Isolated Microgrid Research Articles

Secondary Control Strategy without Communications for Unbalanced Isolated Microgrids

In the context of the energy transition, electrical microgrids have become a key energy solution for isolated zones. For this type of application, low-voltage networks with unbalanced loads are commonly connected. Despite this, many of the hierarchical control strategies presented in the literature have been designed to operate properly only in the presence of balanced loads. For this reason, it is relevant to study how control strategies can be adapted to this scenario, especially those that reduce the dependence on communications to enhance flexibility and reliability. In this sense, this paper presents a secondary layer control strategy that does not require the use of communications to operate in isolated microgrids with unbalanced loads. The strategy guarantees proper performance in terms of power-sharing between the distributed generators of the microgrid. Simulations on Matlab/Simulink are presented to validate the response of proposal.

A novel multi-objective tuning formula for load frequency controllers in an isolated low-inertia microgrid incorporating PV/wind/FC/BESS

Load frequency control (LFC) is vital for isolated microgrids (IMGs), especially when uncertain renewable energy sources (RESs) are present. Enhancing LFC schemes relies mainly on three tracks. Adding new resources to IMG structures is the first track, designing novel controller structures for LFC schemes is the second, and the third is improving controller tuning procedures in the LFC schemes. This research suggests an innovative multi-objective formula (MOF) for controller tuning that combines a novel error criterion termed the integral-square time absolute error of frequency change with the integral-square of IMG controllers' signals. Tested IMG includes multi-sources of diesel engine generators, fuel cells, battery energy storage technologies, and RESs (like photovoltaic and wind turbines). The proposed MOF tuning is evaluated compared to four different objective functions, which are the integral-absolute error (IAE), integral-time absolute error (ITAE), integral-square error (ISE), and integral-time square error (ITSE). The proportional-integral-derivative (PID), fractional-order, and cascade PID controllers are implemented to appraise the proposed MOF extensively against all these single objectives. Statistical analyses are accomplished comprehensively to verify the effectiveness of the artificial rabbits' optimization algorithm (ARO) in competition with other recent optimization algorithms to tune different controllers utilized in the LFC schemes of the examined IMG based on tested objectives. Therefore, ARO is applied to optimize controller settings by combining system nonlinearities with IMG sources' maximal generation rate constraints. The comparative analysis considers settling times, overshoots, IAE, ITAE, ISE, and ITSE performance indices. MATLAB/Simulink simulations confirmed the ability of the suggested MOF tuning to stabilize the system and keep improving performance indices, significantly attaining the minimum settling time even for massive three-type load fluctuations. The first type is step disturbances ranging between 0.1 and 0.25 p.u, the second is varying step disturbances every 5 s, and the third is severe dynamic random load shifts from −0.2 to 0.2 p.u. In addition, the MOF outperforms other competitors' tuning formulas while adding fluctuations of RESs with load disturbances. Furthermore, the robustness analysis is conducted for the applied controllers based on the proposed MOF tuning approach by changing the IMG nominal parameters with ±25 % and adding system nonlinearities. The analysis ensured its efficacy in preserving system stability. Finally, the stability test in the frequency domain using the MATLAB/control design tool verified system stability when different LFC controllers were tuned based on the proposed MOF tuning.

Hierarchical Stochastic Frequency Constrained Micro-Market Model for Isolated Microgrids

With the developments of isolated microgrids (IMGs) and prosumers in remote areas, energy trading has emerged as a critical aspect of IMGs. However, the lack of an upstream network and the low inertia of the system may threaten the secure operation of these networks. This paper proposes a Micro-Market (lM) model for IMGs that includes a precise hierarchical control structure. To address the IMGs low inertia and high intermittency of renewable energy sources (RES), the proposed lM manages the active-reactive power and schedules primary and secondary active reserves to maintain the frequency within in a predefined range. Additionally, a bidirectional linearized AC power flow is established to schedule the reactive reserve and the proposed model is formulated as a two-stage stochastic mixed-integer linear problem (MILP) to maximize social welfare (SW) over the next 24 hours. To validate the effectiveness of the proposed model, the lM is tested on an IMG based on a CIGRE medium-voltage benchmark system, and different operational cases are simulated. The results demonstrate that the proposed model, which takes into account hierarchical control levels and technical issues of the IMG, is a cost-effective way to maximize social welfare while ensuring the secure operation of the IMG.

