and demand response, a genetic algorithm is used. To further balance the supply and demand during extreme cases, load shedding is employed through the use of the artificial neural network. The simulation results displayed corroborate the merit of the proposed method.

Load Disturbance Rejection Based PID Controller for Frequency Regulation of a Microgrid

<p>Today’s world is very much concerned to reduce green house gas emission from the conventional thermal power plants as cutting down emissions from transport and heating sector may not be realistic in the near future. To reduce pollution from electrical power sources, the world is now marching towards usage of renewable energy sources (RESs). These sources being small in capacity are mostly connected at the distribution voltage level. This indirectly reduces transmission and distribution losses as the sources are around the load. This distribution system having small scale energy sources is called as a microgrid or active distribution network. Microgrid operates generally in a grid connected mode. However, circumstances such as fault, voltage sag and large frequency oscillations in the main grid may force the active distribution network to be disconnected from the main grid and operate as an isolated microgrid . During this isolation there will be change in power output from the controllable microsources which are to be regulated properly to have a stable operation in regard to power balance and frequency of operation within the isolated microgrid. An autonomous isolated microgrid comprising both controllable & uncontrollable sources. Like solar, wind, diesel generator(DG), aqua electrolyzer(AE), fuel cell(FC), a battery energy storage system(BESS), and fly wheel(FW) are considered. Solar, wind, DG and FC are power generating source & BESS, FW, AE as energy storage element. The generated hydrogen by an AE is used as fuel for a FC. The power system frequency deviates for the sudden change in load demand and the real power generation. The output power of DG, FC, BESS, FW and power absorbed by AE is regulated by using controller such that frequency of the system is controlled. Controller used is proportional plus integral plus derivative (PID). Load Disturbance Rejection(LDR) is used for tuning of controller gains of the proposed hybrid system. This uses the chien-hornes-resnick(CHR) setting with 20% overshoot. Design of p-f droop(frequency regulation parameter) for different controllable source in microgrid using bode plot stability criterion. The system response with Modified LDR based controller, LDR based controller and classical controller are compared. Investigation shows that Modified LDR based controller gives best response amongst these three methods.</p>

Smart Loads Management Using Droop-Based Control in Integrated Microgrid Systems

Demand response (DR) management is a promising strategy in the future power systems as it allows for better resource utilization. Droop control is a widely used method to perform autonomous power management among sources in microgrids (MGs). This paper proposes an approach to adjust loads using droop control to achieve autonomous demand management. This approach has the potential to improve system reliability and ease of management. The proposed droop-based demand response (DB-DR) scheme operates in grid-connected as well as islanded mode of operation. To develop highly effective droop relations, all relevant variables such as MG operating frequency, power flow from the grid, and the load status are included. The proposed DB-DR scheme enables the loads to participate in maintaining supply/demand balance without a need for communication systems. The development of appropriate relations for a DB-DR system is presented and its performance is verified through simulation studies and hardware experiments.

Transition between grid-connected mode and islanded mode in VSI-fed microgrids

This paper investigates the behaviour of a microgrid system during transition between grid-connected mode and islanded mode of operation. During the grid-connected mode the microgrid sources will be controlled to provide constant real and reactive power injection. During the islanded mode the sources will be controlled to provide constant voltage and frequency operation. Special control schemes are needed to ensure proper transition from constant P–Q mode to constant f–V mode and vice versa. Transition from one mode to other will introduce severe transients in the system. Two kinds of transition schemes based on the status of the off-line controller are discussed and a comparative study is presented for various step changes in the load. An additional-pole-placement-based output feedback controller augmentation during transition between the modes is proposed to reduce the transients. A static output feedback compensator design is proposed for the grid connected to island mode transition and a dynamic output feedback compensator design is proposed for resynchronisation. The performance of the output feedback controllers is tested under various operating conditions and found to be satisfactory for the tested conditions.

An effective Load shedding technique for micro-grids using artificial neural network and adaptive neuro-fuzzy inference system

In recent years, the use of renewable energy sources in micro-grids has become an effectivemeans of power decentralization especially in remote areas where the extension of the main power gridis an impediment. Despite the huge deposit of natural resources in Africa, the continent still remains inenergy poverty. Majority of the African countries could not meet the electricity demand of their people.Therefore, the power system is prone to frequent black out as a result of either excess load to the systemor generation failure. The imbalance of power generation and load demand has been a major factor inmaintaining the stability of the power systems and is usually responsible for the under frequency andunder voltage in power systems. Currently, load shedding is the most widely used method to balancebetween load and demand in order to prevent the system from collapsing. But the conventional methodof under frequency or under voltage load shedding faces many challenges and may not perform asexpected. This may lead to over shedding or under shedding, causing system blackout or equipmentdamage. To prevent system cascade or equipment damage, appropriate amount of load must beintentionally and automatically curtailed during instability. In this paper, an effective load sheddingtechnique for micro-grids using artificial neural network and adaptive neuro-fuzzy inference system isproposed. The combined techniques take into account the actual system state and the exact amount ofload needs to be curtailed at a faster rate as compared to the conventional method. Also, this methodis able to carry out optimal load shedding for any input range other than the trained data. Simulationresults obtained from this work, corroborate the merit of this algorithm.