Standalone Microgrid Research Articles

BWOA assisted PIDF-(1+I) controller for intelligent load frequency management of standalone micro-grid

The study made in this paper has been directed towards a novel load frequency management (LFM) scheme for solar-wind-based standalone micro-grid (SMG). For LFM, this brief deals with the introduction of proportional–integral–derivative with filter — (one plus integral), i.e., PIDF-(1+I) cascade controller. A maiden endeavor has been performed to employ a recently developed black widow optimization algorithm (BWOA) to obtain the supplementary controller parameters. The considered SMG consists of the wind turbine generator, diesel engine generator, solar photovoltaic as distributed generation unit, and flywheel and ultra-capacitor are considered as energy storage systems. Generation rate constraints and governor dead-band type power system’s nonlinearities are also included in this study. This work aims to mitigate the effect of mismatch in demand and generation and minimize the change in frequency deviation (CFD). The maximum obtained CFD with the proposed controller is 0.048 Hz, which is entirely satisfactory and under the permissible limit of IEEE standard. A vivid comparative analysis of artificial bee colony and BWOA tuned controllers like conventional PID, PIDF, and PIDF-(1+I) is also performed. Finally, the detailed robustness assessment of the proposed controller with its real-time implementation through the standard New England IEEE 39 test bus system presents the controller’s superiority.

Optimal deep learning based aggregation of TCLs in an inverter fed stand-alone microgrid for voltage unbalance mitigation

The rapid growth of distributed generating (DG) units due to its advancement in modern day power systems has put a major effect in the operation of low inertial stand-alone Microgrids (MG). Moreover, the limited availability of ancillary services pose a severe challenge in power quality issues especially during unbalanced loading condition. To perpetuate its resiliency, this paper presents an inverter fed Space Vector based Droop controlled Positive-Negative sequence compensation along with deep learning-based aggregation of Thermostatic loads for incorporating Demand Side Management (DSM) to mitigate voltage unbalance (VU) adhering to IEC-61000-3-13 and without compromising the thermal comfort of customers. The major portion of Thermostatic Control Loads (TCLs) comprise of air conditioners that occupy a wide sector in residential and commercial areas; hence the aggregation and scheduling of such loads re-establishes dynamic reactive power of DG by alleviating VU during peak hours. The novel one-time registration of loads is also introduced in this paper by incorporating Artificial Neural Network (ANN) for easy access to customer's newly connected loads to participate in DSM. The test system comprises of eight bus system connected with Solar Photovoltaic, Battery unit, Slow responding Diesel Generator (DZ) along with single and three phase loads constituting of TCLs. The performance of the proposed VU mitigation control strategy is evaluated by considering various case studies and the results are validated through simulations performed in MATLAB / Simulink environment.

Predictive Control of PV/Battery System under Load and Environmental Uncertainty

The standalone microgrids with renewable energy resources (RERs) such as a photovoltaic (PV) system and fast changing loads face major challenges in terms of reliability and power management due to a lack of inherent inertial support from RERs and their intermittent nature. Thus, energy storage technologies such as battery energy storage (BES) are typically used to mitigate the power fluctuations and maintain a power balance in the system. This paper presents a model predictive control (MPC) based power management strategy (PMS) for such standalone PV/battery systems. The proposed method is equipped with an autoregressive integrated moving average (ARIMA) prediction method to forecast the load and environmental parameters. The proposed controller has the capabilities of (1) effective power management, (2) minimization of transients during disturbances, and (3) automatic switching of the operation of the PV between the maximum power point tracking (MPPT) mode and power-curtailed mode that prevents the overcharging of the battery and at the same time maximize the PV utilization. The effectiveness of the proposed method has been verified through a comprehensive simulation-based analysis.

