A microgrid is a decentralized group of electricity sources and loads that normally operates connected to and synchronous with the traditional wide area synchronous grid (macrogrid), but can also disconnect to "island mode" and function autonomously as physical or economic conditions dictate. Microgrids are best served by local energy sources where power transmission and distribution from a major centralized energy source is too far and costly to execute. In this case the microgrid is also called an autonomous, stand-alone or isolated microgrid.
In this way, microgrids improve the security of supply within the microgrid cell, and can supply emergency power, changing between island and connected modes. They also offer an option for rural electrification in remote areas and on smaller geographical islands. As a controllable entity, a microgrid can effectively integrate various sources of distributed generation (DG), especially renewable energy sources (RES).
Control and protection are difficulties to microgrids, as all ancillary services for system stabilization must be generated within the microgrid and low short-circuit levels can be challenging for selective operation of the protection systems. A very important feature is also to provide multiple end-use needs simultaneously, such as heating, cooling, and electricity, since this allows energy carrier substitution and increased energy efficiency due to waste heat utilization for heating, domestic hot water, and cooling purposes (cross sectoral energy usage).
The United States Department of Energy Microgrid Exchange Group defines a microgrid as a group of interconnected loads and distributed energy resources (DERs) within clearly defined electrical boundaries that acts as a single controllable entity with respect to the grid. A microgrid can connect and disconnect from the grid to enable it to operate in both connected or island-mode.
The EU research project describes a microgrid as comprising Low-Voltage (LV) distribution systems with distributed energy resources (DERs) (microturbines, fuel cells, photovoltaics (PV), etc.), storage devices (batteries, flywheels) energy storage system and flexible loads. Such systems can operate either connected or disconnected from the main grid. The operation of microsources in the network can provide benefits to the overall system performance, if managed and coordinated efficiently.
Types of microgrids
Campus environment/institutional microgrids
Community microgrids can serve thousands of customers and support the penetration of local energy (electricity, heating, and cooling). In a community microgrid, some houses may have some renewable sources that can supply their demand as well as that of their neighbors within the same community. The community microgrid may also have a centralized or several distributed energy storages. Such microgrids can be in the form of an ac and dc microgrid coupled together through a bi-directional power electronic converter.
Remote off-grid microgrids
These microgrids never connect to the macrogrid and instead operate in an island mode at all times because of economic issues or geographical position. Typically, an "off-grid" microgrid is built in areas that are far distant from any transmission and distribution infrastructure and, therefore, have no connection to the utility grid. Studies have demonstrated that operating a remote area or islands' off-grid microgrids, that are dominated by renewable sources, will reduce the levelized cost of electricity production over the life of such microgrid projects.
Large remote areas may be supplied by several independent microgrids, each with a different owner (operator). Although such microgrids are traditionally designed to be energy self-sufficient, intermittent renewable sources and their unexpected and sharp variations can cause unexpected power shortfall or excessive generation in those microgrids. This will immediately cause unacceptable voltage or frequency deviation in the microgrids. To remedy such situations, it is possible to interconnect such microgrids provisionally to a suitable neighboring microgrid to exchange power and improve the voltage and frequency deviations. This can be achieved through a power electronics-based switch after a proper synchronization or a back to back connection of two power electronic converters and after confirming the stability of the new system. The determination of a need to interconnect neighboring microgrids and finding the suitable microgrid to couple with can be achieved through optimization or decision making approaches.
Military base microgrids
Commercial and industrial (C&I) microgrids
These types of microgrids are maturing quickly in North America and eastern Asia; however, the lack of well–known standards for these types of microgrids limits them globally. Main reasons for the installation of an industrial microgrid are power supply security and its reliability. There are many manufacturing processes in which an interruption of the power supply may cause high revenue losses and long start-up time. Industrial microgrids can be designed to supply circular economy (near-)zero-emission industrial processes, and can integrate combined heat and power (CHP) generation, being fed by both renewable sources and waste processing; energy storage can be additionally used to optimize the operations of these sub-systems.
