Microgrids For Boston’s Critical Infrastructure: Ensuring Resilience And Profitability – An insight into the integration of distributed energy resources and energy storage systems with smart distribution grids using demand-side management

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Microgrids For Boston’s Critical Infrastructure: Ensuring Resilience And Profitability

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Boston’s Energy Ecosystem: Microgrids And The Value Of District Energy

Department of Informatics and Networked Systems, School of Computing and Information, University of Pittsburgh, Pittsburgh, PA 15213, USA

Received: 21 August 2022 / Revised: 21 September 2022 / Accepted: 26 September 2022 / Published: 28 September 2022

Microgrids have the potential to provide reliable electricity to key elements of a smart city’s critical infrastructure after a disaster, thereby enhancing the resilience of the microgrid electricity system. Policymakers and power grid operators are increasingly concerned about the appropriate configuration and location of microgrids to maintain critical post-disaster infrastructure functions in smart cities. In this context, this paper presents a new method for the microgrid allocation problem that takes into account several technical and economic infrastructure factors such as critical infrastructure components, geospatial location of infrastructures, power requirements and microgrid costs. Specifically, the geographic distribution of a microgrid is presented as an optimization problem for optimizing a weighted combination of the relative importance of nodes across all key infrastructures and the associated costs. In addition, the simulation results of the formulated optimization problem are compared with a modified version of the heuristic method based on critical node identification of an interdependent infrastructure for microgrid placement in terms of resilience of multiple smart critical infrastructures. Numerical results using infrastructure in the city of Pittsburgh, USA. are given as a practical case study to illustrate the methodology and trade-offs. The proposed method provides an efficient method to identify renewable energy sources based on infrastructure requirements.

The proportion of the world’s population residing in an urban environment has increased over the past decade from approximately 33% to 55% [1]. This growth has created enormous demand and pressure on the infrastructure and systems that provide essential city services, resulting in significant interest in the development of smart cities. The main purpose of smart city programs is to create intelligent infrastructure for cities by leveraging innovations in cyber-physical systems, data science and information and communication technology (ICT). Furthermore, smart infrastructures are more dependent on both ICT and electricity for proper operation. This increased dependency can introduce new vulnerabilities and lower infrastructure resilience [2]. In particular, severe weather events (e.g., snow/ice storms, hurricanes, tornadoes, drought-induced fires, etc.) are a growing vulnerability concern, as their frequency, intensity, and geographic extent of severe weather events are predicted to increase with climate change [3]. Currently, severe weather events [4] are the number one reason for power outages in the United States, which in turn are the leading cause of ICT service outages. For this, smart infrastructures provide more consistent and reliable system performance, new features/functions and increased sustainability.

Microgrids In Frequency Regulation Markets

Industrial-scale microgrids are basically self-sustaining power systems typically in the 1.5–5 MW range. They have been advocated as a mechanism to improve power availability in important social and business facilities such as hospitals, military bases and factories. In addition, microgrids are being promoted as an approach to gradually integrate cogeneration from renewable sources, such as wind and solar, into the bulk power grid in the event of a disaster [5]. Microgrids are also proposed in the literature as a solution to achieve climate adaptation and mitigation goals [6].

Figure 1 gives a typical microgrid architecture. As shown in Figure 1, the building blocks of the microgrid are the controller, power switches, local power supplies (e.g., solar cells, wind turbines, and diesel generators), energy storage, and various loads. Microgrids are designed to operate in stand-alone mode and grid-connected mode. In the combined mode scenario, the microgrid serves as additional energy back to the bulk electricity system, reducing peak loads, improving power stability, and reducing harmful emissions [7]. In island mode, the microgrid is disconnected from the main grid and acts as an autonomous power supply. The microgrid controller manages transitions between modes that seek to maintain voltage and synchronism while minimizing load sag and interruption.

Since available power is limited in island mode, power loads are grouped into their importance categories: mission critical, mission priority, and non-critical. Mission critical loads have the highest priority and consist of the core elements of the critical infrastructure of interest (eg hospitals, water treatment plants and cellular network base stations). Priority shipping loads have second priority and will include loads that are important to society but not necessary for the operation of smart critical infrastructure (eg pharmacy, gas station, etc.). Finally, non-critical loads will include residential and non-essential businesses (eg cinemas).

Generally, microgrids have fixed geographic boundaries and are designed in island mode to generate power sufficient to maintain mission-critical loads within geographic boundaries. Thus, based on the power accessible in island mode, the microgrid controller can apply load shedding, non-critical load shedding, and a portion of mission priority loads [5]. In addition, microgrids are required to have the ability to efficiently shift from island mode to grid-connected mode, providing resynchronization with minimal consequences to significant loads through transient phases.

Thinking Outside The Grid: Heila Technologies Delivers ‘virtual’ Microgrids For Sustainable And Resilient Energy

In contrast to nanogrids used in residential installations, a major barrier to the implementation of industrial-scale microgrids is the high cost of building, operating and maintaining a microgrid. Currently, industrial capacity microgrids are mostly owned by a single private organization. Recognizing the non-linear financial cost of implementing microgrids [8], the authors in [9] advocated shared medium-sized microgrids, with the cost falling on both critical load critical infrastructure owners (e.g. mobile network operators telephone companies and hospitals). and government agencies that will utilize the infrastructure during disaster recovery. This community sharing approach could be facilitated by government funding and tax credits. In addition, it may justify reinsurance or bonding mechanisms to help reduce costs. Here, the objective of this work is to design and deploy microgrids based on minimizing the total costs and ensuring the power flow connected to the most vital parts of the infrastructure. Therefore, the proposed design is able to achieve significant techno-economic advantages for microgrids.

Related work on microgrids includes the use of microgrids to improve radial distribution grid recovery after a natural disaster [5, 10] and the dynamic configuration of local microgrids around distributed generation sources after a disaster [11]. Kelly-Pitou [6] introduced the concept of using a microgrid to improve both electricity resilience and climate change mitigation. However, this early work did not propose a method for determining the location of microgrids to improve the resilience of different critical infrastructures considered as a group. In [12], the authors proposed the use of an algorithm to achieve multi-agent resource allocation in distributed scenarios over a shared microgrid, including residential and commercial buildings, with the least information exchange between users. However, their study lacks the commercial and residential part as it does not prioritize critical network nodes.

Most of the research literature on critical infrastructure in smart city systems has focused on optimizing performance and providing new functions. Previous work covering resilience in smart cities has focused specifically on developing frameworks [13] or “hardening” critical infrastructure. Traditionally, policymakers have mandated or supported mitigation techniques such as building flood barriers and rebuilding levees according to a 1-in-100-year probability. However, when considering smart critical infrastructure and increasing weather variability, planners need to move beyond physical hardening techniques, adopting new preparedness methods and policies that recognize reliance on both power and ICT.

In [9], a framework was developed to provide energy and ICT to improve critical infrastructure services for smart cities

Preparing For The Climate Crisis With Community Microgrids

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