Development Of Microgrids Research Articles

A risk-averse day-ahead bidding strategy of transactive energy sharing microgrids with data-driven chance constraints

The rapid development of microgrids (MGs) with various prosumers promotes the accommodation of renewable distributed generation (RDG) and provides platforms for local energy sharing among prosumers. However, the operational uncertainties pose enormous challenges to the day-ahead bidding of MGs in the wholesale electricity market and there is an urgent need for a local market to facilitate the local energy sharing. Thus, this paper proposes a risk-averse day-ahead bidding strategy for MGs with full consideration of the multiple uncertainties originating from the wholesale electricity market, RDG and loads. Based on the transactive energy (TE) sharing concept, the local market is formulated as a Stackelberg game (SG) to effectively capture the strategic interaction among the MG and prosumers, where a distributed iterative algorithm with a bisection approach that only requires exchanging TE-related information is adopted to achieve the SG equilibrium without compromising privacy concerns. To handle the uncertainties of RDG and loads, the power balances are formulated as chance constraints and a data-driven quantile forecasting method is developed for achieving the computational tractability of chance constraints without any prior knowledge or probability distribution assumptions. Furthermore, a risk criterion of the conditional value-at-risk is incorporated in the day-ahead bidding model of MGs for risk aversion towards uncertainties of the wholesale electricity market. The effectiveness of the proposed solution is extensively demonstrated through numerical simulation.

Research on Performance Evaluation Index System and Assessment Methods for Microgrid Operation in the Port Area

The vertical integration of ‘Generation-Grid-Load-Storage’ in microgrids for port areas is a prevailing trend. To comprehensively and accurately assess the operational efficiency of microgrids and develop an effective means for promoting the sustainable and scalable development of microgrids in port areas, an applicable evaluation index system and comprehensive evaluation method are essential. Addressing the issues of subjectivity in quantitative evaluation decision-making for different configuration and allocation schemes in port areas and the lack of a comprehensive evaluation system for microgrids in port areas, this study aims to scientifically and reasonably evaluate and select the most optimal configuration and energy dispatching schemes for microgrids in port areas. In this paper, the performance indicators of microgrids in port areas are hierarchically structured and classified into five dimensions: economic, energy efficiency, environmental, system reliability, and safety. A comprehensive evaluation index system for microgrid systems in port areas is constructed. Furthermore, an evaluation model for microgrid operational efficiency based on improved CRITIC-TOPSIS is proposed. The coefficient of variation is introduced to measure the relative strength and relative variation of indicators among dimensions, reducing the impact of correlation between indicators and improving the accuracy and objectivity of the evaluation results. Then, the TOPSIS method is used to calculate the comprehensive evaluation values and rank the optimal microgrid schemes in port areas. Finally, the feasibility of the evaluation index system and evaluation method for the operational efficiency of microgrids in port areas is verified through case analysis. The results indicate that the evaluation method based on improved CRITIC-TOPSIS can objectively and quantitatively evaluate the operational efficiency of microgrids in different port areas. The proposed method reasonably avoids the strong subjectivity in weight calculation by traditional expert judgment during the planning phase of microgrids in port areas, providing a new and scientifically effective engineering evaluation and analysis method for the evaluation of microgrid operational efficiency in port areas.

Multi-objective energy management of island microgrids with D-FACTS devices considering clean energy, storage systems and electric vehicles

Abstract The development of microgrids is progressing due to intelligent load demands, clean energy, batteries and electric vehicles. The presence of such systems in microgrids causes power balance inconsistency, leading to increased power losses and deviation in voltage. In this paper, a mixed-integer non-linear programming model is proposed for modelling island microgrid energy management considering smart loads, clean energy resources, electric vehicles and batteries. Similarly, a flexible distributed AC transmission system device is proposed to prevent voltage deviation and reduce power losses. A scenario-based multi-objective function has been proposed to decrease energy losses and voltage deviations and energy outages of clean energy resources, reduce emissions from fossil-fired distributed generation and finally decrease load outages to reduce the vulnerability of the islanded microgrid. Regarding the proposed mixed-integer non-linear model and the high number of variables and constraints, a modified evolutionary algorithm based on particle swarm optimization has been proposed to solve the proposed model, which can be more efficient than other algorithms to achieve global optimal solutions. The model presented is implemented on a 33-node island microgrid and the results illustrate that the proposed algorithm and model are effective in reducing energy losses and voltage deviation, as well as reducing the vulnerability of the microgrid. The simulation results demonstrate that the proposed approach can lead to significant improvements in the performance of the microgrid. Specifically, the approach can result in a 27% reduction in losses, a 6% reduction in pollution and a 31% improvement in voltage. Additionally, the approach allows maximum utilization of renewable energy sources, making it a promising solution for sustainable energy management.