Basic components in microgrids
A microgrid presents various types of generation sources that feed electricity, heating, and cooling to the user. These sources are divided into two major groups – thermal energy sources (e.g,. natural gas or biogas generators or micro combined heat and power) and renewable generation sources (e.g. wind turbines and solar).
In a microgrid, consumption simply refers to elements that consume electricity, heat, and cooling, which range from single devices to the lighting and heating systems of buildings, commercial centers, etc. In the case of controllable loads, electricity consumption can be modified according to the demands of the network.
In microgrid, energy storage is able to perform multiple functions, such as ensuring power quality, including frequency and voltage regulation, smoothing the output of renewable energy sources, providing backup power for the system and playing a crucial role in cost optimization. It includes all of chemical, electrical, pressure, gravitational, flywheel, and heat storage technologies. When multiple energy storages with various capacities are available in a microgrid, it is preferred to coordinate their charging and discharging such that a smaller energy storage does not discharge faster than those with larger capacities. Likewise, it is preferred a smaller one does not get fully charged before those with larger capacities. This can be achieved under a coordinated control of energy storages based on their state of charge. If multiple energy storage systems (possibly working on different technologies) are used and they are controlled by a unique supervising unit (an energy management system - EMS), a hierarchical control based on a master/slaves architecture can ensure best operations, particularly in the islanded mode.
Point of common coupling (PCC)
This is the point in the electric circuit where a microgrid is connected to a main grid. Microgrids that do not have a PCC are called isolated microgrids which are usually present in remote sites (e.g., remote communities or remote industrial sites) where an interconnection with the main grid is not feasible due to either technical or economic constraints.
Advantages and challenges of microgrids
A microgrid is capable of operating in grid-connected and stand-alone modes and of handling the transition between the two. In the grid-connected mode, ancillary services can be provided by trading activity between the microgrid and the main grid. Other possible revenue streams exist. In the islanded mode, the real and reactive power generated within the microgrid, including that provided by the energy storage system, should be in balance with the demand of local loads. Microgrids offer an option to balance the need to reduce carbon emissions with continuing to provide reliable electric energy in periods of time when renewable sources of power are not available. Microgrids also offer the security of being hardened from severe weather and natural disasters by not having large assets and miles of above-ground wires and other electric infrastructure that need to be maintained or repaired following such events.
A microgrid may transition between these two modes because of scheduled maintenance, degraded power quality or a shortage in the host grid, faults in the local grid, or for economical reasons. By means of modifying energy flow through microgrid components, microgrids facilitate the integration of renewable energy, such as photovoltaic, wind and fuel cell generations, without requiring re-design of the national distribution system. Modern optimization methods can also be incorporated into the microgrid energy management system to improve efficiency, economics, and resiliency.
Microgrids, and the integration of DER units in general, introduce a number of operational challenges that need to be addressed in the design of control and protection systems, in order to ensure that the present levels of reliability are not significantly affected, and the potential benefits of Distributed Generation (DG) units are fully harnessed. Some of these challenges arise from assumptions typically applied to conventional distribution systems that are no longer valid, while others are the result of stability issues formerly observed only at a transmission system level. The most relevant challenges in microgrid protection and control include:
- Bidirectional power flows: The presence of distributed generation (DG) units in the network at low voltage levels can cause reverse power flows that may lead to complications in protection coordination, undesirable power flow patterns, fault current distribution, and voltage control.
- Stability issues: Interactions between control system of DG units may create local oscillations, requiring a thorough small-disturbance stability analysis. Moreover, transition activities between the grid-connected and islanding (stand-alone) modes of operation in a microgrid can create transient instability. Recent studies have shown that direct-current (DC) microgrid interface can result in a significantly simpler control structure, more energy efficient distribution and higher current carrying capacity for the same line ratings.
