Grid-connected Microgrid System Research Articles

Optimal scheduling of microgrids considering real power losses of grid-connected microgrid systems

Energy conservation, emission reduction and vigorous development of new energy are inevitable trends in the development of the power industry, but factors such as energy storage loss, solar energy loss and line loss in real power situations have led the problem to a complex direction. To address these intricacies, we use a more precise modeling approach of power loss and propose a collaborative optimization method integrating the Deep-Q-Network (DQN) algorithm with the multi-head attention mechanism. This algorithm calculates weighted features of the system’s states to compute the Q-values and priorities for determining the next operational directives of the energy system. Through extensive simulations that replicate real world microgrid (MG) scenarios, our investigation substantiates that the optimization methodology presented here effectively governs the distribution of energy resources. It accomplishes this while accommodating uncertainty-induced losses, ultimately achieving the economic optimization of MG. This research provides a new approach to deal with problems such as energy loss, which is expected to improve economic efficiency and sustainability in areas such as microgrids.

Power Quality Improvement and Seamless Transfer in a Grid-connected Microgrid System using H∞ Controller

Power Quality Improvement and Seamless Transfer in a Grid-connected Microgrid System using H∞ Controller

Resilience analysis and improvement strategy of microgrid system considering new energy connection.

With the increasing demand for electricity, microgrid systems are facing issues such as insufficient backup capacity, frequent load switching, and frequent malfunctions, making research on microgrid resilience crucial, especially to improve system power supply reliability. This paper proposes a method for analyzing the resilience metric of new energy grid-connected microgrid system, and proposes optimization strategies to improve resilience. Firstly, a measurement method for the resilience of the microgrid system is established based on the operating characteristics of the system components. Secondly, the sensitivity relationship between system resilience and parameters is established, and an optimization model for resilience improvement strategies of microgrid systems based on parameter sensitivity is constructed. Finally, simulation verification is conducted based on the IEEE 37-node microgrid system. The results show that the proposed measurement method can scientifically and reasonably measure the resilience of the microgrid system, and the resilience improvement strategy significantly improves the operational resilience, verifying the effectiveness and robustness of the proposed analysis method.

A swarm-intelligent based load-shifting strategy for clean and economic microgrid operation

The required load in a typical microgrid structure fluctuates from hour to hour. Based on the peaks and troughs of the load demand curve, the power system utilities preset different price of electricity at various periods of the same day which is referred to as time-of-use (TOU) pricing policy. An optimal economic strategy called demand side management (DSM) reduces load during peak hours by shifting the elastic loads and compensates the shifted load by increasing the demand during valley hours. This recreates the total demand pattern on the demand price elasticity relation. The novel benefaction of this research suggests a DSM approach based on a hybrid intelligence technique to attain a compromised solution between minimum generation costs and pollutants emitted by DERs of an LV grid-connected microgrid system. Several grid involvement strategies, power market pricing types, and demand response mechanisms are examined in five separate instances for the microgrid system. The outcomes achieved in each example show that the recommended DSM technique may be applied and is appropriate in terms of cost reduction. When 30–40% of customers participated in the DSM curriculum, the generation cost was reduced by 10–13%. Environment constrained economic dispatch provided a superior compromise amongst lowest generation cost and emission for different microgrid load models. Statistical analysis and comparison of the results from previously published literatures validates the superiority of the proposed approach incorporated with DSM policy.

Optimization of distribution network operating parameters in grid tied microgrid with electric vehicle charging station placement and sizing in the presence of uncertainties

ABSTRACT The power generated by renewable sources is prone to uncertainties which encourages to perform effective modelling to ensure the reliable operation of the grid-connected microgrid (MG) system. This work focuses on the uncertainty modelling of primary sources of solar power, wind power and electric vehicle (EV) load considering three factors battery capacity, state of charge (SoC) and type of EVs charged by employing Monte-Carlo Simulation (MCS) to minimize the distribution system's voltage stability, reliability and power loss (VRP) index. The objective function is tested on the modified IEEE-33 bus distribution system under three diverse scenarios with optimum sizing and placement of RESs and EVCS. To obtain optimal solutions for the proposed problem in a reasonable computation time, modified version of teaching and learning-based optimization (TLBO) and the JAYA algorithm are applied as the rate of convergence is superior to other existing methods in the literature and does not require any precise control parameters. For all the scenarios, it can be seen that the modified JAYA algorithm outperforms TLBO and other existing approaches. The findings of the results reveal the efficacy of uncertainty modelling in a proposed grid-connected DC MG to curtail the VRP index.