Enhancing Microgrid Stability and Energy Management: Techniques, Challenges, and Future Directions

Microgrid technology offers a new practical approach to harnessing the benefits of distributed energy resources in grid-connected and island environments. There are several significant advantages associated with this technology, including cost-effectiveness, reliability, safety, and improved energy efficiency. However, the adoption of renewable energy generation and electric vehicles in modern microgrids has led to issues related to stability, energy management, and protection. This paper aims to discuss and analyze the latest techniques developed to address these issues, with an emphasis on microgrid stability and energy management schemes based on both traditional and distinct approaches. A comprehensive analysis of various schemes, potential issues, and challenges is conducted, along with an identification of research gaps and suggestions for future microgrid development. This paper provides an overview of the current state of the field and proposes potential areas of future research.

Understanding the community in community microgrids: A conceptual framework for better decision-making

A community microgrid comes with the introduction of non-conventional distributed renewable energy infrastructure, affecting the behaviour of community members and their relationship with energy. The aspects of ownership, trust, collaboration and its often-discursive structure will be reflected in the cultural and social factors, such as norms and values in a community. The success of specific community microgrids is widely dependent on the community's ability to engage in various activities connected to the microgrid installation and operation. This paper conceptualises existing literature on community microgrids, focusing on the representation and inclusion of community preferences, needs and behaviour across the development stages. From this analysis, a conceptual-theoretical framework is proposed based on social capital theory for identifying community characteristics to determine key needs and considerations for microgrid adoption. The framework is divided into four components: social capital, community capability, community type and microgrid impact. Social capital, including its dimensions such as structural, cognitive, and relational capital forms the foundation of the framework and serves to evaluate the community capability and determine its type, which in turn affects its impact on the community microgrid. Finally, we present an initial step in operationalising our conceptual framework as a practical tool to guide further research in the development of community microgrids. Ultimately, this research can benefit both academia and industry by providing a comprehensive and practical approach to understanding the importance of social factors in community microgrid success.

Segmentation of interconnected power systems considering microgrids and the uncertainty of renewable energy sources

AbstractThis paper proposes an approach for segmentation of power systems to prevent uncontrolled islanding. With the development of microgrids (MGs) and increased penetration of renewable energy sources (RESs) in the power system, it is necessary to consider the effect of MGs and the stochastic behaviour of RESs in the controlled islanding process. First, the enormous search space for finding the boundary points is reduced by the clustering of the coherent generators and the buses which are placed in sections that cannot be separated from the coherent groups. Then, linear AC power flow is defined as a sub‐problem and solved by linear programming to satisfy the power system and MG constraints. In this step, an optimization model is defined, and a mixed‐integer linear programming (MILP)‐based model is suggested to find cut‐sets and islands arrangement with reduced load shedding. In view of the fact that the fluctuation of RESs may have the significant effects on the power imbalance, to cover the uncertainties a scenario based stochastic simulation is considered. Finally, the effect of uncertainties on cut‐sets and load curtailment is evaluated. The effectiveness of the proposed methodology is demonstrated by the simulation on the test system.

Community response to microgrid development: Case studies from the U.S.

Microgrids could improve grid reliability and resiliency, while decentralizing, decarbonizing, and democratizing electricity provision. Recent federal and state level policies and investments have sought to encourage their development. Yet, little research has been done to understand how communities respond to microgrid proposals. We conducted case studies of community response to four different community microgrid proposals in the U.S. – two successful (Hot Springs, NC; Panton, VT) and two unsuccessful (Albany, NY; Carson, CA) – examining relevant media coverage and policy documents (n = 533) and conducting semi-structured interviews with active stakeholders (n = 28). Findings suggest that community leaders and local citizens initially viewed microgrids favorably, particularly those utilizing renewable energy as their primary generation source. Backup generation via fossil fuel sources appeared less problematic. Utility-backed proposals providing multiple component benefits in addition to resiliency – such as peak shaving and/or cost savings for utilities and transmission owners – proved more successful than those proposed by other entities without such benefits. Early, sustained, and responsive community engagement by the developer was also critical to project success – and will likely only become more so as microgrids scale up (both in numbers and size) and touch multiple stakeholders.