- Modeling: Many characteristics of traditional schemes such as the prevalence of three-phase balanced conditions, primarily inductive transmission lines, and constant-power loads, do not necessarily hold true for microgrids, and consequently, models need to be revised.
- Low inertia: Microgrids exhibit a low-inertia characteristic that makes them different to bulk power systems, where a large number of synchronous generators ensures a relatively large inertia. This phenomenon is more evident if there is a significant proportion of power electronic-interfaced DG units in the microgrid. The low inertia in the system can lead to severe frequency deviations in island mode operation if a proper control mechanism is not implemented. Synchronous generators run at the same frequency as the grid, thus providing a natural damping effect on sudden frequency variations. Synchronverters are inverters which mimic synchronous generators to provide frequency control. Other options include controlling battery energy storage or a flywheel to balance the frequency.
- Uncertainty: The operation of microgrids involves addressing much uncertainty, which is something the economical and reliable operation of microgrids relies on. Load profile and weather are two uncertainties that make this coordination more challenging in isolated microgrids, where the critical demand-supply balance and typically higher component failure rates require solving a strongly coupled problem over an extended time horizon. This uncertainty is higher than those in bulk power systems, due to the reduced number of loads and highly correlated variations of available energy resources (the averaging effect is much more limited).
To plan and install microgrids correctly, engineering modelling is needed. Multiple simulation tools and optimization tools exist to model the economic and electric effects of microgrids. A widely used economic optimization tool is the Distributed Energy Resources Customer Adoption Model (DER-CAM) from Lawrence Berkeley National Laboratory. Another is Homer Energy, originally designed by the National Renewable Energy Laboratory. There are also some power flow and electrical design tools guiding microgrid developers. The Pacific Northwest National Laboratory designed the publicly available GridLAB-D tool and the Electric Power Research Institute (EPRI) designed OpenDSS. A European tool that can be used for electrical, cooling, heating, and process heat demand simulation is EnergyPLAN from Aalborg University in Denmark. The open source grid planning tool OnSSET has been deployed to investigate microgrids using a three‑tier analysis beginning with settlement archetypes (case‑studied using Bolivia).
In regards to the architecture of microgrid control, or any control problem, there are two different approaches that can be identified: centralized and decentralized. A fully centralized control relies on a large amount of information transmittence between involving units before a decision is made at a single point. Implementation is difficult since interconnected power systems usually cover extended geographic locations and involve an enormous number of units. On the other hand, in a fully decentralized control, each unit is controlled by its local controller without knowing the situation of others. A compromise between those two extreme control schemes can be achieved by means of a hierarchical control scheme consisting of three control levels: primary, secondary, and tertiary.
The primary control is designed to satisfy the following requirements:
- To stabilize the voltage and frequency
- To offer plug and play capability for DERs and properly share the active and reactive power among them, preferably, without any communication links
- To mitigate circulating currents that can cause over-current phenomenon in the power electronic devices
The primary control provides the setpoints for a lower controller which are the voltage and current control loops of DERs. These inner control loops are commonly referred to as zero-level control.
Secondary control has typically seconds to minutes sampling time (i.e. slower than the previous one) which justifies the decoupled dynamics of the primary and the secondary control loops and facilitates their individual designs. The setpoint of primary control is given by secondary control in which, as a centralized controller, it restores the microgrid voltage and frequency and compensates for the deviations caused by variations of loads or renewable sources. The secondary control can also be designed to satisfy the power quality requirements, e.g., voltage balancing at critical buses.
Tertiary control is the last (and the slowest) control level, which considers economical concerns in the optimal operation of the microgrid (sampling time is from minutes to hours), and manages the power flow between microgrid and main grid. This level often involves the prediction of weather, grid tariff, and loads in the next hours or day to design a generator dispatch plan that achieves economic savings. More advanced techniques can also provide end to end control of a microgrid using machine learning techniques such as deep reinforcement learning.