Design and implementation of an off-grid hybrid microgrid for Chittagong and Faridpur

The challenge of rural electrification has become more challenging today than ever before. Grid-connected and off-grid microgrid systems are playing a very important role in this problem. Examining each component’s ideal size, facility system reactions, and other microgrid analyses, this paper proposes the design and implementation of an off-grid hybrid microgrid in Chittagong and Faridpur with various load dispatch strategies. The hybrid microgrids with a load of 23.31 kW and the following five dispatch algorithms have been optimized: (i) load following, (ii) HOMER predictive, (iii) combined dispatch, (iv) generator order, and (v) cycle charging dispatch approach. The proposed microgrids have been optimized to reduce the net present cost, CO2 emission, and levelized cost of energy. All five dispatch strategies for the two microgrids have been analyzed in HOMER Pro. Power system reactions and feasibility analyses of microgrids have been performed using ETAP simulation software. For both the considered locations, the results propound that load following is the outperforming approach having the lowest energy cost of $0.1728/kWh, operational cost of $2944.13, present cost of $127,528.10, and CO2 emission of 2746 kg/year for the Chittagong microgrid and lowest energy cost of $0.2030/kWh, operating cost of $3530.34, present cost of 149,287.30, and CO2 emission of 3256 kg/year for Faridpur microgrid with a steady reaction of the power system.

Investigating effect of various time varying load models in grid connected microgrid system integrated with renewables and cogeneration units

ABSTRACT The optimal allocation of sources considering voltage-dependent load models is essential as the power consumption of the loads is sensitive to voltage magnitude. In this paper, optimal allocation of microgrid system with cogeneration units, renewable energy sources (RES), shunt capacitors and heat boiler are determined for constant, residential, industrial, commercial and mixed load models. The cost, emission, energy loss, voltage deviation and voltage stability values for each load model is determined using particle swarm optimisation (PSO) integrated fuzzy max–min approach while the uncertainties in RES are taken into account. Results demonstrate that the cost, energy loss and voltage deviation values are maximum for constant power (CP) load model compared with other load models. Furthermore, the system with constant impedance (CZ) load achieves maximum loading capability than with other types of constant loads. The proposed method is validated on 33-bus grid-connected microgrid system with all the load models.

Analysis of microgrid configuration with optimal power injection from grid using point estimate method embedded fuzzy-particle swarm optimization

This paper aims to analyze the effect of integration of combined heat and power (CHP) units, renewables, shunt capacitors, and a heat boiler in a grid connected microgrid (GMG) system. In addition to that, a comparative study is conducted between the GMG and zero bus concept based microgrid (ZBMG) systems. In ZBMG, a predefined amount of power is injected from the grid. Therefore, one of the dispatchable distributed energy resources (DERs) in the ZBMG maintains the power balance and the corresponding DER unit is entitled as zero bus DER. In this paper, eight different microgrid configurations are formed by several combinations of renewable and non renewable sources, which are categorized under GMG and ZBMG systems. The multiple objectives such as total cost, emission, and energy loss are combined and solved using fuzzy technique and particle swarm optimization (PSO) algorithm. Also, point estimate method (PEM) is implemented to handle the uncertainty in renewables. The effect of grid, dispatchable units, renewables, and heat boiler on the objectives in each microgrid configuration is inspected. The results show that the microgrid configuration with non renewables is attained minimum cost and has a minimum emission with renewables. The integration of all types of sources in a microgrid configuration leads to a decrement in all the objectives. The proposed method is tested on a 33-bus grid connected microgrid system considering electrical and heat loads.