Cooperative Hierarchical Control of Isolated Microgrids Considering Energy Storage System Aggregation

The integration of numerous energy storage systems (ESSs) improves the reliable and economic operation of microgrids but also enlarges the burden of control and communication systems. This paper proposes a cooperative hierarchical control for isolated microgrids with ESSs, which fully frees from the centralized paradigm and is therefore superior in flexibility and scalability. Firstly, the ESS cooperative control based on the distributed frequency controller is introduced for the state of charge (SoC) balance and the frequency regulation. Then, the ESS aggregation is considered. The aggregated ESS model is established and the real-time model parameters are derived by proposed distributed state observers. Finally, energy management is employed to allocate the output power between generators and the aggregated ESS. A detailed theoretical analysis of the dynamic and steady-state performance of proposed controllers and observers is provided. Simulations on the IEEE 33-bus and the 69-bus system verify the effectiveness of proposed methods.

A novel cascade-loop controller for load frequency control of isolated microgrid via dandelion optimizer

In fast-growing isolated microgrids (IMGs), load frequency control (LFC) ensures optimal power quality for end users. Stochastic grids, notably with renewable energy resources (RESs), require robust and intelligently designed LFC schemes. Thus, this research presents a novel cascade-loop controller combining a fractional order-proportional derivative with a filter and a fractional order-proportional tilt integral derivative (FPDN-FPTID) to improve LFC for single and multi-area IMGs. Recent dandelion optimization adjusts FPDN-FPTID controller settings. Anti-windup keeps the controller out of the non-linear zone for low inertia IMGs. It concerns various sources' maximum generating rates. The two-area IMG model shows its potential and scalability. Extensive MATLAB/Simulink simulations show that the FPDN-FPTID controller outperforms numerous published controllers, either single or cascade-loop, in minimum error criteria, undershoots/ overshoots/settling times, frequency, and tie-line power deviation following load and RES variations. Finally, the sensitivity study indicates the suggested controller stabilizes the system despite ±25 % parameter changes.

Adaptive Control Approach-Based Isolated Microgrid System with Alleviating Power Quality Problems

In this article, a dual third-order generalized integrator-based phase-locked loop (DTOGI-PLL) and an additional degree of freedom-based frequency locked loop (ADF-FLL) control approaches are utilized on a voltage source converter (VSC) to control an isolated microgrid system under different operating conditions. The proposed adaptive approaches provide a fast dynamic response with a precise estimation of frequency, phase angle, and fundamental load current component compared to that of the TOGI-PLL and least mean square (LMS) algorithms. An ADF-FLL allows closed-loop poles to perform more optimally, resulting in faster dynamic performance without compromising filtering capability. Moreover, the proposed adaptive approaches with VSC provide power support, load leveling, harmonic eliminations, and enhance the isolated microgrid’s overall power quality during dynamics in load and energy sources. A solar PV (SPV) array with perturb & observe (P&O) MPPT control is interfaced at the DC link of a bidirectional controller (BDC) to draw maximum solar power. Through dc-link voltage control, the BDC with energy storage system (ESS) ensures the appropriate power flow and power equilibrium between energy sources and load. The Simulation and test results show the dynamic performance of the isolated microgrid is examined under different operational scenarios.

Modified Droop Control for Microgrid Power-Sharing Stability Improvement

Isolated microgrid (IMG) power systems face the significant challenge of achieving fast power sharing and stable performance. This paper presents an innovative solution to this challenge through the introduction of a new droop control technique. The conventional droop controller technique used in inverter-based IMG systems is unable to provide satisfactory performance easily, as selecting a high droop controller gain to achieve fast power sharing can reduce the system’s stability. This paper addresses this dilemma by proposing a modified droop control for inverter-based IMGs that effectively dampens low-frequency oscillations, even at higher droop gain values that would typically lead to instability. The design is described step-by-step, and the proposed controller’s effectiveness is validated through time domain simulation analysis. The results demonstrate the significant improvement in stability and fast power sharing achieved with the proposed controller. This innovative technique presents a promising solution for achieving fast power sharing and stable performance in IMG power systems.

