Integration Of Microgrids Research Articles

Demand response based microgrid's economic dispatch

The development of energy management tools for next-generation Distributed Energy Resources (DER) based power plants, such as photovoltaic, energy storage units, and wind, helps power systems be more flexible. Microgrids are entities that coordinate DERs in a persistently more decentralized fashion, hence decreasing the operational burden on the main grid and permitting them to give their full benefits. A new power framework has emerged due to the integration of DERs-based microgrids into the conventional power system. With the rapid advancement of microgrid technology, more emphasis has been placed on maintaining the microgrids' long-term economic feasibility while ensuring security and stability. The objective of this research is to provide a multi-objective economic operation technique for microgrids containing air-conditioning clusters (ACC) taking demand response into account. A dynamic price mechanism is proposed, accurately reflecting the system's actual operational status. For economic dispatch, flexible loads and air conditioners are considered demand response resources. Then, a consumer-profit model and an AC operating cost model are developed, with a set of pragmatic constraints of consumer comfort. The generation model is then designed to reduce the generation cost. Finally, a microgrid simulation platform is developed in MATLAB/Simulink, and a case is designed to evaluate the proposed method's performance. The findings show that consumer profit increases by 69.2% while ACC operational costs decrease by 18.2%. Moreover, generation costs are reduced without sacrificing customer satisfaction.

Overcoming the Fluctuating Curve from PV Power Generation by Modelling the Integration of Hydrogen Energy Storage Into Electricity Microgrid

Java Madura Bali (Jamali) system is the Indonesian largest grid, which contributes approximately 61%, with the Coal Thermal dominates by 59% and followed by the New Renewable Energy (NRE) of 9%. Solar Photovoltaic Power Plants (SPP) contribute only 1% from the NRE itself. Low voltage customers (TR) are approximately 61% with the residential contribute approximately 42%. The rates of the national SAIDI is 12.72 hours/subscriber/year and the national SAIFI is 9.25 times per subscriber/year. There is some challenge in regulating voltage in area with high penetration of solar PV, case of voltage fluctuation in response to the fluctuating of solar irradiance, as well as other factors such as load transient. This voltage fluctuation is proportional to the amount of current generated by the PV system and also proportional to the solar irradiance.Hydrogen energy storage (HES) is an alternative to NRE-based energy storage technology. Integrating solar PV with hydrogen energy storage and optimisation device may mitigate PV-driven voltage fluctuation, preventing excessive reserve power flow on the grid. The hydrogen energy storage system can cover variation of the loads at the nearby solar PV system in the microgrid and the ability to manage those loads, as mentioned in the energy management system. Integrating the HES within Solar PV system can improve the curve shape, improve system reliability and voltage stability, especially in the Residential Microgrid. Also may build the opportunities to earn new revenues from wholesale electricity markets, enhancing the reliability rate and competitive monetary value.

Enhancing Microgrid Stability through a Hybrid Virtual Synchronous Machine Topology

Abstract: Combined heat and power generation (DER) produced by diesel generators is gradually being replaced by consumer renewable energy (RES). However, since RES sources often reduce the inertia of the grid, they can cause serious problems, especially in microgrids. Therefore, inverters interacting with different DERs connected to the microgrid need to change their control method. Because of their similarity to synchronous motors, virtual synchronous generators (VSGs) are one of the best known for microgrid power generation and can be included in a safety assessment. Many questions remain, as VSGs are still a new concept and are often considered for DER integration in microgrids. In addition, although the business and the ideas that develop it are discussed in the business literature, there is no difference in everything that can be found in the literature. The integration of VSG-based inverters into microgrids with different renewable energy sources is the focus of this article. This PhD is the result of a collaboration between the two laboratories G2Elab and Lab, Schneider Electric and its R&D transformer group.

Fuzzy-based cooperative interaction between stand-alone microgrids interconnected through VSC-based multiterminal converter

This paper proposes a cooperative strategy for the flexible integration of stand-alone AC microgrids using an intermediate multiterminal DC link based on voltage source converters. The strategy manages cooperative power exchange between microgrids through a knowledge-based fuzzy inference system that relies on the current operating conditions of the microgrids. By determining the amount of power to be exchanged between microgrids to improve global reliability, the cooperative strategy achieves an overall reduction in load loss and an increase in the use of available renewable energy. Additionally, the multiterminal DC link provides complete isolation between microgrids, allowing for independent AC bus voltage regulation and management. The effectiveness and expandability of the proposed cooperative energy exchange strategy for enhancing the overall operation of multiple integrated microgrids have been fully verified by simulation and experimental validation.