A Comprehensive Review of Digital Twin Technology for Grid-Connected Microgrid Systems: State of the Art, Potential and Challenges Faced

The concept of the digital twin has been adopted as an important aspect in digital transformation of power systems. Although the notion of the digital twin is not new, its adoption into the energy sector has been recent and has targeted increased operational efficiency. This paper is focused on addressing an important gap in the research literature reviewing the state of the art in utilization of digital twin technology in microgrids, an important component of power systems. A microgrid is a local power network that acts as a dependable island within bigger regional and national electricity networks, providing power without interruption even when the main grid is down. Microgrids are essential components of smart cities that are both resilient and sustainable, providing smart cities the opportunity to develop sustainable energy delivery systems. Due to the complexity of design, development and maintenance of a microgrid, an efficient simulation model with ability to handle the complexity and spatio-temporal nature is important. The digital twin technologies have the potential to address the above-mentioned requirements, providing an exact virtual model of the physical entity of the power system. The paper reviews the application of digital twins in a microgrid at electrical points where the microgrid connects or disconnects from the main distribution grid, that is, points of common coupling. Furthermore, potential applications of the digital twin in microgrids for better control, security and resilient operation and challenges faced are also discussed.

Optimal designing of grid-connected microgrid systems for residential and commercial applications in Pakistan

Conventional energy sources (CESs) are currently serving most of the global energy demands, but they will be substantially depleted as moving towards the end of this decade. The generation of electricity from such sources is causing the emission of greenhouse gases that is resulting in deleterious effect on the environment along with changing climatic and energy patterns of the planet. Therefore, the world is heading toward decentralization, and microgrids are playing a key role in this process. The advantages of renewables, which are acknowledged globally as benign, eco-friendly, economical, and inexhaustible resources available worldwide, are to credit for such a massive surge in the utilization of renewable resources in microgrid technology. Despite having an enormous renewable energy potential, Pakistan spends a sizable portion of its budget on energy imports of coal, oil, and liquefied natural gas, however, with good planning, current energy crises might be eliminated or at least mitigated to a greater extent, assuring energy security, economic prosperity, and lower carbon emissions inside the country. This study considers the optimal component planning in a grid-connected microgrid with five objectives to achieve that are to reduce the cost of energy, increase the renewable share, cut greenhouse gas emissions, enhance the reliability of power supply and to make electricity generation sustainable in the long run for the country. Different solar PV capacities are tested against the energy cost, renewable share and emission of greenhouse gases in order to attain the trade-off. The cost of energy is minimized by 92.47%, renewable share rises to 85%, and CO2 emissions are decreased by 48% for residential application. In the case of commercial application, however, the cost of energy is lowered by 48.52%, the renewable energy share rises to 71.1%, and CO2 emissions are reduced by 61% through incorporating solar PV into the current power system.

Energy Internet-Based Load Shifting in Smart Microgrids: An Experimental Study

This study investigated a grid-connected smart microgrid (MG) system integrating solar photovoltaic (PV) panels and a battery energy storage system (BESS) as distributed energy resources (DERs) to locally serve residential loads. The load-shifting demand-side management (DSM) technique was employed to effectively manage the load appliances. The proposed load-shifting algorithm relies on minimum price incentives to allow customers to allocate their load appliances economically during minimum price periods. The algorithm considers the waiting times and minimum tariff periods for appliances, calculates precise operating durations for each appliance, and prioritizes powering the appliances from the MG first, followed by the main grid. The system comprises two non-shiftable and three shiftable loads. When the MG power is insufficient to activate all shiftable loads, the system transfers the remaining unsupplied shiftable appliances to periods with low-priced energy. The Energy Internet concept is adopted to manage energy and monitor usage when a customer is unable to check the accuracy of their energy meter by supervising the system’s features on-site. The proposed comprehensive system enables load management, continuous monitoring, customer awareness, and energy cost saving. Six cases were studied, both numerically and experimentally, with varying MG power generation and load pre-scheduling periods, with and without DSM application. In all adopted cases, the implemented system save energy costs by at least 50%.