Energy and Economic Analysis of Renewable Energy-Based Isolated Microgrids with AGM and Lithium Battery Energy Storage: Case Study Bigene, Guinea-Bissau

By the year 2020, 90% of the population with access to electricity worldwide was surpassed. However, the reality is very different for many countries, especially for those on the African continent that had more than 572 million people without electricity service at the end of 2019. This work studies the implementation of an isolated microgrid activated with photovoltaic energy and energy storage in batteries under the case study of the community of Bigene, located in the African country of Guinea-Bissau. This type of project is a potential solution to the problem of access to energy, but as the cost of the energy storage system is typically very high, this work technically and economically addresses the effect of using absorbed glass material (AGM) and lithium batteries. A simulator was developed using TRNSYS software to analyze the operation of the microgrid under a defined annual demand profile for different types of users, and economic analysis was conducted considering a project lifetime of 25 years. The results showed no significant differences in the solar fraction of both types of batteries when the photovoltaic power was less than 600 kW, regardless of the capacity of the storage bank. The analysis of auxiliary power requirements showed that lithium technology leads to a lower consumption from 800 kW of PV capacity, and utilizing less than this capacity did not have a significant difference with AGM batteries. In this microgrid with a photovoltaic capacity of less than 700 kW and an energy storage of less than 2580 kWh, the type of storage technology, AGM or lithium, did not represent a considerable difference in the levelized cost of energy, indicating that AGM technology could be selected considering its low initial investment cost compared to lithium batteries.

An adaptive frequency regulation strategy with high renewable energy participating level for isolated microgrid

To improve the renewable energy sources (RES) utilization of isolated microgrids (IMG) in frequency regulation process, an adaptive frequency regulation strategy with high renewable energy participating level is proposed in this paper: 1) an adaptive droop control method is conceived for primary frequency regulation, in which the designed droop coefficients are adjustable with the real-time wind velocity and state of charge (SoC) of energy storage units (ESUs); as the most important contribution, 2) a general flexible model predictive control (FMPC) framework with adaptive cost function and constraints is developed for secondary frequency regulation. For 2), i) the weight coefficients of the cost function can be adaptively adjusted according to frequency deviation through a pre-designed intelligent function, in which the specification of determining the key parameters is involved; ii) the designed constraints' boundaries can dynamically shift with wind velocity and ESU's SoC; iii) the negative impact of model's uncertainties can also be mitigated by implementing the proposed FMPC. Finally, the effectiveness of the proposal is verified by the comprehensive simulation and experimental study, and the results show that the proposal can significantly improve RES's utilization level while guaranteeing frequency regulation performance and operation safety in IMG.

Distributed Adaptive-MPC Type Optimal PMS for PV-Battery Based Isolated Microgrid

In the absence of an external grid, supplying quality power to critical loads in renewables, i.e., solar photovoltaics (PV)-battery-based self-sustained isolated microgrid (MG) system is quite troublesome. Because of involved generation arbitrage and variable load conditions, a robust power management scheme is essential. In this article, a distributed strategy with an adaptive model predictive control (MPC) principle is proposed. It considers all possible uncertainties, viz., intermittent generation as time-varying solar irradiance, variable load profile, alongside maintaining smooth charging/discharging cycle of storage units and shedding of noncritical loads. For this purpose, a novel comprehensive small-signal state-space model of MG with PV-battery systems having dedicated parallel <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RLC</i> loads and a low-voltage network is considered, which accounts for inverter dc-bus link dynamics. The controller tracks the maximum power point of PV and keeps the MG power balance intact for both active and reactive powers by considering interconnected bus dynamics. The viability of the proposed scheme is verified by performing extensive testing, viz., variable solar irradiance profile, continuous small and large variations of loads, shedding of the noncritical loads, multiple topology subsystems, comparative study with state-of-art MPC, and smooth transition of battery charging/discharging cycles using MATLAB platform over 24 and 48 h duration.