In case of emergencies such as blackouts, tertiary control can manage a group of interconnected microgrids to form what is called "microgrid clustering", acting as a virtual power plant to continue supplying critical loads. During these situations the central controller should select one of the microgrids to be the slack (i.e. master) and the rest as PV and load buses according to a predefined algorithm and the existing conditions of the system (i.e. demand and generation). In this case, the control should be real time or at least at a high sampling rate.
A less utility-influenced controller framework is that from the Institute of Electrical and Electronics Engineers, the IEEE 2030.7. The concept relies on 4 blocks: a) Device level control (e.g. voltage and frequency control), b) Local area control (e.g. data communication), c) Supervisory (software) control (e.g. forward looking dispatch optimization of generation and load resources), and d) Grid layers (e.g. communication with utility).
A wide variety of complex control algorithms exist, making it difficult for small microgrids and residential distributed energy resource (DER) users to implement energy management and control systems. Communication upgrades and data information systems can be expensive. Some projects try to simplify and reduce the expense of control via off-the-shelf products (e.g. using a Raspberry Pi).
Hajjah and Lahj, Yemen
The UNDP project “Enhanced Rural Resilience in Yemen” (ERRY) uses community-owned solar microgrids. It cuts energy costs to just 2 cents per hour (whereas diesel-generated electricity costs 42 cents per hour). It won the Ashden Awards for Humanitarian Energy in 2020.
A two year pilot program, called Harmon’Yeu, was initiated in the Spring of 2020 to interconnect 23 houses in the Ker Pissot neighborhood and surrounding areas with a microgrid that was automated as a smart grid with software from Engie. Sixty-four solar panels with a peak capacity of 23.7 kW were installed on five houses and a battery with a storage capacity of 15 kWh was installed on one house. Six houses store excess solar energy in their hot water heaters. A dynamic system apportions the energy provided by the solar panels and stored in the battery and hot water heaters to the system of 23 houses. The smart grid software dynamically updates energy supply and demand in 5 minute intervals, deciding whether to pull energy from the battery or from the panels and when to store it in the hot water heaters. This pilot program was the first such project in France.
Les Anglais, Haiti
A wirelessly managed microgrid is deployed in rural Les Anglais, Haiti. The system consists of a three-tiered architecture with a cloud-based monitoring and control service, a local embedded gateway infrastructure and a mesh network of wireless smart meters deployed at fifty-two buildings.
Non-technical loss (NTL) represents a major challenge when providing reliable electrical service in developing countries, where it often accounts for 11-15% of total generation capacity. An extensive data-driven simulation on seventy-two days of wireless meter data from a 430-home microgrid deployed in Les Anglais investigated how to distinguish NTL from the total power losses, aiding in energy theft detection.
The Mpeketoni Electricity Project, a community-based diesel-powered micro-grid system, was set up in rural Kenya near Mpeketoni. Due to the installment of these microgrids, Mpeketoni has seen a large growth in its infrastructure. Such growth includes increased productivity per worker, at values of 100% to 200%, and an income level increase of 20–70% depending on the product.
Stone Edge Farm Winery
- 100% renewable energy
- Cogeneration (combined heat and power -- CHP)
- Demand response
- Distributed generation
- Electricity generation
- Electrical grid
- Energy storage
- Flywheel energy storage
- Grid connection
- Peak shaving
- Renewable energy development
- Renewable energy
- Vehicle-to-grid (V2G)
- Wind power
- "microgrid". Electropedia. International Electrotechnical Commission. 2017-12-15. Retrieved 2020-10-06.
group of interconnected loads and distributed energy resources with defined electrical boundaries forming a local electric power system at distribution voltage levels, that acts as a single controllable entity and is able to operate in either grid-connected or island mode"
- Hu, J.; Bhowmick, P. (2020). "A consensus-based robust secondary voltage and frequency control scheme for islanded microgrids". International Journal of Electrical Power & Energy Systems. 116: 105575.