Joint coordination of optimal power management and energy storage system sizing for a full-scale marine current turbine considering microgrid integration constraint

The issues of variability and uncertainty of tidal speed result in severe challenges for standalone microgrid (as island grids for examples) operators. Indeed, to maintain the system power balance, existing classical generators which are associated with tidal power units must be able to frequently change their operating point, either up or down, to respond to the fast fluctuations of tidal power and consumption and sometimes exceed their maximal ramp capability. This in turn accelerates aging process and results in serious damage. The switching to a safer and more reliable system seems to be a promising and long-term solution. This paper proposes to associate a supercapacitor-based Energy Storage System (SC-ESS) to a tidal turbine to smooth the fast power production fluctuations. The association of this SC-ESS with the tidal turbine unit aims to meet requirements on the variation of injected tidal power in an islanded microgrid. An original smart power management strategy is proposed for the use of the ESS. Taking into account this strategy, an optimal design methodology based on simulations on the more severe encountered day cases is proposed. This methodology allows to determine a minimal sizing of the ESS to fulfil the grid requirements. The paper also proposes a complete modeling of the whole system behavior. The Energetic Macroscopic Representation (EMR) tool is used to realize the system model where the inversion-based control principle is then used to deduce the control schemes. This global methodology is applied to a test tidal turbine which is based on a real 1 MW prototype setup to the islanded grid of Ushant in France. Using real measured data, it is shown that a relatively small and low cost SCs pack is sufficient to accommodate the high tidal power fluctuations. A comparison is performed between the existing configuration where a resistor bank is used to shave the excessive power variation and the considered case where SCs pack is used. For one tidal cycle, it is shown that a reduction in energy loss of 18.2% is achieved, which presents a non-negligible gain for Ushant's Island microgrid.

Coordinated control between a grid forming inverter and grid following inverters suppling power in a standalone microgrid

Battery energy storage systems, fuel cells, and photovoltaic generators are being adopted in distribution networks to achieve CO2 emission reduction. These power sources require inverters to connect to AC networks. However, sub- networks, such as a microgrids containing inverter power sources, may be disconnected from the utility network and operated in a standalone mode during extended blackouts. This study focuses on a standalone microgrid supplied by inverter power sources without a synchronous generator and proposes a new microgrid inverter control. In this inverter control, a single grid forming inverter is operated as a master power source to determine frequency and voltage, and other inverters, called grid following inverters, are operated as subordinate power sources with active and reactive power control. The necessary functions in the energy management system are examined, and the coordinated operation of all inverters in the microgrid is demonstrated via simulation.

Planning and optimization of microgrid for rural electrification with integration of renewable energy resources

Microgrids are an effective means to provide power to urban and rural communities. Microgrid planning must anticipate both the system's economic feasibility and long-term stability. Due to existing challenging ambitions, limitations, and the uncertainty of renewable energy production, the planning of microgrids is a difficult task. In the present work, a standalone microgrid is planned to integrate solar, wind turbine, diesel generator, and battery for the rural community of the hilly state of Uttarakhand (India). The Feasibility and techno-economic analysis of a proposed microgrid is conducted. The microgrid's performance is investigated using differential evolution and other existing algorithms, particle swarm optimization, and genetic algorithm to ascertain the cheapest option to energize the area. The sizing of components and sensitivity analysis of energy cost with changes in various parameters of the energy system is investigated. The optimization results suggest that the energy cost is $0.16/kWh, with a renewable fraction of 92% and a net present cost of $ 41,078. The obtained results indicated that a renewable-based energy system provides a more effective solution for the electrification of the rural population.

Multiobjective Optimization of a Hybrid PV/Wind/Battery/Diesel Generator System Integrated in Microgrid: A Case Study in Djelfa, Algeria