Enhancing the Conventional Controllers for Load Frequency Control of Isolated Microgrids Using Proposed Multi-Objective Formulation via Artificial Rabbits Optimization Algorithm

Isolated microgrids (IMGs) power remote areas. However, IMG may lower the frequency stability and increase frequency excursions with low system inertia. Load frequency management ensures system stability. Thus, the paper proposes a novel multi-objective tuning strategy to improve IMG’s load frequency control (LFC) and take the microgrid controller’s control signals into account. Diesel engine generator, fuel cell, battery energy storage system, and renewable energy sources (RESs) like photovoltaic and wind systems make up the IMG. Conventional controllers such as proportional-integral (PI) and proportional integral derivative (PID) are classically tuned based on the standard error criteria as a traditional single-objective tuning approach. Due to the low inertia of the system and the stochastic nature of RES, they cannot act as required under different operating scenarios. Therefore, the PI and PID controllers are tuned using the proposed multi-objective-based tuning approach to reduce the frequency deviations. In addition, anti-windup is applied to the enhanced classic controllers to keep them distant from the nonlinear zone and beyond the source’s physical constraints. The proposed tuning process also considers the maximum practical generation rates for different sources. The recent Artificial Rabbits Optimization (ARO) algorithm is applied to simultaneously adjust the controller parameters for several controlled sources in IMG. Extensive simulations in MATLAB and Simulink confirm the effectiveness of the proposed approach to keep the system stable even when facing high levels of disturbances. In addition, accomplishing sensitivity analysis, severe ±25% changes to the system’s parameters guarantee that the proposed tuning strategy keeps the system stable.

A Novel Stochastic Mixed-Integer-Linear-Logical Programming Model for Optimal Coordination of Hybrid Storage Systems in Isolated Microgrids Considering Demand Response

Storage systems and demand-response programs will play a vital role in future energy systems. Batteries, hydrogen or pumped hydro storage systems can be combined to form hybrid storage facilities to not only manage the intermittent behavior of renewable sources, but also to store surplus renewable energy in a practice known as ‘green’ storage. On the other hand, demand-response programs are devoted to encouraging a more active participation of consumers by pursuing a more efficient operation of the system. In this context, proper scheduling tools able to coordinate different storage systems and demand-response programs are essential. This paper presents a stochastic mixed-integer-lineal-logical framework for optimal scheduling of isolated microgrids. In contrast to other works, the present model includes a logical-based formulation to explicitly coordinate batteries and pumped hydro storage units. A case study on a benchmark isolated microgrid serves to validate the developed optimization model and analyze the effect of applying demand-response premises in microgrid operation. The results demonstrate the usefulness of the developed method, and it is found that operation cost and fuel consumption can be reduced by ~38% and ~82% by applying demand-response initiatives.

An algorithm for power flow analysis in isolated hybrid energy microgrid considering DG droop model and virtual impedance control loop

Power flow analysis (PF) is an essential tool for secure and efficient operation in power systems. For isolated microgrid (IMG) with only local distributed generators (DGs), there is no slack bus that enables the microgrid to have a constant frequency. So, the bus admittance matrix (Ybus) is not fixed. Also, IMG usually has droop-controlled DGs (DCDG) whose voltage and power are frequency-dependent. These factors make PF a challenging task for IMG that cannot be accomplished through the classic PF techniques. This paper proposes a substantial modification to the well-established Newton–Raphson PF algorithm, called (ENR), to fit the IMG. A new formulation of the Jacobian matrix is developed to accommodate the different control characteristics of DGs as well as the frequency variation. Droop control, maximum power point tracking, and constant power control are considered as DG control types with complete models. Moreover, the virtual impedance concept and its control loop are integrated into the DCDG control scheme to guarantee the stable operation regardless the microgrid X/R ratio. Further, the ENR convergence speed is improved by introducing acceleration factors for voltage angle, magnitude, and frequency. The optimal acceleration factors are determined using a modified PSO method. The ENR is applied to a 45-bus IMG with 12 renewable and dispatchable DGs based on a modified version of the IEEE 33-bus test system. Results are compared to time-domain simulations and also to recent literature. The accuracy and high speed of the ENR are verified.

