Community Microgrid Research Articles

Networked Microgrids: Exploring the Possibilities of the IIT-Bronzeville Grid

Bronzeville is a community located in the city of Chicago that features a diverse historic district with essential city services, residential housing, and educational institutions. The Bronzeville neighborhood houses the headquarters of the Chicago Police and Fire Department, De La Salle Institute, Illinois College of Optometry, Boulevard Care Center, Chicago Public Library, Pilgrim Baptist Church, Bronzeville Nursing and Living Center, Chicago Military Academy, Pentecostal Church, Perspectives Math & Science Academy, and other institutions. The area provides an ideal location for the continued refinement and development of advanced electric power services, which can be demonstrated through the implementation of a community microgrid: the Bronzeville community microgrid (BCM). The BCM is the backbone of a planned community of the future, where residents and critical facilities enjoy a sustainable environment and utilize innovative smart grid products. The BCM can serve as a pilot project for demonstrating the merits of instituting Chicago as a smart city. Distribution automation devices capable of fault interruption and sectionalization will be strategically deployed so that a fault would only result in a local outage rather than an interruption to the entire area. The BCM operation will comprise several types of distributed energy resources (DER s). A battery energy storage system (BESS) located in close proximity to photovoltaic panels provides an effective means to mitigate the variability of renewable energy. The BESS is also effective in improving the power quality at customer sites.

Optimal sizing of renewable energy generations in a community microgrid using Markov model

The installation of renewable energy generation resources (such as photovoltaic arrays and wind-turbine generators) in a microgrid is important because a microgrid can increase the penetration of renewable energies in a smart grid. A community may be a grid-tied microgrid in which an energy management system may dispatch elastic loads (such as air conditioning systems). This paper investigates the optimal sizing of renewable energy generation resources in a community microgrid. The cost of renewables and community welfare are optimized while the comfort zone of indoor temperature in all homes is maintained using air conditioning systems. Community welfare is ensured by minimizing the purchased power from and maximizing the sold power to the utility grid with different time-of-use electricity tariffs. Since the problem of interest involves a large number of variables and chronological constraints, Markov models of photovoltaic power generation, wind generation, load and temperature are utilized to reduce the numbers of variables and constraints. The Markov-based optimization problem is then solved using the interior-point algorithm. The simulation results, based on a smart community of 50 homes, reveal the applicability of the proposed method.

Optimal multiple microgrids based forming of greenfield distribution network under uncertainty

Multiple microgrid (MMG) operation concept of community microgrid (MG) provides enhanced resiliency and reliability through self-healing, enabling a high penetration of distributed generations (DGs), power interchange between MGs and real-time communication. In this study, the methodology of optimal design of low-voltage greenfield distribution grids based on multiple MGs in the presence of uncertainties is presented. The electrical and geographical borders of MGs community are determined using some important criteria such as power balance and spatial distribution of load. Within MGs, both of dispatchable and non-dispatchable DGs are considered. The external grid is assumed as a backup for each MG in abnormal conditions. The proposed method determines the optimal borders of MGs, optimal size and site of DGs for each autonomous MG simultaneously. The imperialist competitive algorithm is used to optimise the total cost of optimal MG clustering problem. The method is implemented to a vacant area with residential and commercial customers. The MGs optimal service area, DGs location, size and type within each MG and LV feeder's route are indicated and compared both for deterministic and probabilistic planning cases.

Achieving Resilience at Distribution Level: Learning from Isolated Community Microgrids

Increasing power system resilience at the distribution level is crucial due to the negative social impact of blackouts, as the undesired consequences get worse the longer the system restoration takes. Statistical records demonstrate that system recovery times after high-impact, low-probability events (e.g., earthquakes, tsunamis, and floods) are often faster for generation and transmission segments than for the distribution system. During the 2010 Chilean earthquake (8.8 Mw on the Richter scale), for example, the distribution system in the most affected area (almost 1.1 million customers) was not totally back in service until two weeks after the first major seismic event. In contrast, the transmission system rapidly recovered, with most of the bulk system buses re-energized by the end of the first day and the remainder during the second day. Additional installed generation capacity and repairing minor damage to most of the affected generation plants allowed for the recovery of most of the supply within a few days. Only 6.1% of the installed generation capacity required major repairs (which took up to six months to complete).