"Москітна флотилія" на енергетичному фронті: малі енергетичні мережі на базі цифрових платформ

In the conditions of Russia's military aggression, the role and importance of measures aimed at ensuring the energy security of the state is growing. The introduction of digital technologies has a significant potential for improving management mechanisms, increasing the reliability and efficiency of both individual components and the country's energy system as a whole. A special place in this process is occupied by the deployment and integration of the sector of local networks of renewable energy generation into the country’s energy system, which are created on the basis of digital platforms. The purpose of the proposed work is to define the potential of digital platforms as a means to coordinate the interaction between private generators of renewable energy in local energy markets. The research tools include structural, functional, systemic and institutional analysis. It is shown that the development of microgrids of renewable energy generation based on digital platforms is able to stimulate radical restructuring of the production system and electricity distribution markets. The author reveals various peculiarities of digital platforms as an organizational form of interaction in local energy markets. It is shown that they provide a synergistic effect of uniting small producers of renewable energy into a microgrid and forming a two-sector model of the public energy system. The structure of microgrid digital platforms is presented. They unite the owners of personal rooftop solar photovoltaic systems, wind, bio-, and hydropower units, power generation surplus storage stations, consumers, and energy distribution companies on the basis of the core platform. The article reveals the mechanism of building energy systems based on the principles of "Industry 4.0". Attention is focused on the need to implement a comprehensive policy to support the platformization of the renewable energy sector. The tools for its provision are presented.

Stability analysis framework for isolated microgrids with energy resources integrated using voltage source converters

Integrating distributed energy resources (DERs) enables the development of microgrids, which opens up a broad field of study. However, the dynamic behaviour of these energy resources presents challenges in these new electric systems. The stability of systems with high penetration of DERs is a developing research topic, where enhancement strategies are typically focused on specific issues, while general approaches often present several challenges without testing scenarios. In this document, an analysis of several stability issues is presented and tested in an islanded system based on the CIGRE low voltage benchmark. The conclusions obtained are noteworthy and propose further discussion and research, to enhance the understanding and future study of islanded microgrid stability with only converter-integrated energy resources.

Energy management method for microgrids based on improved Stackelberg game real-time pricing model

With the rapid development of microgrids with distributed generations (DGs) and energy storage system (ESS), it is important to study energy management methods to improve the operation economy of microgrids. However, there is currently a lack of research on microgrid’s energy management models including multi-party groups such as wind turbines, photovoltaics and ESS. This paper proposed an energy trading management method of microgrids based on Stackelberg game real-time pricing mechanism, which can solve the more complex optimization operation problem of microgrids. First, the rolling optimization was carried out to determine the charging and discharging behavior of ESS for maximizing the total benefit microgrid in the next few time slots. Further, a Stackelberg game real-time pricing model was built. The electricity prices of different entities in the microgrid in the next time slot were optimized by microgrid operator (MGO) to determine the load demand of each DG, preference parameter in the utility function of DGs was improved to promote the internal energy interaction and the economic benefits of the microgrid. Finally, the results show that our method can effectively improve DGs’ total utility and stimulate energy trading within the microgrid. Compared with no optimization and traditional method, the daily profit of MGO obtained by our method was increased by 31.89% and 5.4% respectively, verifying the economics of the proposed method.

Performance Under Limited Service Capacity for Load Balancing EV Charging Network

The economic benefit and energy security brought by renewable energy have greatly promoted the development of microgrid (MG). However, the load demand varies from area to area, resulting in the unbalanced load distribution among MGs. With the perfection of charging facilities, electric vehicle (EV) has attracted more consumers in the automobile market. A large number of EVs connected to MGs without coordination may threaten the safe operation of the power grid. Moreover, considering the constraints of economic factors, the number of charging piles in the MG is limited, i.e., the service capacity of MG is limited. Based on this, the impact of service capacity on the load balancing and average user time is studied. The load balancing matching strategy (LBMS) is adopted to lead the EV charging behavior. We find that the larger service capacity means that the load distribution is more balanced and the average user time is shorter. Furthermore, we find the optimal service capacity of the power grid. When the service capacity is more than that, it will no longer improve the system performance and cause the waste of charging facilities.