Intelligent electric vehicles charging coupled demand response of isolated microgrid

AbstractIn recent times, the shrinkage of fossil fuel reserves and increase in greenhouse emissions have compelled to switch to suitable eco‐friendly solutions. Electric vehicles (EVs), being one such solution, have been the center of attraction for the industries as well as the researchers. This paper deals with the inclusion of plug‐in EVs (PEVs) in isolated microgrid (I‐MG). An intelligent demand‐side management approach has been proposed for co‐ordination of the power generation from distributed generators, battery energy storage systems (BESSs), and other forms of distributed energy resources (DERs) to fulfill the daily load demand as well as energy demand of EVs. Medium voltage I‐MG integrated with DERs, BESSs and PEVs has been used for the study and the analysis has been done to justify the need for smart charging of PEVs in an I‐MG. The proposed technique combines smart charging and demand response which simplifies the consumer’s concerns and provides a cost‐effective solution.

A Comparative Analysis of Peak Load Shaving Strategies for Isolated Microgrid Using Actual Data

Peak load reduction is one of the most essential obligations and cost-effective tasks for electrical energy consumers. An isolated microgrid (IMG) system is an independent limited capacity power system where the peak shaving application can perform a vital role in the economic operation. This paper presents a comparative analysis of a categorical variable decision tree algorithm (CVDTA) with the most common peak shaving technique, namely, the general capacity addition technique, to evaluate the peak shaving performance for an IMG system. The CVDTA algorithm deals with the hybrid photovoltaic (PV)—battery energy storage system (BESS) to provide the peak shaving service where the capacity addition technique uses a peaking generator to minimize the peak demand. An actual IMG system model is developed in MATLAB/Simulink software to analyze the peak shaving performance. The model consists of four major components such as, PV, BESS, variable load, and gas turbine generator (GTG) dispatch models for the proposed algorithm, where the BESS and PV models are not applicable for the capacity addition technique. Actual variable load data and PV generation data are considered to conduct the simulation case studies which are collected from a real IMG system. The simulation result exhibits the effectiveness of the CVDTA algorithm which can minimize the peak demand better than the capacity addition technique. By ensuring the peak shaving operation and handling the economic generation dispatch, the CVDTA algorithm can ensure more energy savings, fewer system losses, less operation and maintenance (O&amp;M) cost, etc., where the general capacity addition technique is limited.

Isolation Microgrid Design for Remote Areas with the Integration of Renewable Energy: A Case Study of Con Dao Island in Vietnam

In remote areas, extending a power line to the primary electricity grid can be very expensive and power losses are high, making connections to the grid almost impossible. A well-designed microgrid that integrates renewable energy resources can help remote areas reduce investment costs and power losses while providing a reliable power source. Therefore, investigating the design of an independent and economically practical microgrid system for these areas is necessary and plays an important role. This paper introduces a design procedure to design an isolated microgrid using HOMER software (HOMERPro 3.14.5) for remote areas. In Vietnam, due to the obstruction of the mountainous terrain or the isolated island location, many remote areas or islands need electrification. A simple case study of a hybrid system with a 60 kW peak load demand on Con Dao island in Vietnam is used to illustrate the proposed design method. Specifically, a hybrid system that includes a PV system, batteries, and a diesel generator is designed. To provide the full information of the designed hybrid system designed, each solution is analyzed and evaluated in detail according to the sensitivity parameters.