Optimal Interconnection Planning of Community Microgrids With Renewable Energy Sources

The optimal planning of the interconnected network of multimicrogrids is discussed in this paper. The interconnection planning will enhance the reliability and the economic operation of a community of microgrids. The proposed approach will apply a probabilistic minimal cut-set-based iterative methodology for the optimal planning of interconnection among microgrids with variable renewable energy sources. The optimal planning takes into account various factors including the economics, reliability, and variability of renewables, network- and resource-based uncertainties, and adaptability to accommodate the prevailing operating concerns. A clustering-based method is considered for analyzing the variable data concerning the potential deployment of renewable energy in microgrids. The proposed interconnection planning methodology is applied to a six-microgrid system and the planning results are discussed. The numerical results demonstrate that the proposed interconnection planning methodology will determine an optimal topology accurately and efficiently for a cluster of microgrids, and show that the proposed adaptive planning methodology can easily be applied to practical microgrid applications.

Techno-economic, environmental, and safety assessment of hydrogen powered community microgrids; case study in Canada

This paper proposes a comprehensive design of a renewable hydrogen powered microgrid that can provide backup power to a community in Cornwall, Ontario when disconnected from the power grid. The work employs the implementation of the energy hub concept to optimally design and operate energy generation systems to meet energy loads of a community. Solar PVs, wind turbines, electrolysers, hydrogen tanks, fuel cells and fuel cell vehicles are considered as the components that make up the entire system providing energy within the community. Failure mode and effect analysis (FMEA) is done to assess the safety of hydrogen based microgrid.The major load centers include a fresh food distribution center and a residential complex, where the peak demand is ∼5410 kW. The results of a mixed integer linear programming optimization problem show that a renewable energy generation system size of 2000 kW (400 kW-solar Photovoltaic and 1600 kW-wind turbine) is required. In addition to this, a backup fuel cell generation system of 3000 kW is also needed for the two-day blackout period. One of the positive attributes of implementing vehicle to grid services during islanded operation mode is that it enables the community to offset investment in fuel cell backup generation capacity by 1000 kW. Thirty-eight Toyota Mirai have been used to provide the vehicle to grid service. Due to the scale of the system, it is observed that even after proposing the use of existing market pricing mechanisms for the services offered by the microgrid, the energy system does not have a positive net present value at the end of its project life. Therefore, further economic incentives in the form of bundling costs need to be sanctioned for cleaner microgrid energy systems to be developed. This submission was the Grand Prize Winner of the Hydrogen Education Foundation's 2016 Hydrogen Student Design Contest.

Optimal siting and sizing of tri-generation equipment for developing an autonomous community microgrid considering uncertainties

Community microgrids are central pillars of the modern clean and efficient infrastructures, due to their deployment in municipalities. Community energy mangers are responsible for fulfilling the energy demands of inhabitants, especially during outages of the main grid. Determination of optimal sizes of generation sources and optimal site for deployment of these sources is a key issue. Therefore, in this paper, development of an autonomous community microgrid is suggested through optimal sizing and siting of tri-generation equipment. Total network losses (thermal and electrical) for different seasons of the year are considered for determining the optimal site of the energy hub. Thermal losses are computed through modified Dijkstra algorithm and electrical losses are computed by using exact loss formula. Worst-case realization of uncertainties associated with energy demands (cooling, heat, and power) are considered for optimal sizing of tri-generation equipment to fulfil the load demands of community microgrid throughout the year. Final sizes of tri-generation equipment are determined through worst-case realization of uncertainties associated with renewable energy sources. Particle swarm optimization (PSO) is used for both sizing and siting of tri-generation equipment in the community microgrid. Standard IEEE 33-bus distribution system is transformed into a sustainable community microgrid by placing the optimally sized energy hub at the optimal location determined by PSO.

Optimal economic operation of isolated community microgrid incorporating temperature controlling devices

With the increasing connection of controllable devices to isolated community microgrid, an economic operation model of isolated community microgrid based on the temperature regulation characteristics of temperature controlling devices composed of wind turbine, micro-gas turbine, energy storage battery and heat pump is proposed. With full consideration of various economic costs, including fuel cost, start-stop cost, energy storage battery depletion expense and penalty for wind curtailment, the model is solved by hybrid particle swarm optimization (HPSO) algorithm. The optimal output of the micro-sources and total operating cost of the system in the scheduling cycle are also obtained. The case study demonstrates that temperature adjustment of temperature controlling devices can adjust the power load indirectly and increase the schedulability of the isolated community microgrid, and reduce the operating cost of the microgrid.