- "About Microgrids".
- Hu, J.; Lanzon, A. (2019). "Distributed finite-time consensus control for heterogeneous battery energy storage systems in droop-controlled microgrids". IEEE Transactions on Smart Grid. 10 (5): 4751–4761.
- "isolated microgrid". Electropedia. International Electrotechnical Commission. 2017-12-15. Retrieved 2020-10-06.
group of interconnected loads and distributed energy resources with defined electrical boundaries forming a local electric power system at distribution voltage levels, that cannot be connected to a wider electric power system
- "A Survey of Techniques for Designing and Managing Microgrids", IEEE PES GM 2015
- "Features and Benefits - Microgrids". www.districtenergy.org. Retrieved 2018-06-28.
- "DOE Microgrid Workshop Report" (PDF).
- Hatziargyriou, Nikos (2014). Microgrids Architectures and Control. John Wiley and Sons Ltd. p. 4. ISBN 978-1-118-72068-4.
- Ernie Hayden. "Introduction to Microgrids" (PDF). Archived from the original (PDF) on 19 February 2018. Retrieved 20 June 2016. CS1 maint: discouraged parameter (link)
- Saleh, Mahmoud; Esa, Yusef; Mhandi, Yassine; Brandauer, Werner; Mohamed, Ahmed (2016). "Design and implementation of CCNY DC microgrid testbed". 2016 IEEE Industry Applications Society Annual Meeting. pp. 1–7. doi:10.1109/IAS.2016.7731870. ISBN 978-1-4799-8397-1.
- Thomson, Greg (2018). "The Sonoma Community Microgrid Initiative" (PDF). Clean Coalition.
- Chandrasena, Ruwan P.S.; Shahnia, Farhad; Ghosh, Arindam; Rajakaruna, Sumedha (2015-08-06). "Dynamic operation and control of a hybrid nanogrid system for future community houses". IET Generation, Transmission & Distribution. 9 (11): 1168–1178. doi:10.1049/iet-gtd.2014.0462.
- "Design and Analyze Micro-Grids".
- Ali, Liaqat; Shahnia, Farhad (June 2017). "Determination of an economically-suitable and sustainable standalone power system for an off-grid town in Western Australia". Renewable Energy. 106: 243–254. doi:10.1016/j.renene.2016.12.088.
- Shahnia, Farhad; Moghbel, Moayed; Arefi, Ali; Shafiullah, G. M.; Anda, Martin; Vahidnia, Arash (2017). "Levelized cost of energy and cash flow for a hybrid solar-wind-diesel microgrid on Rottnest island". 2017 Australasian Universities Power Engineering Conference (AUPEC). pp. 1–6. doi:10.1109/aupec.2017.8282413. ISBN 9781538626474.
- Pashajavid, Ehsan; Shahnia, Farhad; Ghosh, Arindam (2015). "Development of a Self-Healing Strategy to Enhance the Overloading Resilience of Islanded Microgrids". IEEE Transactions on Smart Grid: 1. doi:10.1109/tsg.2015.2477601.
- Pashajavid, Ehsan; Shahnia, Farhad; Ghosh, Arindam (2017-01-05). "Provisional internal and external power exchange to support remote sustainable microgrids in the course of power deficiency". IET Generation, Transmission & Distribution. 11 (1): 246–260. doi:10.1049/iet-gtd.2016.0897.
- Pashajavid, Ehsan; Shahnia, Farhad; Ghosh, Arindam (2015). "Overload management of autonomous microgrids". 2015 IEEE 11th International Conference on Power Electronics and Drive Systems. pp. 73–78. doi:10.1109/peds.2015.7203515. ISBN 9781479944026.
- Pashajavid, Ehsan; Shahnia, Farhad; Ghosh, Arindam (2015). "Overloading conditions management in remote networks by coupling neighboring microgrids". 2015 50th International Universities Power Engineering Conference (UPEC). pp. 1–6. doi:10.1109/upec.2015.7339874. ISBN 9781467396820.