A novel peak load shaving algorithm for isolated microgrid using hybrid PV-BESS system

A novel peak load shaving algorithm has been proposed in this study for peak shaving application in hybrid PV-BESS connected Isolated Microgrid (IMG) system. This algorithm will help an IMG system to operate its generation systems optimally and economically along with PV generation unit. An IMG model has been developed in MATLAB/Simulink environment with actual load data, conventional Gas Turbine Generator (GTG), Photovoltaic (PV) generation system and Battery Energy Storage System (BESS). The proposed algorithm has been tested with the designed IMG model. To evaluate the effectiveness of the algorithm, simulation case studies have been conducted with actual load data and actual PV generation data. The simulation results demonstrate that the algorithm can minimize the limitations of the existing methods and it can use the PV generation system effectively. Peak shaving service can be found from this algorithm as a simple and forcible way. A comparative analysis has been conducted of the proposed algorithm with the conventional methods. The comparison results can easily reflect that the proposed algorithm can ensure the optimal use of PV generation system and can serve peak shaving service effectively. It can also ensure an economic and environment friendly system where the existing algorithms are limited to serve these. The proposed algorithm can mitigate the available power issues for hybrid PV-BESS connected system and it can also minimize the operating cost by dispatching the generation units optimally.

Role of vanadium redox flow batteries in the energy management system of isolated microgrids

The small size of isolated microgrids (IMGs), high intermittency and fluctuations of renewable generations, and low inertia of distributed energy resources make the frequency an important factor in the operation of IMGs that should be managed considering technical and economic constraints. The fast response time and long lifecycle of vanadium redox flow batteries (VRFBs) make them a promising candidate for energy and frequency management of IMGs. Accordingly, this paper proposes a novel energy management system (EMS) for IMGs which aims to optimize energy and reserve scheduling of VRFBs in coordination with droop controlled distributed generators. The objective of the EMS is to minimize the total operation cost of the IMG while dynamic and static frequency securities are preserved. In the proposed EMS, the hierarchical control structure of IMGs is precisely formulated and the VRFB is incorporated in the EMS to provide both energy and reserve in primary and secondary control levels. Moreover, to get accurate results, the nonlinear characteristics of VRFBs are considered in the developed model and linearized by an efficient approach. The proposed EMS is formulated as a two-stage stochastic mixed-integer linear programming problem (MILP) that guarantees the global optimal solution. Case studies on a test IMG indicate that optimal coordination of VRFBs in energy and reserve scheduling can reduce the operation cost more than 11.67%.

Maximum sensitivity-constrained coefficient diagram method-based PIDA controller design: application for load frequency control of an isolated microgrid

This paper proposes an improved coefficient diagram method (CDM) for proportional integral derivative acceleration (PIDA) controller design. In the improved CDM, stability indices are obtained using a graphical approach based on the maximum sensitivity constraints. The stability indices play an important role in the designing of the controller and stability of the closed-loop control system. Further, the improved CDM is utilized to compute the analytical expressions for the coefficients gain of PIDA controller. From the application point of view, the proposed control approach is designed for load frequency control (LFC) of an isolated microgrid (IMG). In IMG, the generators cannot supply constant electrical power and sometimes cause an imbalance between power generation and demand. Thus, LFC scheme is applied to maintain the balance between power generation and demand. The effectiveness and robustness of proposed control approach are analyzed for IMG system under $$\pm 50$$ % parametric uncertainty, random load demand, random solar and wind power deviation profile. The efficacy and performance of proposed control approach are examined in comparison with the published PID, 2DOF-PID and PIDA control schemes.

Modeling of an isolated microgrid with hybrid PV-BESS system for peak load shaving simulation

In this paper, a simplified model of an isolated microgrid (IMG) with hybrid photovoltaic (PV)-battery energy storage system (BESS) is discussed. The concept of peak load shaving is also demonstrated. The developed model helps an isolated power system to minimize the demand and maximize the economic benefit. MATLAB/Simulink tool was used to simulate the electrical circuit of the IMG system. The IMG model contains four sub-systems, namely the PV model, time varying load profile model, BESS model and gas turbine generator (GTG) dispatch model. To evaluate the performance of the developed IMG, a simulation case study was conducted under realistic load conditions of Universiti Teknologi PETRONAS (UTP). Results indicated that simulation illustrates the precise situation of the real-time system, as found in the UTP microgrid. Results also revealed that the concept of peak load shaving broadly illustrated in this study. The implementation of the proposed IMG model may bring economic benefit by minimizing peak load demand. © 2021 Md Masud Rana et al.