Multilayered Protection Strategy for Developing Community Microgrids in Village Distribution Systems

Village or community microgrids are being encouraged to improve resiliency against unexpected events. They also improve energy efficiency and reliability of power delivery to critical loads. However, many protection challenges exist in making the shift away from conventional distribution systems. In this paper, a multilayered protection strategy is presented for developing a community microgrid in a village within the 69-bus distribution system. The proposed strategy is verified by simulation studies in MATLAB/Simulink against various fault conditions. A comparison between the proposed strategy and existing distribution protection schemes is also provided.

Agent-based modelling of coalition formation in energy micro-grids

In micro-grids energy is generated and consumed locally from intermittent renewable energy sources. Because of energy variability, sometimes there are energy surpluses and sometimes deficits. The ill effects of intermittency can be reduced by trading energy by means of a connected electricity grid. This work introduces an alternative solution by forming coalitions among micro-grid communities, since mainline electricity grids are subject to faults and outages. These coalitions can withstand power outages by sharing energy among them. We present a model for dynamic micro-grid coalition formation and demonstrate that the model is scalable and preserves the autonomy of individual micro-grids by enabling them to join and depart from a coalition. Our empirical studies demonstrate that our model reduces overall 'discomfort' (a notion defined in the paper), so that even when all participating micro-grids in a coalition experience deficits, they can share energy so that their overall discomfort is minimised.

Agent-based modelling of coalition formation in energy micro-grids

In micro-grids energy is generated and consumed locally from intermittent renewable energy sources. Because of energy variability, sometimes there are energy surpluses and sometimes deficits. The ill effects of intermittency can be reduced by trading energy by means of a connected electricity grid. This work introduces an alternative solution by forming coalitions among micro-grid communities, since mainline electricity grids are subject to faults and outages. These coalitions can withstand power outages by sharing energy among them. We present a model for dynamic micro-grid coalition formation and demonstrate that the model is scalable and preserves the autonomy of individual micro-grids by enabling them to join and depart from a coalition. Our empirical studies demonstrate that our model reduces overall 'discomfort' (a notion defined in the paper), so that even when all participating micro-grids in a coalition experience deficits, they can share energy so that their overall discomfort is minimised.

The community microgrid distribution system of the future

There is a recognized need for community microgrids to serve multiple electricity customers in the event of long-term unavailability of the main power grid. Community microgrids connect critical loads and distributed energy resources of multiple owners, thereby presenting significant new design goals, operating constraints and business models.

A Smart Pool Search Matheuristic for Solving a Multi-objective Microgrid Storage Planning Problem

Abstract In this paper, a multi-objective power dispatching problem that uses Plug-in Electric Vehicle (PEV) as storage units is considered. The problem involves several PEVs and a microgrid community, composed of small houses, residential areas, and different Renewable Energy Resources. Three different objectives are considered: microgrid total costs; usage of PEV batteries and maximum grid peak load. In order to find sets of non-dominated solutions, a matheuristic black box solves several Mixed Integer Linear Programming (MILP) subproblems. We improve a previously developed MILP model and design a new multi-objective matheuristic including new problem initialization mechanisms.

Fuel cell cars in a microgrid for synergies between hydrogen and electricity networks

Fuel cell electric vehicles convert chemical energy of hydrogen into electricity to power their motor. Since cars are used for transport only during a small part of the time, energy stored in the on-board hydrogen tanks of fuel cell vehicles can be used to provide power when cars are parked. In this paper, we present a community microgrid with photovoltaic systems, wind turbines, and fuel cell electric vehicles that are used to provide vehicle-to-grid power when renewable power generation is scarce. Excess renewable power generation is used to produce hydrogen, which is stored in a refilling station. A central control system is designed to operate the system in such a way that the operational costs are minimized. To this end, a hybrid model for the system is derived, in which both the characteristics of the fuel cell vehicles and their traveling schedules are considered. The operational costs of the system are formulated considering the presence of uncertainty in the prediction of the load and renewable energy generation. A robust min-max model predictive control scheme is developed and finally, a case study illustrates the performance of the designed system.

Development and application of a model‐based collaborative analysis and design framework for microgrid power systems

Microgrids have been recognised as essential components of the smart grid. However, recent advances on communication, control, and other intelligent techniques have also significantly increased the design complexity of the microgrids. This calls for attention for the microgrid community to be aware of the latest design challenges and develop visionary approaches to re-evaluate the legacy power system design concepts and analysis tools that are currently utilised for microgrid studies. This study proposes a novel model-based analysis and design framework tailored specifically for microgrids based on the concept of model-integrated computing. The proposed framework aims to provide a flexible and extensible integrated environment to facilitate rapid modelling and simulation of microgrids as well as the implementation of other control, analysis, and microgrid design applications. In this study, the authors focus on demonstrating and examining how the adoption of the proposed framework can effectively reduce the duration and costs of the design process, enhance the experience of the end-users, and improve the overall quality and efficiency of the microgrid study activities. Case studies under various microgrid operating scenarios are presented to validate the effectiveness of the proposed framework.