Hybrid Renewable Energy Sources (HRES) integrated into a microgrid (MG) are a cost-effective and convenient solution to supply energy to off-grid and rural areas in developing countries. This research paper focuses on the optimization of an HRES connected to a stand-alone microgrid system consisting of photovoltaics (PV), wind turbines (WT), batteries (BT), diesel generators (DG), and inverters to meet the energy demand of fifteen residential housing units in the city of Djelfa, Algeria. In this context, the multiobjective salp swarm algorithm (MOSSA), which is among the latest nature-inspired metaheuristic algorithms recently introduced for hybrid microgrid system (HMS) optimization, has been proposed in this paper for solving the optimization of an isolated HRES. The proposed multiobjective optimization problem takes into account the cost of energy (COE) and loss of power supply probability (LPSP) as objective functions. The proposed approach is applied to determine three design variables, which are the nominal power of photovoltaic, the number of wind turbines, and the number of battery autonomy days considering higher reliability and minimum COE. In order to perform the optimum size of HMG, MOSSA is combined with a rule-based energy management strategy (EMS). The role of EMS is the coordination of the energy flow between different system components. The effectiveness of using MOSSA in addressing the optimization issue is investigated by comparing its performance with that of the multiobjective dragonfly algorithm (MODA), multiobjective grasshopper optimization algorithm (MOGOA), and multiobjective ant lion optimizer (MOALO). The MATLAB environment is used to simulate HMS. Simulation results confirm that MOSSA achieves the optimum system size as it contributed 0.255 USD/kW h of COE and LPSP of 27.079% compared to MODA, MOGOA, and MOALO. In addition, the optimization results obtained using the proposed method provided a set of design solutions for the HMS, which will help designers select the optimal solution for the HMS.

Effective dispatch strategies assortment according to the effect of the operation for an islanded hybrid microgrid

The optimized design of a freestanding hybrid microgrid for various distinct dispatch controls is assessed in this paper, which considers the optimal sizes of individual components, system response, and reliability analysis. The effective design and management of stand-alone islanded hybrid smartgrids are getting increasingly importance and influences as the prevalence of renewable energy in microgrids grows. Melville Island, off the coast of eastern Queensland, Australia, is taken as the test microgrid in this study. For the optimal sizing and techno-economic assessment of the intended hybrid microgrid system consist of of solar diesel generator, PV , battery storage, and wind turbine, four dispatch approaches have been unitized: load following, generator order, combined dispatch, and cycle charging strategy. The proposed off-grid microgrid's CO2 emissions, total net present cost (NPC), and the Levelized cost of energy (LCOE) have all been optimized. In HOMER software, all the possible dispatch algorithms were analyzed, and the power system responses and reliability study were carried out using DIgSILENT PowerFactory. The findings of the study are useful for determining the optimum hybrid combination and available resources for the best performance of an off-grid microgrid employing various dispatch mechanisms. Following the simulation data, load-following is the best dispatch mechanism for stand-alone microgrid architecture since it has the lowest LCOE and NPC.

Fault Classification with Convolutional Neural Networks for Microgrid Systems

The microgrid (MG) networks require adaptive and rapid fault classification mechanisms due to their insufficient kinetic energy reserve and dynamic response of power electronic converters of distributed generation (DG) systems. To achieve this requirement, this study explores the issues in standalone (SA) and grid-connected (GC) operating modes of MG and develops a near-real-time intelligent disturbance detection and protective solutions for their stable operation. In the proposed approach, an intelligent fault classification mechanism is developed using the advantages of wavelet transform and convolutional neural networks (CNNs). Initially, the voltage and current outcomes for each and every possible fault in the MG network are identified and the wavelet transforms are applied for preprocessing and image conversion. The converted images are identified as scalograms which are further trained with the CNNs. To assess the development of the proposed approach, the IEEE 13 bus system is considered for data gathering. To replicate the real-time behavior of the MG network, the additive white Gaussian noise (AWGN) and additive impulsive Gaussian noise (AIGN) are injected at various levels during the classifier development process. The trained classifier has an average training accuracy of 99.1% for SA MG and 97.7% for GC MG, and the average testing accuracies are 98.9% for SA MG and 97.1% for GC MG.

Frequency Stabilization of Stand-Alone Microgrid with Tuned PID Controller

Frequency deviation is a major concern in a power network due to the frequent load changes. The stand-alone hybrid microgrid is developed with wind/solar systems with MPPT techniques, and this system also faces frequency instability due to the source and load variations. PID controllers are used to mitigate the frequency deviation in the proposed stand-alone hybrid microgrid. The PID controller parameters are optimized using the Ziegler-Nichols method. The system is developed in MATLAB Simulink, and the proposed Ziegler-Nichols tuned PID controllers maintain the system frequency within the IEEE standards under both source and load variations.