The Central American Power System: Achievements, Challenges, and Opportunities for a Green Transition

Over the past few decades, Central American countries have seen a steady increase in their energy needs. Luckily, the region has abundant renewable energy resources and, as a result, has been busy constructing wind and photovoltaic power facilities. However, while these renewable sources are promising, they come with some risks—mainly, their variable power generation can pose a challenge to the interconnected regional system. This paper explores the current state of the Central American power system and the obstacles it faces as it strives to transition to a more environmentally-friendly energy system. To do so, the authors employed power flow analysis and transient stability studies, which were conducted using ETAP (Electrical Transient Analyzer Program) to model and simulate the power system. Their study revealed that the Central American power system is at risk of instability, and they suggest that integrating ancillary services and storage solutions could strengthen its resilience. Additionally, the authors advocate for the development of microgrids, energy management, and sustainable decarbonization plans. Lastly, the authors emphasize the importance of short-, medium-, and long-term power planning to make better decisions.

Power Distribution System Outage Management Using Improved Resilience Metrics for Smart Grid Applications

Smart grid systems play a significant role in improving the resilience of distribution systems (DSs). In this paper, two strategies are proposed for implementation of a smart grid application: (a) a network reconfiguration and (b) a network reconfiguration with mobile emergency generator (MEGs) deployment. An improved set of resilience metrics to quantify and enhance the resiliency of distribution systems (DSs) is developed for the proposed optimization. The metrics aim to determine a suitable strategy and the optimal number and capacity of MEGs to restore the disconnected loads through the development of several microgrids. These metrics are then aggregated with the proposed strategy to develop an automated solution provider. The objective is to maximize system resilience considering the priority loads. The proposed resilience metrics are tested on the IEEE 33-Bus radial DSs. The case studies conducted proved the performance of the proposed power outage management strategy and resilience metrics in maximizing system resiliency for smart grids.

Robust Controller for Community Microgrids for Stability Improvement in Islanded Mode

Many utilities are developing microgrids to improve power reliability and grid resiliency for customers. One critical challenge in microgrid design is maintaining system stability with changing operating conditions in the microgrid. The technical and contractual constraints of accessibility and controllability to customer-owned resources limit available control options. This paper details a single-phase community microgrid model and illustrates the stability challenges. It further proposes adopting an optimal controller using predictive current control (PCC) and robust control mu-synthesis to improve microgrid stability in islanded operating mode. Incorporating the mu-synthesis in the controller design assures the microgrid's robust stability. The proposed method facilitates the incorporation of main uncertainties in the microgrid: change in resources, uncertainties in their modeling, and load variation. The proposed method overcomes the constraints and does not impact the customer's resources normal operation. Furthermore, the controller has a simple structure and is easy to implement. The simulation results validate that the designed controller can maintain the system stability and achieve optimal performance against various changes in the microgrid. This paper presents a practical solution to the challenges utilities are facing in microgrid development.

Multi-timescale scheduling strategy for multi-microgrids with accelerated alternating direction method of multipliers and stochastic model predictive control

The superiorities of renewable energy, such as wind and solar energy, have promoted the development of microgrids (MGs) and multi-microgrids (MMGs). However, how to coordinate the scheduling and transactions of MMGs with multi-timescale is still an important issue. This paper presents a scheduling and trading strategy of MMGs with two time-scales: day-ahead and intra-day. In the day-ahead scheduling stage, a MMG system with peer-to-peer connection is considered. Based on the idea of distributed updating parameters and adaptive selecting values in Alternating Direction Method of Multipliers (ADMM), an accelerated ADMM algorithm named improved adaptive accelerated ADMM (IAA-ADMM) is proposed, which is modeled and solved in a distributed manner. In the intra-day scheduling stage, based on the day-ahead scheduling, this paper utilizes stochastic model predictive control (SMPC) to optimize the intra-day model, which helps address the uncertainties of wind, solar, and load forecasting. The effectiveness of the proposed approach is validated using numerical examples. The results show that the IAA-ADMM provides higher stability and faster convergence and facilitates easier implementation. The SMPC shows higher economic performance and has a higher application potential.