Optimal scheduling in demand-side management based grid-connected microgrid system by hybrid optimization approach considering diverse wind profiles

Demand side management (DSM) is one of the trending economic strategies which shifts the elastic demand to the off-peak hours from the peak hours so as to reduce the overall generation cost of the system. The work done in this paper can be categorized in three phases. In the first phase, various wind speed to power conversion mathematical models available in literature are analysed to find out the one with maximum level of wind penetration. For second phase, an economic DSM strategy is implemented to restructure the forecasted load demand model for various participation levels. In the final phase the cost-effective optimization of two microgrid distribution systems are percolated. As an optimization tool, novel hybrid CSAJAYA has been used to carry on the study. Different types of grid participating and pricing strategies along with valve point loading effect and wind energy uncertainty are considered to amplify the complexity and practicality of the study. The generation costs reduced from 3 to 5% when the forecasted demand was reformed with 20% DSM participation for both the test systems. A detailed comparison with the results from various optimization tools studied confirms the effectiveness of the proposed hybrid approach. The hybrid optimization tool presented in this paper performs better in terms of central tendencies, nonparametric statistical analysis, and algorithm execution time.

Comparative Analysis of Lithium-Ion and Lead–Acid as Electrical Energy Storage Systems in a Grid-Tied Microgrid Application

Microgrids (MGs) are a valuable substitute for traditional generators. They can supply inexhaustible, sustainable, constant, and efficient energy with minimized losses and curtail network congestion. Nevertheless, the optimum contribution of renewable energy resource (RER)-based generators in an MG is prohibited by its variable attribute. It cannot be effectively deployed due to its application’s power quality and stability issues. Therefore, an energy storage system is employed to alleviate the variability of RERs by stabilizing the power demand against irregular generation. Electrical energy storage systems (EESSs) are regarded as one of the most beneficial methods for storing dependable energy supply while integrating RERs into the utility grid. Conventionally, lead–acid (LA) batteries are the most frequently utilized electrochemical storage system for grid-stationed implementations thus far. However, due to their low life cycle and low efficiency, another contending technology known as lithium-ion (Li-ion) is utilized. This research presents a feasibility study approach using ETAP software 20.6 to analyze the performance of LA and Li-ion batteries under permissible charging constraints. The design of an optimal model is a grid-connected microgrid system consisting of a PV energy source and dynamic load encompassed by Li-ion and LA batteries. Finally, the comparative study led to significant conclusions regarding the specific attributes of both battery technologies analyzed through the operation, revealing that Li-ion is a more conducive energy storage system than LA.

Demand Response Management of a Residential Microgrid Using Chaotic Aquila Optimization

In this paper, Chaotic Aquila Optimization has been proposed for the solution of the demand response program of a grid-connected residential microgrid (GCRMG) system. Here, the main objective is to optimize the scheduling pattern of connected appliances of the building such that overall user cost are minimized under the dynamic price rate of electricity. The GCRMG model considered for analysis is equipped with a fuel cell, combined heat and power (CHP), and a battery storage system. It has to control and schedule the thermostatically controlled deferrable and interruptible appliances of the building optimally. A multipowered residential microgrid system with distinct load demand for appliances and dynamic electricity price makes the objective function complex and highly constrained in nature, which is difficult to solve efficiently. For the solution of such a complex highly constrained optimization problem, both Chaotic Aquila Optimization (CAO) and Aquila optimization (AO) algorithms are implemented, and their performance is analyzed separately. Obtained simulation results in terms of optimal load scheduling and corresponding user cost reveal the better searching and constrained handling capability of AO. In addition, experimental results show that a sinusoidal map significantly improves the performances of AO. Comparison of results with other reported methods are also made, which supports the claim of superiority of the proposed approach.

Optimal energy management of grid-connected multi-microgrid systems considering demand-side flexibility: A two-stage multi-objective approach

• Proposing stochastic multi-objective framework considering demand-side flexibility. • Providing opportunity of cost-saving and smoothing load profile by coordinated DR. • Proposed model remains the operating cost of multi-microgrid systems at its optimal. • Introducing APFDPPI index which evaluates the energy flexibility of DR programs. • Performing a sensitivity analysis on the battery scaling factor. This paper proposes multi-objective optimization framework to enhance the performance of demand response programs in distribution networks. The demand response programs are one of the main resources to enhance the flexibility of the energy systems to manage the uncertain behavior of renewable generation and demand loads. But, the uncoordinated response of customers creates a new peak in the load profile when the market prices are low. Therefore, we present a two-stage multi-objective framework that simultaneously reduces the operating costs and enhances the efficiency of demand response programs in the grid-connected microgrid systems. The first stage focuses on the optimal energy management of the grid-connected microgrid systems from the economic perspective. The second stage focuses on the demand-side flexibility to uniform the load profile. Also, we introduce the Average Power Flexibility during Peak Period Index (APFDPPI) to evaluate the energy flexibility of the demand response programs. The proposed model has been tested on a standard grid-connected microgrid, and the simulation results show that the proposed model improves the amount of energy not served by 22.12%. Also, the peak load and the load factor have been improved by 12.96% and 15.17%, respectively compared to uncoordinated demand response programs.