Analysis of LoRa Transmission Delay on Dynamic Performance of Standalone DC Microgrids

One important aspect toward proper and stable functioning of a communication-based controlled microgrid is data transmission. Consequently, an analysis of the effect of data transmission delay is of significance for any chosen communication protocol. This paper focuses on the effect of employing LoRa for data transfer at the secondary control level of a standalone DC microgrid. It analyses the effect of LoRa transmission delay on the dynamic performance of DC microgrids. This paper simulates a community DC microgrid that operates in three modes: PV mode, battery mode and generator mode. This microgrid operates as a centralized communication-based controlled microgrid, with the secondary control level operating as an event-driven level. The system incorporates a hierarchical system where data is transferred between the various distributed energy resources (DERs) local controllers and the microgrid central controller (MGCC). Simulations for three scenarios are presented. In the first scenario, the microgrid is designed and simulated without a communication delay to observe the system behavior. Then LoRa transmission delay is calculated for the various signals transferred between the MGCC and the local controllers. This delay is introduced into the simulation as transport delays and the system exhibits a level of stability degradation. Subsequently, a time delay compensation system is incorporated into the system for more robust operation. The delay compensation is applied in two simulation scenarios. In the first scenario, the system inductor (L) and capacitor (C) components are re-calculated, and the system is re-simulated to get a stable system even with the applied communication delay. In the second scenario, the proportional integrator (PI) controller in the microgrid central controller is re-designed to a more robust form to compensate for the delay caused by the LoRa transmission. The results obtained from the two modified simulations realize a stable DC microgrid. This system modification allows for system stability again, similar to the simulation when the microgrid operated without any communication delay. This, therefore, demonstrates that with proper system design and implementation, low bandwidth communication systems such as LoRa can be effectively employed for data transfer in event-driven communication-based controlled DC microgrids.

Coordinated Distributed Voltage Control Methods for Standalone Microgrids

A microgrid is a small-scale power grid comprising distributed generators (DGs), distributed storage systems, and loads. It will lose contribution from the main grid if it shifts to islanded mode due to pre-planned or unforeseen disturbances. To restore the terminal voltages of all the distributed generators to the reference value, this paper presents three coordinated secondary control strategies. First, motivated by the synchronization control theory of multiagent systems, a distributed control technique is developed where each of the DGs is considered an agent and they exchange information via a communication network. second, a two-level control technique is designed in which a global controller is employed to monitor the overall performance of the DGs by transmitting corrective signals to the local controllers of the agents. In this technique, all the communication is between the global controller and the local controllers without any direct communication between the agents. Third, decentralized control is provided in which each DG is separately controlled by its local controller that operates based on the local feedback measurements. Simulations are carried out on an islanded microgrid consisting of four DGs to illustrate our design approach.

Sustainable electrification planning of rural microgrid using renewable resources and its environmental impact assessment.

The global population continually increases, and providing power and ensuring sustainable development is becoming increasingly challenging. As a result of increased industrialization and mobility, population growth produces changes in land usage and greenhouse gas emissions. Air quality is influenced by the amount of energy used. The release of carbon dioxide and other pollutants into the atmosphere harms the ecosystem. Although renewable energy sources can help reduce carbon emissions, their unreliability means that energy output is unpredictable, necessitating the development of battery storage to bridge the demand-supply gap. Much attention has been paid to combining renewable energy sources with batteries into rural electrification. The designing and operation of a rural standalone microgrid with electrical loads modeled for the electrification energy deficient village of Uttarakhand (India). The proposed work optimized the component size, cost of energy, net present cost, and pollutant emission reduction in the environment. The optimization is carried out using the gray wolf optimization algorithm. Four different microgrid systems are investigated for the feasibility evaluation of cost-effective rural power. A comparative evaluation of models is provided based on environmental and economic factors. The optimum design has an energy cost of 0.313 $/kWh and a net present cost of $ 65,241.32. The second arrangement, which has the most significant level of renewable energy penetration (90%), has provided a reliable power supply to the region. On the other hand, the proposed design satisfied all constraints while retaining a competitive energy cost.