Quantum Deep Learning for Fast Switching of Full-Bridge Power Converters

With the qualitative development of DC microgrids, the usage of different loads with unique conditions and features is now possible in electric power grids. Due to the negative impedance features of some loads, which are called constant power loads (CPLs), the control of DC power converters faces huge challenges from a stability point of view. Despite the significant advances in semiconductors, there is no upgrade in the control of gate drivers to exploit all potential of power electronic systems. In this paper, quantum computations are incorporated into artificial intelligence (AI) to stabilize a full-bridge (FB) DC-DC boost converter feeding CPL. Aiming to improve the bus voltage stabilization of the FB DC-DC boost converter, a quantum deep reinforcement learning (QDRL) control methodology is developed. By defining a reward function according to the specification of the FB power converter, the desired performance and control objectives are fulfilled. The main task of QDRL is to adjust the control coefficients embedded in the feedback controller to suppress the negative impedance effect resulting from deploying the CPLs. By deploying the potential advantages of quantum fundamentals, the deep reinforcement learning improved by quantum specifications will not only enhance the performance of the DRL algorithm on conventional processes but also advance related research areas such as quantum computing and AI. Unlike the basic quantum theory, which requires real quantum hardware, QDRL can be executed on classic computers. To examine the feasibility of the QDRL scheme, hardware-in-the-loop (HiL) examinations are conducted using the OPAL-RT. The comparison of the proposed controller with the classic state-of-the-art methodologies reveals the superiority and feasibility of QDRL-based control schemes in both the transient and steady-state conditions to other schemes. Analysis using various performance criteria, including the integral absolute error (IAE), integral time absolute error (ITAE), mean absolute error (MAE), and root mean square error (RMSE), demonstrates the dynamic improvement of the proposed scheme over sliding mode control (approximately 50%) and proportional integral control (approximately 100%).

Modelling of microgrids to insure resource adequacy in the capacity market

AbstractThe penetration of renewable resources in distribution networks have led to the creation of a concept called microgrids. Microgrids act as a bus with the ability to control the amount of consumption and generation, from the viewpoint of system operator. If the amount of capacity that can be provided by microgrids is known, they can be effective in providing resource adequacy and the required capacity of the network. This paper contains two contributions. Modelling of capacity value of a microgrid that includes wind turbines, photovoltaic, non‐renewable generators, loads and batteries is the first innovation of this paper. Here, a capacity value model for microgrids is created for the first time. The application of microgrid capacity value model to a long‐term issue, such as ensuring resource adequacy in the capacity market, constitutes the second innovation of this paper. Consequently, there are two distinct innovations in this work. The presence of microgrids in the capacity market has increased competition and reduced costs, and on the other hand, it will help the microgrids development through their long‐term generation revenues. The proposed method has been tested on IEEE 57‐bus test system. Results have shown the efficiency of using microgrids in the capacity market.

Wind characteristics of Tamil Nadu coast towards development of microgrid - A case study for simulation of small scale hybrid wind and solar energy system

Wind's intermittent nature poses a considerable challenge for an effective microgrid design, particularly in “Island mode.” The objective of this research is to investigate the wind characteristics of a coastal location in Tamil Nadu, India, with a special emphasis on wind consistency, to establish a successful microgrid at the site. The research was based on wind data acquired from an 80 m high meteorological mast established in Manamelkudi, Pudukkottai District, Tamil Nadu, India, from January to December 2017. Based on the analysis, it is observed that, while being within the moderate wind potential regime, the region has a substantially stable wind pattern when compared to the in-land windy places. According to the assessment, the site is expected to effectively complement solar generation, with 74% of its wind generation occurring between 06:00 p.m. and 06:00 a.m. Considering the consistency of wind and the complementary nature of solar generation, the Manamelkudi location is considered to have promising potential for the development of microgrid systems using wind and solar hybrid power. The investigation demonstrated that the geography of the site plays a critical role in the consistent wind pattern of the Manamelkudi site.

Possibilities, Challenges, and Future Opportunities of Microgrids: A Review

Microgrids are an emerging technology that offers many benefits compared with traditional power grids, including increased reliability, reduced energy costs, improved energy security, environmental benefits, and increased flexibility. However, several challenges are associated with microgrid technology, including high capital costs, technical complexity, regulatory challenges, interconnection issues, maintenance, and operation requirements. Through an in-depth analysis of various research areas and technical aspects of microgrid development, this study aims to provide valuable insights into the strategies and technologies required to overcome these challenges. By assessing the current state of microgrid development in Pakistan and drawing lessons from international best practices, our research highlights the unique opportunities microgrids present for tackling energy poverty, reducing greenhouse gas emissions, and promoting sustainable economic growth. Ultimately, this research article contributes to the growing knowledge of microgrids and their role in addressing global sustainability issues. It offers practical recommendations for policymakers, industry stakeholders, and local communities in Pakistan and beyond.

Development of a DC Microgrid with Decentralized Production and Storage: From the Lab to Field Deployment in Rural Africa

Development of a DC Microgrid with Decentralized Production and Storage: From the Lab to Field Deployment in Rural Africa