- Shahnia, Farhad; Bourbour, Soheil (September 2017). "A practical and intelligent technique for coupling multiple neighboring microgrids at the synchronization stage". Sustainable Energy, Grids and Networks. 11: 13–25. doi:10.1016/j.segan.2017.06.002.
- Susanto, Julius; Shahnia, Farhad; Ghosh, Arindam; Rajakaruna, Sumehda (2014). "Interconnected microgrids via back-to-back converters for dynamic frequency support". 2014 Australasian Universities Power Engineering Conference (AUPEC). pp. 1–6. doi:10.1109/aupec.2014.6966616. hdl:20.500.11937/40897. ISBN 9780646923758.
- Arefi, Ali; Shahnia, Farhad (2018). "Tertiary Controller-Based Optimal Voltage and Frequency Management Technique for Multi-Microgrid Systems of Large Remote Towns". IEEE Transactions on Smart Grid. 9 (6): 5962–5974. doi:10.1109/tsg.2017.2700054.
- Shahnia, Farhad; Bourbour, Soheil; Ghosh, Arindam (2015). "Coupling Neighboring Microgrids for Overload Management Based on Dynamic Multicriteria Decision-Making". IEEE Transactions on Smart Grid: 1. doi:10.1109/tsg.2015.2477845.
- Emily W. Prehoda; Chelsea Schelly; Joshua M. Pearce (2017). "U.S. Strategic Solar Photovoltaic-Powered Microgrid Deployment for Enhanced National Security". Renewable and Sustainable Energy Reviews. 78: 167–175. doi:10.1016/j.rser.2017.04.094. Retrieved 23 May 2017. CS1 maint: discouraged parameter (link)
- Guarnieri, Massimo; Bovo, Angelo; Giovannelli, Antonio; Mattavelli, Paolo (2018). "A Real Multitechnology Microgrid in Venice: A Design Review". IEEE Industrial Electronics Magazine. 12 (3): 19–31. doi:10.1109/MIE.2018.2855735. hdl:11577/3282913.
- Hosseinimehr, Tahoura; Ghosh, Arindam; Shahnia, Farhad (May 2017). "Cooperative control of battery energy storage systems in microgrids". International Journal of Electrical Power & Energy Systems. 87: 109–120. doi:10.1016/j.ijepes.2016.12.003.
- Alexis Kwasinki. "Grid-Microgrids Interconnection". Retrieved 20 June 2016. CS1 maint: discouraged parameter (link)
- Stadler, Michael; Cardoso, Gonçalo; Mashayekh, Salman; Forget, Thibault; DeForest, Nicholas; Agarwal, Ankit; Schönbein, Anna (2016). "Value streams in microgrids: A literature review". Applied Energy. 162: 980–989. doi:10.1016/j.apenergy.2015.10.081.
- Saleh, Mahmoud; Esa, Yusef; Mohamed, Ahmed A. (2019). "Communication-Based Control for DC Microgrids". IEEE Transactions on Smart Grid. 10 (2): 2180–2195. doi:10.1109/TSG.2018.2791361.
- Olivares, Daniel E.; Mehrizi-Sani, Ali; Etemadi, Amir H.; Canizares, Claudio A.; Iravani, Reza; Kazerani, Mehrdad; Hajimiragha, Amir H.; Gomis-Bellmunt, Oriol; Saeedifard, Maryam; Palma-Behnke, Rodrigo; Jimenez-Estevez, Guillermo A.; Hatziargyriou, Nikos D. (2014). "Trends in Microgrid Control". IEEE Transactions on Smart Grid. 5 (4): 1905–1919. doi:10.1109/TSG.2013.2295514.
- A. A. Salam, A. Mohamed and M. A. Hannan (2008). "Technical challenges on Microgrids". ARPN Journal of Engineering and Applied Sciences. 3: 64.