Adaptive Voltage and Current Control to Improve Stability and Restoration of Operation after the Occurrence of a Transient Fault in The Inverter-based Standalone Microgrid

Small signal stability analysis and control strategies are well provided for conventional power systems. Still, in inverter-based microgrids, it is necessary to determine the model features and control specific oscillation modes. In this paper, inverter-based standalone microgrid performance modelling, including voltage and current control, has been developed. This model has inverter control loop details but does not provide switching performance. A simple adaptive controller controls the microgrid voltage and current, with only three parameters, including two negatively stable feedbacks and positive unstable feedback. Advantages of this controller over a Proportional Integral Derivative (PID) controller include proper adaptation to system changes, flexibility in setting up, and a robust deal with sudden changes in the system. Finally, by making drastic changes in the operation of a sample microgrid, such as loading and short circuit faults, we prove the effectiveness of the proposed adaptive control scheme in improving the stability and restoration of operation after the occurrence of a transient fault in the microgrid.

Energy management system for a small-scale microgrid

In recent years, the power system has been evolved into microgrids, which are little pockets of self-contained entities. Different distributed, interconnected generation units, loads, and energy storage units make up a typical microgrid system. The increased energy efficiency of these units on microgrids is gaining popularity day by day. Because of their stochastic behavior, renewable generation causes an imbalance in the power system, which needs microgrid energy management. To solve these issues, a variety of novel approaches have been explored in the literature. For the stand-alone microgrid in this research, efficient energy management and control mechanism is adopted. A photovoltaic system, a wind turbine, and a battery energy storage device make up this stand-alone microgrid. The power stability of the hybrid system is ensured by a sophisticated controller. The main purpose of this study is to regulate the DC/DC bidirectional converter (DBC), which connects the Li-ion battery to the DC bus of the stand-alone microgrid. This paper describes the development of a wind/photovoltaic power generation system to the load, as well as MPPT techniques like perturb and observe (P&O). The system is simulated and the results are presented using MPPT techniques. There is no requirement for a specific power model in the suggested method. Only power and voltage system data are used by DBC. A stand-alone microgrid system was simulated using MATLAB.

Optimal planning of renewable integrated rural microgrid for sustainable energy supply

AbstractRenewable resources can help reduce carbon emissions, but their inconsistency causes inconsistent energy generation, mandating the introduction of a battery bank to overcome the demand‐supply gap. The integration of renewables for electrical supply systems in rural regions has received much attention, as has the hybrid energy system with storage for microgrids. This work presents an optimization technique for the design and operation of a standalone microgrid with load demand. The research framework is demonstrated by a case study in a remote rural location in Uttarakhand (India). This research proposes an integrated techno‐economic optimization and power management of a standalone integrated renewable energy system to meet the electrical energy demand. The levelized cost of energy (LCOE), the net present cost (NPC), and pollution emission are minimized using grey wolf optimization. Four alternative models are compared based on environmental considerations and economic research. According to the simulation findings, the optimal configuration has a 0.203 $/kWh LCOE and a 92% renewable portion. In addition, the optimization results have been presented and compared. Finally, a sensitivity analysis is performed to determine the impact of various factors on the system in question.

Power quality enhancement of grid-islanded parallel microsources using new optimized cascaded level control scheme

The integration of standalone microgrids led to unconventional electrical system with new challenges raised. The new technical challenges regard power losses, stability, and power quality (PQ). This research work addressed the PQ improvement in the parallel multi-inverter operation of islanded microgrid (MG). Improvements of PQ covers voltage/frequency regulation, total harmonic distortion suppression and circulating current mitigation. In this paper, a standalone MG based on a triple action controller has been proposed. It has improved the PQ of a microsource in various load conditions. Furthermore, parallel inverters based on the proposed standalone MG control scheme were proposed. The results represented a satisfactory PQ enhancement for optimizing decentralized controllers. Moreover, the overall system has been tested by two scenarios, sudden load variations and flicker injection to observe their impacts on the system’s PQ. The stability of the system has been investigated and ensured. The overall results proved that the proposed controllers ensured PQ improvement allowing active and reactive power to be shared. Implementation of the proposed technique has the potential to save installation of FACTS devices that used to be installed to enhance MG PQ. The proposed scheme could be embedded into modern inverter modules for economical MG operation.