Reinforcement learning-based composite differential evolution for integrated demand response scheme in industrial microgrids

The fourth industrial revolution is being propelled by the “Energy Internet,” which aims to encourage the integration of industrial multi-energy microgrids (MEMG) and renewable energy sources. The conventional demand response (DR) schemes only utilize a single energy source, which limits the industrial users (IUs) and prevents them from making full use of the demand side's communication capabilities. However, smart industrial multi-energy microgrids (MEMGs) give IUs additional options for meeting their energy needs by integrating diverse energy sources, including electricity, natural gas, and thermal power. This new approach to DR programs is known as “Integrated Demand Response” (IDR). This research work proposes a smart IDR program for a novel grid-connected industrial MEMG framework consisting of exhaust air wind turbines, concentrated photovoltaic-thermal panels, an electrical energy storage system (EES), a thermal energy storage (TES), a diesel generator, an indirect customer-to-customer energy trading platform, and typical electrical and thermal industrial loads. The proposed smart IDR considers the uncertainties of both wind and solar power generation and the buying and selling costs of electrical and thermal energy to automatically reduce the industry's total power consumption and battery EES degradation costs. A novel State-Action-Reward-State-Action (SARSA)-based composite different evolution (DE) method is proposed to solve a complex scenario-based non-convex optimization problem. It uses two selection strategies, three mutation strategies, and a positive feedback mechanism to change the states of the individuals. The strategies are coupled in pairs, resulting in a total of six distinct actions that may be performed by the SARSA agents. This allows an individual to not get stuck at a local optimum and adaptively benefit from all the mutation and parameter selection methods. Moreover, SARSA has introduced two more factors, the discount factor and the learning rate, which further improve the optimization performance. The proposed method is also compared with five other state-of-the-art methods to prove its effectiveness in minimizing industrial energy bills and battery degradation costs. The simulated results confirmed that the proposed SARSA-based composite DE algorithm has achieved the lowest total energy cost and battery degradation costs when compared with other state-of-the-art algorithms.

Design and Simulation of DC Microgrid for Utility

Due to the widespread use of direct current (DC) power sources, including fuel cells, solar photovoltaic (PV), and other DC loads, high-level integration of various energy storage systems, including batteries, supercapacitors, and DC microgrids, has become more significant in recent years. Additionally, DC microgrids do not experience problems with synchronization, harmonics, reactive power regulation, or frequency control like traditional AC systems do. The control of DC bus voltage as well as power sharing is complicated by the inclusion of various distributed generators, such as PV, wind, fuel cells, loads, and energy storage devices, in the same DC bus. Several control strategies, including centralized, decentralized, distributed, multilevel, and hierarchical control, are described to assure the secure and safe functioning of DC microgrids.

Microgrids in Competitive Market Environment: An Indian Perspective

Microgrids are believed to be the befitting green solution to the ever-rising energy crisis in the developing nations. The resource rich nations are rapidly shifting their dependence on microgrids to meet the reduced carbon footprint target at a global level. This paper addresses this issue and presents a detailed technical review on microgrid integration in competitive electricity market scenario. An in-depth coverage of the need for and importance of microgrid deployments across India is presented in this work. The relevant literature that highlights the significance of various energy storage systems is reviewed. The authors present the perspective of microgrid integration in a competitive market scenario covering both day ahead and real time market scenarios thereby discussing the concept of maximizing social benefit in a grid integrated microgrid framework. This work also focuses on microgrid optimization techniques and outlines a detailed comparison showing merits and demerits of all the techniques implemented by the researchers so far. The authors highlight the fact that green energy holds the potential to not only outgrow the fossil fuels but it shall do so by fetching the requisite economic benefit to the investors as well.

Reliability-Based Optimal Integrated Microgrid Scheduling in Distribution Systems

This paper proposes a reliability-based optimal scheduling model of integrated microgrids. The proposed model is capable of delivering optimal scheduling of each individual microgrid and aggregated system. In addition, it is compatible with both grid-connected and islanded operation modes. The developed problem formulation of the proposed model takes into account the reliability indices SAIDI, SAIFI, and CAIDI to evaluate the reliability of the integrated system. Numerical simulations on a modified IEEE-33 bus test system, involving four integrated microgrids, were performed to investigate the advantages and the robustness of the developed model. Furthermore, the impact of merging Battery Energy Storage Systems (BESSs) on the optimization outcome is examined, which demonstrates its significant effectiveness in improving the power systems' reliability.