- F.D Kanellos; A.I. Tsouchnikas; N.D. Hatziargyriou. (June 2005). "Microgrid Simulation during Grid Connected and Islanded Modes of Operation". Proc. Of the Canada International Conference on Power System Transient (IPTS'05). 113: 19–23.
- Jin, Ming; Feng, Wei; Liu, Ping; Marnay, Chris; Spanos, Costas (2017-02-01). "MOD-DR: Microgrid optimal dispatch with demand response". Applied Energy. 187: 758–776. doi:10.1016/j.apenergy.2016.11.093.
- Tenti, Paolo; Caldognetto, Tommaso (2019). "On Microgrid Evolution to Local Area Energy Network (E-LAN)". IEEE Transactions on Smart Grid. 10 (2): 1567–1576. doi:10.1109/TSG.2017.2772327.
- Mashayekh, Salman; Stadler, Michael; Cardoso, Gonçalo; Heleno, Miguel (2017). "A mixed integer linear programming approach for optimal DER portfolio, sizing, and placement in multi-energy microgrids". Applied Energy. 187: 154–168. doi:10.1016/j.apenergy.2016.11.020.
- Saleh, Mahmoud S.; Althaibani, Ammar; Esa, Yusef; Mhandi, Yassine; Mohamed, Ahmed A. (2015). "Impact of clustering microgrids on their stability and resilience during blackouts". 2015 International Conference on Smart Grid and Clean Energy Technologies (ICSGCE). pp. 195–200. doi:10.1109/ICSGCE.2015.7454295. ISBN 978-1-4673-8732-3.
- Dragicevic, Tomislav; Lu, Xiaonan; Vasquez, Juan; Guerrero, Josep (2015). "DC Microgrids–Part I: A Review of Control Strategies and Stabilization Techniques" (PDF). IEEE Transactions on Power Electronics: 1. doi:10.1109/TPEL.2015.2478859.
- Dragicevic, Tomislav; Lu, Xiaonan; Vasquez, Juan C.; Guerrero, Josep M. (2016). "DC Microgrids—Part II: A Review of Power Architectures, Applications, and Standardization Issues". IEEE Transactions on Power Electronics. 31 (5): 3528–3549. Bibcode:2016ITPE...31.3528D. doi:10.1109/TPEL.2015.2464277.
- Kim, Yun-Su; Kim, Eung-Sang; Moon, Seung-Il (2016). "Frequency and Voltage Control Strategy of Standalone Microgrids with High Penetration of Intermittent Renewable Generation Systems". IEEE Transactions on Power Systems. 31 (1): 718–728. Bibcode:2016ITPSy..31..718K. doi:10.1109/TPWRS.2015.2407392.
- Peña Balderrama, JG; Balderrama Subieta, S; Lombardi, Francesco; Stevanato, N; Sahlberg, A; Howells, Mark; Colombo, E; Quoilin, Sylvain (1 June 2020). "Incorporating high-resolution demand and techno-economic optimization to evaluate micro-grids into the Open Source Spatial Electrification Tool (OnSSET)". Energy for Sustainable Development. 56: 98–118. doi:10.1016/j.esd.2020.02.009. ISSN 0973-0826. Retrieved 2021-02-19.
- Saleh, Mahmoud; Esa, Yusef; Mohamed, Ahmed (2017). "Hardware based testing of communication based control for DC microgrid". 2017 IEEE 6th International Conference on Renewable Energy Research and Applications (ICRERA). pp. 902–907. doi:10.1109/ICRERA.2017.8191190. ISBN 978-1-5386-2095-3.
- Pashajavid, Ehsan; Shahnia, Farhad; Ghosh, Arindam (2015). "A decentralized strategy to remedy the power deficiency in remote area microgrids". 2015 50th International Universities Power Engineering Conference (UPEC). pp. 1–6. doi:10.1109/upec.2015.7339865. ISBN 9781467396820.