Optimizing the penetration of standalone microgrid, incorporating demand side management as a guiding principle

In this work, we demonstrate the importance of implementing techniques that allow us to include demand side management as a tool for the planning of energy systems, in this particular case, standalone power systems. Penetration indexes are also proposed and calculated to establish the minimum requirements for the energy supply of a predominantly residential system powered by renewable resources. The indexes were optimized using meta-heuristic optimization techniques based on a genetic algorithm and particle swarm optimization. Periods of one, five and 10 years were analyzed in order to understand the importance of the penetration of these technologies. Through the use of numerical tools, the relationship between generation and demand is optimized for different cases, with the aim of reducing the energy that is not supplied to the system at minimum cost. This document analyzes a series of penetration indexes that were obtained by optimizing an energy system. The mentioned indexes allow to visualize the behavior of the technologies susceptible of being implemented in the western region of Mexico. The purpose of the work is focused on understanding the potential of demand management as a structural element and foundation of energy networks that use renewable energy.

Thermal analysis and optimization of stand-alone microgrids with metal hydride based hydrogen storage

Stand-alone microgrids, also known as remote area power supply systems, are crucial towards providing electricity access to off-the-grid locations/buildings and for communities trying to become 100% dependent on renewables. Design and development of efficient energy storage system remains a key challenge for the stand-alone microgrid technology. Metal hydride based hydrogen-energy storage system, offering long term energy storage at near ambient conditions and additional benefits of thermal and green hydrogen output, have attracted researchers and industrialists worldwide. In this work, LaNi5 (Lanthanum Penta-nickel) based hydrogen-energy storage system for stand-alone microgrid application is studied. An optimization study is performed to find the optimal sizes of hybrid (solar + wind) and wind microgrid components for the requirements of typical Indian village/UK community of 50 households located at various geographical locations, having diverse solar and wind resources availability. The study ensures that the microgrid satisfies the required electric load but is not over-designed, which is achieved by limiting the two performance parameters i.e., unmet load fraction and excess electricity fraction, below 10%. The optimization study is done based on an hourly analysis for a year using the simulation software HOMER. A thermal analysis is carried out to quantify the additional benefit of thermal output from the energy storage system. Comparisons between the performance and thermal output of optimized hybrid and wind microgrids are carried out for the selected locations. Also, green hydrogen produced for energy storage and available for use at the end of the year is quantified. Upon comparing hybrid (solar PV + wind turbine) and wind energy based microgrids, it is observed that hydrogen storage requirement decreases by up to 97% while using hybrid energy source depending on the location. Besides serving electrical load, the microgrid delivers thermal outputs of about 1kWh and 5kWh for Indian and UK locations respectively.

Study of power management of standalone DC microgrids with battery supercapacitor hybrid energy storage system

<p>In the last years, renewable energy (RE) is increasing widely in the energy sector, and microgrid technology is overgrowing. In this paper, stand-alone microgrid using solar photovoltaic (PV) energy as a source of renewable energy is simulated to provide power for direct current (DC) loads with hybrid energy storage system (HESS) which consists of battery and supercapacitor bank. The proposed microgrid system is tested under various cases of load and variable irradiance to confirm and validate the proposed management strategy to remain the DC bus voltage within a stable limit. The performance of DC microgrid is comparing with and without supercapacitor (SC) bank and notes a desirable decrease in the magnitude of transient voltage when using HESS. The sun power SPR-E19-320 standard was simulated to analyze system performance taking into account the constant load demand. Note that HESS helps reduce transient of DC voltage very effectively in all situations. Very large transients arise due to sudden changes in load demand is also compensated by HESS. The results obtained indicate that the stand-alone DC microgrid with HESS is very beneficial for reducing transient of DC-link voltage that occurs due to sudden change in load or fault. The proposed system is performed by MATLAB/Simulink environment.</p>