State-of-the-Art Literature Review of Power Flow Control Methods for Low-Voltage AC and AC-DC Microgrids

The development of AC distribution systems provides for the seamless integration of low-voltage microgrids with distributed energy resources (DERs). This poses new challenges for the control of normal, emergency, and post-emergency states of microgrids, calling for the creation and development of information and communications technology infrastructure. Power converters/inverters that are used to integrate renewable DERs lack inertia. Along with them, fossil fuel-fired generation units are also being integrated into microgrids. These include gas generator sets, diesel generator sets, and microturbines, having small (up to 1–2 s) values of mechanical inertia constants—Tj. This leads to an increase in the rate of transients by a factor of 5–10. Under these conditions, the technical requirements for the speed of automatic power flow control systems, as well as the methods they rely on, have to be reconsidered. Microgrids include DC microgrids, AC microgrids, and hybrid (AC-DC) microgrids. In the case of hybrid microgrids, DERs are connected to the DC grid and are integrated into the AC grid through a common inverter. The complexity of the task of microgrid control is due to the need to choose properly the type and extent of control actions so as to prevent the emergence and development of accidents. The employed control methods must ensure the reliable power supply to consumers and the quality of power in microgrids, as well as the reliable operation of the external distribution systems into which they are integrated. The article gives an overview of control methods for low-voltage AC and AC-DC microgrids, which allow one to tackle effectively solve the tasks.

A State-of-the-Art Review on Electric Power Systems and Digital Transformation

The electric power system is undergoing a significant transformation driven by advances in digital technologies. This article provides a comprehensive and detailed analysis of recent advances and the future outlook of electric power systems, with a particular emphasis on the impacts of digital transformation. By conducting a thorough examination of over 150 up-to-date research papers, the study highlights the key developments shaping the future of the field, such as the integration of renewable energy, distributed generation, microgrids, and smart grids. The analysis includes comparison tables and SWOT analysis for each technology, offering insights into their strengths, weaknesses, opportunities, and threats. The study also provides a historical and conceptual overview of digital transformation in electric power systems, exploring recent digital technologies such as cloud computing, the Internet of Things, blockchain, digital twins, and their impact on the electric power system. The article concludes by addressing the barriers and challenges in this transformation. Overall, this research offers a comprehensive and up-to-date analysis of the current state and future outlook of electric power systems, providing valuable insights for researchers, practitioners, and policymakers.

Artificial intelligence applications for microgrids integration and management of hybrid renewable energy sources

The integration of renewable energy sources (RESs) has become more attractive to provide electricity to rural and remote areas, which increases the reliability and sustainability of the electrical system, particularly for areas where electricity extension is difficult. Despite this, the integration of hybrid RESs is accompanied by many problems as a result of the intermittent and unstable nature of RESs. The extant literature has discussed the integration of RESs, but it is not comprehensive enough to clarify all the factors that affect the integration of RESs. In this paper, a comprehensive review is made of the integration of RESs. This review includes various combinations of integrated systems, integration schemes, integration requirements, microgrid communication challenges, as well as artificial intelligence used in the integration. In addition, the review comprehensively presents the potential challenges arising from integrating renewable resources with the grid and the control strategies used. The classifications developed in this review facilitate the integration improvement process. This paper also discusses the various optimization techniques used to reduce the total cost of integrated energy sources. In addition, it examines the use of up-to-date methods to improve the performance of the electrical grid. A case study is conducted to analyze the impact of using artificial intelligence when integrating RESs. The results of the case study prove that the use of artificial intelligence helps to improve the accuracy of operation to provide effective and accurate prediction control of the integrated system. Various optimization techniques are combined with ANN to select the best hybrid model. PSO has the fast convergence rate for reaching to the minimum errors as the Normalized Mean Square Error (NMSE) percentage reaches 1.10% in 3367.50 s.