Optimal Design of Grid-Connected Microgrid System for Cold Chain Logistics Centre in China

Optimal Design of Grid-Connected Microgrid System for Cold Chain Logistics Centre in China

A Capacity Optimization Method for a Hybrid Energy Storage Microgrid System Based on an Augmented ε- Constraint Method

In general, microgrids have a high renewable energy abandonment rate and high grid construction and operation costs. To improve the microgrid renewable energy utilization rate, the economic advantages, and environmental safety of power grid operation, we propose a hybrid energy storage capacity optimization method for a wind–solar–diesel grid-connected microgrid system, based on an augmented ε- constraint method. First, the battery is coupled with a seasonal hydrogen energy storage system to establish a hybrid energy storage model that avoids the shortcomings of traditional microgrid systems, such as a single energy storage mode and a small capacity. Second, by considering the comprehensive cost and carbon emissions of the power grid within the planning period as the objective function, the abandonment rate of renewable energy as the evaluation index, and the electric energy storage and seasonal hydrogen energy storage system operating conditions as the main constraints, the capacity allocation model of the microgrid can be constructed. Finally, an augmented ε- constraint method is implemented to optimize the model above; the entropy–TOPSIS method is used to select the configuration scheme. By comparative analysis, the results show that the optimization method can effectively improve the local absorption rate of wind and solar radiation, and significantly reduce the carbon emissions of microgrids.

Parameter design method of grid-connected inverter microgrid system

LCL filter is widely used in three-phase voltage converters due to its superior high-frequency harmonic suppression ability. In this paper, aiming at the instability problem caused by the resonance peak of the impedance characteristics of the LCL filter third-order system, the relationship between the parameters of the filter inductance, damping resistance, and the harmonic suppression ability is deduced. The impedance analysis method is used to obtain the constraint conditions of the grid stability on the LCL parameters. Based on the stability criterion, a parameter design scheme of passive damping LCL filter is proposed. Finally, experiments are conducted on filters that conform to the proposed design method, and the simulation results verify the rationality and effectiveness of the design method.

A Comparative Study of the Influence of BESS and STATCOM on Post-Fault Voltage Recovery in Microgrid

Reliable and efficient power flow in the electrical grid is crucial given network expansion and the incorporation of numerous renewable sources. Microgrids are becoming more and more important in the global energy sector due to its numerous benefits. The variable nature of distributed energy resources (DER) in microgrid makes large-scale DER integration potentially unstable for system voltage. Grid regulations place restrictions on the voltage control of DER unit, which raises the need for reactive power support. Proper placement of flexible AC transmission system (FACTS) under post-fault conditions may enable faster voltage recovery. In this work, battery energy storage system (BESS) and static synchronous compensator (STATCOM) have been considered for improving the post-fault voltage in DER integrated weakly grid-connected microgrid system. Two operation scenarios have been considered for analyzing the behavior of BESS and STATCOM individually at post-fault situation. According to the results of the simulation, BESS requires lesser rating than STATCOM for faster recovery of post-fault voltage of the system.

Mathematical Model for Household Off-Grid Simulation (Off-Grid System Sizing)

Abstract The paper presents the results of the research, which was initiated in our previous publication. The main goal of the research is to develop and validate our own multi-objective simulation tool for determination of optimal mix and sizing of off-grid and grid-connected microgrid systems. The first version of the developed model was tailored specifically for simulation of household off-grid system, which consisted of solar photovoltaics (PV), micro wind turbine, electric batteries, and backup power generator. Proposed algorithms are based on simulation of mentioned resources and hourly electric loads of off-grid system with the objective to reduce unsupplied energy volumes and total system costs. Several alternatives were considered with different configurations of the off-grid system and dispatching strategies of available resources. The developed model was validated with calculations of real off-grid system and results were compared to those, which were made in the previous publication, using Homer Pro software.