- M. D. Ilić; S. X. Liu (1996). Hierarchical Power Systems Control: Its Value in a Changing Industry (Advances in Industrial Control). London: Springer.
- Shahnia, Farhad; Ghosh, Arindam; Rajakaruna, Sumedha; Chandrasena, Ruwan P.S. (2014-02-01). "Primary control level of parallel distributed energy resources converters in system of multiple interconnected autonomous microgrids within self-healing networks". IET Generation, Transmission & Distribution. 8 (2): 203–222. doi:10.1049/iet-gtd.2013.0126.
- Bidram, Ali; Davoudi, Ali (2012). "Hierarchical Structure of Microgrids Control System". IEEE Transactions on Smart Grid. 3 (4): 1963–1976. doi:10.1109/TSG.2012.2197425.
- Chandrasena, Ruwan P.S.; Shahnia, Farhad; Ghosh, Arindam; Rajakaruna, Sumedha (2014). "Secondary control in microgrids for dynamic power sharing and voltage/Frequency adjustment". 2014 Australasian Universities Power Engineering Conference (AUPEC). pp. 1–8. doi:10.1109/aupec.2014.6966619. hdl:20.500.11937/11871. ISBN 9780646923758.
- François-Lavet, Vincent; Taralla, David; Ernst, Damien; Fonteneau, Raphael. Deep reinforcement learning solutions for energy microgrids management. European Workshop on Reinforcement Learning (EWRL 2016).
- IEEE 2030.7
- Furst, Jonathan; Gawinowski, Nik; Buttrich, Sebastian; Bonnet, Philippe (2013). "COSMGrid: Configurable, off-the-shelf micro grid". 2013 IEEE Global Humanitarian Technology Conference (GHTC). pp. 96–101. doi:10.1109/GHTC.2013.6713662. ISBN 978-1-4799-2402-8.
- Stadler, Michael (2018). "A flexible low cost PV/EV microgrid controller concept based on a Raspberry Pi" (PDF). Center for Energy and innovative Technologies.
- UNDP Yemen wins acclaimed international Ashden Awards for Humanitarian Energy
- Joel Spaes (July 3, 2020). "Harmon'Yeu, première communauté énergétique à l'Île d'Yeu, signée Engie". www.pv-magazine.fr. Retrieved January 27, 2021. CS1 maint: discouraged parameter (link)
- Nabil Wakim (December 16, 2020). "A L'Ile-d'Yeu, soleil pour tous… ou presque". www.lemonde.fr. Retrieved January 27, 2021. CS1 maint: discouraged parameter (link)
- Buevich, Maxim; Schnitzer, Dan; Escalada, Tristan; Jacquiau-Chamski, Arthur; Rowe, Anthony (2014). "Fine-grained remote monitoring, control and pre-paid electrical service in rural microgrids". IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks. pp. 1–11. doi:10.1109/IPSN.2014.6846736. ISBN 978-1-4799-3146-0.
- "World Bank Report".
- Buevich, Maxim; Zhang, Xiao; Schnitzer, Dan; Escalada, Tristan; Jacquiau-Chamski, Arthur; Thacker, Jon; Rowe, Anthony (2015-01-01). "Short Paper: Microgrid Losses: When the Whole is Greater Than the Sum of Its Parts". Proceedings of the 2Nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments. BuildSys '15: 95–98. doi:10.1145/2821650.2821676. ISBN 9781450339810.
- Kirubi, et al. “Community-Based Electric Micro-Grids Can Contribute to Rural Development: Evidence from Kenya.” World Development, vol. 37, no. 7, 2009, pp. 1208–1221.
- "Microgrid at Stone Edge Farm Wins California Environmental Honor". Microgrid Knowledge. 2018-01-18. Retrieved 2018-06-28.
- "Stone Edge Farm — A Sandbox For Microgrid Development | CleanTechnica". cleantechnica.com. 2017-11-24. Retrieved 2018-06-28.