Economic Dispatch for an Agent-Based Community Microgrid

In this paper, an economic dispatch (ED) problem for a community microgrid is studied. In this microgrid, each agent pursues an ED for its personal resources. In addition, each agent is capable of trading electricity with other agents through a local energy market. In this paper, an energy market operating in the presence of the grid is introduced. The proposed market is mainly developed for an experimental community microgrid at the Missouri University of Science and Technology, Rolla, MO, USA, and can be applied to other distribution level microgrids. To develop the algorithm, first, the microgrid is modeled and a dynamic ED algorithm for each agent is developed. Afterwards, an algorithm for handling the market is introduced. Lastly, simulation results are provided to demonstrate the proposed community market, and show the effectiveness of the market in reducing the operation costs of passive and active agents.

A Hierarchical Energy Management System Based on Hierarchical Optimization for Microgrid Community Economic Operation

In view of the merits and promising applications of microgrid community (MGC), this paper presents a two-level hierarchical optimization method for MGC’s energy management system in smart grid environment. The lower level focuses on an individual microgrid (MG), and the upper level is responsible for managing the MGs and MG community level devices (MCLDs). It is executed consecutively from lower level to upper level in order to minimize operational costs. First, the lower level optimizes the power output of MGs generators, the charge/discharge power of energy storage system, and the exchanged power with upstream grid. The results of the lower level are transferred to the upper level as its constraints. Second, the upper level makes decisions about MCLDs’ powers and the exchanged power between distribution networks based on results from the lower level while ignoring any internal constituents of MG. The model is built in ways that nonlinearity is removed by linearization approximation and nonconvexity is removed by adding implicit logic constraints. A case study based on a real system in South China’s Guangxi Province is analyzed. The results demonstrate the effectiveness of the method. Of the four scenarios tested, two are proved cost-effective and are recommended for MGC operation.

A three-phase community microgrid comprised of single-phase energy resources with an uneven scattering amongst phases

This paper considers a three-phase, low voltage community network with both grid-connected and autonomous modes of operation, which is composed of a group of residential houses and some single-phase, converter-interfaced distributed energy resources (DER) with equal and arbitrarily scattering of the DERs among the phases. The vigorous operation of such a microgrid system is examined with the proposed management techniques. In such a network, it is highly probable for one phase to have a high generation capacity while the other phases experience a higher demand; a technically challenging problem for a network operating in autonomous mode. In this paper, it is proposed for the single-phase DERs of such a system to operate under a droop-based voltage control technique while an appropriate technique is proposed to facilitate the transmission of the excess power from one phase to other phases. The proposals are validated by extensive digital simulations in PSCAD/EMTDC for several scenarios to demonstrate the feasibility of operating such a system and the efficacy of the proposed techniques.

Robust economic model predictive control of a community micro-grid

In this paper we propose a novel economic robust predictive controller for periodic operation. The proposed controller joins dynamic and economic trajectory planning and robust predictive controller for tracking in a single layer taking into account bounded disturbances, algebraic constraints and periodic operation. We study the closed-loop system properties of the proposed controller and provide a design procedure that guarantees that the perturbed closed-loop system converges asymptotically to the optimal economic reachable periodic trajectory, constraint satisfaction and recursive feasibility. The proposed controller has been applied to control a cluster of interconnected micro-grids. Each nano-grid is connected to an electric utility and has a renewable energy source, a cluster of batteries and a metal hydride based hydrogen storage system. The cluster must satisfy a periodic energy demand while maximizing the profit of the energy sold to the electric utility taking into account time varying prices.

The key technologies and analysis of research state of microgrid community

Microgrid (MG) based on renewable energy source (RES) is an important component of the energy development strategy in China. Microgrid community (MGC) is a new product that has resulted from the development of MG and has reached a critical stage. In China, research on MGC currently remains at an early stage. This paper focuses on an analysis of the concept and characteristics of MGC as well as the key technologies involved in it. In addition, this paper discusses the research progress and achievement of the first MGC demonstration project in China—key technologies and a demonstration of the efficient and reliable operation of it. Finally, this paper provides an outlook on the further development and construction of MGC throughout China.