Fractional order [formula omitted] controller for microgrid power system using cohort intelligence optimization

Microgrids are the future of energy management systems. Effective deployment and integration of microgrids can provide energy independence to many communities. The effectiveness of a microgrid primarily depends on its stability and reliability. Fractional regulators offer promising solutions to ensure stable microgrid performances. This article proposes a Fractional order Proportional–Integral–Derivative (FOPID) based secondary Load Frequency Control (LFC) for single area and dual-area AC microgrid systems. Cohort Intelligence (CI) based optimization was employed to tune the five major gain values of fractional PID regulators. The performance of the proposed CI tuned FOPID regulator was compared with that of the traditional PID controller tuned by Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) on the same single and dual control area microgrid systems. Four different cases of AC microgrid simulations were explored for LFC performance assessments and effective comparisons among different controllers and tuning algorithms. The first case considered load changes in single area AC microgrid with and without distributed energy system. The second case considered load variations in the two area AC microgrid system. The third and fourth cases included variations in random step load and system parameters respectively. Primary results affirm the superiority of the CI tuned FOPID regulator over its GA and PSO tuned PID counterparts in terms of its better steady-state precision, expressed in terms of the Integral Time Absolute Error (ITAE) selected as the objective function.

An Advanced Control and Stability Analysis of Wind Solar Integrated Microgrid

In this article, we suggest a micro-grid methodology based on renewable energy sources (RES) in order to make more efficient use of renewable energy sources and use less energy from the traditional power grid. Off-grid, RES likes solar (generated by a photovoltaic panel) and wind can be stored in a battery and utilised to power loads. As an additional measure, a Fuzzy logic-based energy-saving method has been applied. Microgrids are used to integrate these systems in a decentralised fashion, and they provide a suite of technology solutions that facilitate communication between end users and dispersed power plants. This raises the question of how best to administer these systems. In order to guarantee that both the generating and distribution systems produce energy at low operating costs, energy management in microgrids is described as a data and monitoring network that allows the required functions. In this study, we discuss the difficulties associated with using RES and managing a microgrid. Voltage and frequency variations result from the dynamic nature of DG systems. Unpredictable dynamics result from the load's unknowability. As a result of this nonlinear dynamic, there are observable changes to the microgrid's operation. In this study, we test the efficiency of the microgrid in a variety of settings. We compare the PI controller's performance on the MATLAB/Simulink platform to that of a Fuzzy logic-based controller with various levels of complexity.

An Advanced Control and Stability Analysis of Wind Solar Integrated Microgrid

In this article, we suggest a micro-grid methodology based on renewable energy sources (RES) in order to make more efficient use of renewable energy sources and use less energy from the traditional power grid. Off-grid, RES likes solar (generated by a photovoltaic panel) and wind can be stored in a battery and utilised to power loads. As an additional measure, a Fuzzy logic-based energy-saving method has been applied. Microgrids are used to integrate these systems in a decentralised fashion, and they provide a suite of technology solutions that facilitate communication between end users and dispersed power plants. This raises the question of how best to administer these systems. In order to guarantee that both the generating and distribution systems produce energy at low operating costs, energy management in microgrids is described as a data and monitoring network that allows the required functions. In this study, we discuss the difficulties associated with using RES and managing a microgrid. Voltage and frequency variations result from the dynamic nature of DG systems. Unpredictable dynamics result from the load's unknowability. As a result of this nonlinear dynamic, there are observable changes to the microgrid's operation. In this study, we test the efficiency of the microgrid in a variety of settings. We compare the PI controller's performance on the MATLAB/Simulink platform to that of a Fuzzy logic-based controller with various levels of complexity.

Compressed air storage: Opportunities and sustainability issues

AbstractAs an effective strategy to implement electrical load shifting and to encourage the use of alternative renewable energies, such as solar and wind generation, the energy storage system plays an important role in the energy internet and the smart grid. Compressed air energy storage is a promising technique due to its efficiency, cleanliness, long life, and low cost. This paper reviews CAES technologies and seeks to demonstrate CAES's models, fundamentals, operating modes, and classifications. Application perspectives are described to promote the popularisation of CAES in the energy internet and smart grids. We review recent work on CAES. We evaluate and analyse these results to discover gaps and opportunities. The most important results indicate that CAES is generally considered an EES (electrical energy storage) option for wind power integration. However, current research is beginning to investigate CAES in combination with solar energy systems. Gaps may be identified in the study associated with CAES for microgrid integration and demand management which are future uses of CAES.

Integration of CCHP microgrids in NZEB with critical loads under high PQR requirements, a position paper

In recent years, many projects have been developed to reduce the energy consumption of buildings, both from the point of view of energy efficiency and the integration of renewable energies. However, few projects are related to the problem of integrating DER in environments dominated by high-tech equipment, the so-called ”critical loads”: data centers, railroad stations, airports, and hospitals. The European Interreg Sudoe IMPROVEMENT project aim is to renovate existing public buildings where critical loads predominate, converting them into nearly zero-energy buildings (NZEB), and for this purpose, it integrates combined cooling, heat, and power (CCHP) microgrid with renewable and other distributed energy resources (DER) like hybrid energy storage systems (ESS). With still one year to go before the end of the project, the consortium partners present in this position paper the latest progress of their respective work packages to date.

Robust Coordinated Optimization With Adaptive Uncertainty Set for a Multi-Energy Microgrid

With the increasing integration of the multi-energy microgrid (MEM) with the distribution network (DN), the distributed coordination between MEM and DN becomes critical. This paper proposes a distributed scheduling method for the coupled MEM-DN under operational uncertainties. First, a worst-expectation min-max-max-min robust optimization model is formulated for MEM considering the uncertainties of renewable distributed generation (wind and photovoltaic) as well as its class probability. Second, the column and constraint generation algorithm with an alternating iteration strategy (C&CG-AIS) is proposed to accelerate the solution by decoupling the subproblems. Third, the multi-interval convex hull uncertainty set (MCHUS) is proposed to reduce the conservatism of robust optimization by decreasing the low-probability scenarios. Furthermore, the Bregman alternating direction method with multipliers (BADMM) is combined with the alternating optimization procedure (AOP) to overcome the convergence difficulty in the nonconvex distributed MEM-DN model. Finally, the effectiveness of the proposed model and method is verified by simulation tests based on IEEE-33 node DN and a park-level MEM.

Optimal Scheduling of Distribution Network With Autonomous Microgrids: Frequency Security Constraints and Uncertainties

Widespread integration of autonomous microgrids (MGs) into the distribution network (DN) makes the scheduling of distribution systems challenging. Especially, the uncertainties of renewable energy sources (RESs) and load demand put the MG frequency at the risk of violation for its low inertia and the high penetration of RESs. To address the schedule problems associated with uncertainties and frequency security, a day-ahead scheduling optimization model is proposed based on the chance-constrained programming (CCP) theory. The frequency security constraints and uncertainties of RESs/load demand associated with MGs are considered during the development of the proposed model. The total operation cost of the distribution system consisting of DN and MGs is minimized, while the MG frequency deviations caused by uncertainties are restricted in the predefined safe range by the proposed CCP-based model. Besides, a linearization method is presented and used to transform the proposed model into a mixed-integer linear program to determine the efficiency of the CCP-based model. Finally, numerous case studies are conducted to illustrate the effectiveness and good scalability of the proposed model and understand the advantages of using the model. The RT-LAB hardware-in-loop tests are carried out to study the real-time performance under the scheduling solved by the proposed model. Simulation and experimental results validate that the proposed model can be used to minimize the total operation cost of the DN system integrated with MGs while ensuring that the MG frequency deviations are operated within an acceptable range.

Simulation of Power Router-Based DC Distribution Systems with Distributed Generation and Energy Storage Units

The development of the electric power industry needs to be understood against the current backdrop of the transition to technological platforms facilitating the adoption of smart grids. Smart grids can be made up of separate clusters (microgrids) consisting of power consumers, power grids, and distributed generation (DG) units. To improve energy efficiency, DC microgrids can be integrated into smart grids to deliver power to consumers within a building (or several buildings) and at the sites of C&I facilities. It is advisable to carry out integrations of DC and AC microgrids with DG and energy storage units on the basis of power routers used to couple grids of different voltage classes. This study outlines a computer model of power router-based integration of DC and AC microgrids with distributed generation and energy storage units. The model was developed in the MATLAB environment. The paper also features the results of a study of the proposed methods as applied to voltage control under normal and emergency operating conditions of a DC and AC distribution grid.

A dynamic hybrid protection scheme for on-site emergency power system operated through an integrated microgrid during station blackout in NPP

Post Fukushima nuclear disaster, application of renewable energy operated integrated microgrid (IMG) into nuclear power plants for strengthening the station blackout (SBO) power supply becomes popular. The IMG powered emergency-SBO (EM-SBO) is a bidirectional power system which leads to substantial variation in fault current. On the other hand, as per the guidelines of nuclear regulatory authority, minimum protection scheme is to be provided for EM-SBO power system to avoid unnecessary tripping of the safety power system. This scenario is a challenging task and a serious concern to provide suitable protection mechanism. To address this issue, a dynamic hybrid protection (DHP) scheme (hybrid differential and adaptive overcurrent protection scheme) is proposed. The proposed DHP scheme has been validated in EMTP-rv and DigSILENT Power Factory simulation software followed by harmonics analysis through Simulink. Finally, the superiority of DHP scheme for IMG has been established.