Smart infrastructure planning: Coordinating distributed community energy resources

By Emi Minghui Guia, Iain MacGillb, Regina Betzc 

Abstract

As distributed energy resources (DER) deployment by households and communities continues to grow in many cities, city planners are struggling to integrate them into both energies yet also wider infrastructure (such as transport) planning and implementation in the smartest way. To best address these challenges, smart infrastructure planning strategies should align both design and operation objectives to achieve allocative efficiency and revenue adequacy to optimize social welfare for households and communities, and to incentivize customer participation and private investments.  The integration and coordination of distributed community resources can be best undertaken through multi-level energy management systems (EMS) at both the household and the community level that work with each other to achieve wider power system, network and community goals.

Introduction

One important feature of smart cities is to introduce smart infrastructure that enables the efficient use, and effective management and control of environmental and economic resources. New infrastructure options create both challenges yet also opportunities for achieving this. For example, distributed energy resources (DERs) such as rooftop photovoltaics systems (PV), battery energy storage (BES), electric vehicles (EVs) and smart load control can complement yet also compete with existing centralised energy infrastructure. As DER deployment by households and communities continues to grow in many cities, city planners are struggling to integrate them into both energies yet also wider infrastructure (such as transport) planning and implementation in the smartest way. To maximise their value requires technology enablers, supported by Internet-of-Things (IoTs), advanced metering, and smart grid technologies, as well as business and social innovations involving smart communities to deliver innovative services to the public [1].

Currently, there are several approaches for the integration of DERs into the existing electricity arrangements, ranging from more passive to more active roles for prosumers (producer consumers). Some prosumers deploy DERs purely for own consumption and do not export to the grid, including off-grid applications, while some may sell excess electricity to the grid via bilateral arrangements with the market operator (for larger sites) or their retailer at specified pre-determined rates. Others may choose to participate more actively through a virtual power plant (VPP), established by an aggregator, to export to the grid through private or market arrangements in a more coordinated manner, to provide services such as demand response and contingency reserves. Finally, some could participate through a more autonomous peer-to-peer trading (P2P) marketplace, to share and trade energy among the community, representing an even higher level of customer decision making and customer engagement [2].

As examples of these higher engagement models for prosumers, the world’s largest virtual power plant to date is being planned and implemented by the South Australian government involving a network of potentially up to 50,000 home solar PV systems rated at 5kW, each coupled with 13.5kWh Tesla Powerwall 2 battery systems [3]. Aside from lowering energy bills and providing higher reliability for those participating households, this development offers wider benefits for smart cities goals including i) increasing the protection of vulnerable citizens through providing priority installation for vulnerable households; ii) improving quality of life and reducing environmental footprint by providing renewable clean power; iii) allowing more efficient electricity network management through flexible battery system operation to reduce peak demand; iv) creating opportunities for better energy efficiency and demand side management amongst participating households via a real-time energy use app. In addition, this distributed electricity infrastructure can support smart transportation initiatives, such as EVs and thus further increase the utilization of these assets.  

Several microgrid projects including some using blockchain technologies and different approaches to peer-to-peer trading, are also being trialled in the state of Victoria and Western Australia [4]. Beyond the initial trial stage supported by the State governments and Federal agencies such as Australian Renewable Energy Agency, these projects are intended to be mostly privately owned and operated. Private investors will decide whether to participate in such projects based on its expected future cash flow and economic returns [5]; a utility may favor the project if in regions where network congestion can be relieved, reliability can be improved or cost savings can be realized [6].

A smart infrastructure planning strategy should align both design and operation objectives to achieve allocative efficiency and revenue adequacy to optimize social welfare for households and communities, and to incentivize customer participation and private investments, as illustrated in Figure 1. Providers with expertise in providing the technologies and platforms are typically playing the role of planners for these more sophisticated integration options, such as VPPs, P2Ps, and community microgrids. Many challenges exist in a) determining the optimal asset and capacity mix, particularly in relation to communal investments and private individual investments [7]; b) balancing social and economic goals of providers and communities; c) effective joint planning and integration of distributed community assets and centralized assets; d) an appropriate tariff design to provide some level of longer term assurance, and to contain price fluctuations to an acceptable level, taking into consideration of consumer willingness-to-pay, the spending power of the community and broader equity considerations. Further work is required to develop innovative designs and models to achieve sustainable and efficient outcomes for communities, investors, providers, and broader energy consumers.

Figure 1. Design objectives and design elements of smart infrastructure planning (adapted from [8])

Article 03 Figure 01

 

Looking further into future trends in smart technology and communications, a growing number of prosumers will decide to invest in sophisticated metering and energy management technologies, systems and controllers, sensors and actuators to measure and control electricity consumption of home appliances, micro-generation, and the battery storage in their electric vehicles [9]. Coordinating such prosumers will likely best be undertaken through multi-level energy management systems (EMS) that work with each other to achieve wider power system, network and community goals.

  1. At the household level, the EMS will assist in managing their own electricity consumption to increase energy efficiency and reduce the electricity cost based on the dynamic status of electricity tariffs, generation, household appliances, sensor data, weather data, and occupants' activity data.
  2. At the community level the EMS will coordinate and joint-optimize community resources, communicating to the broader electricity system and market as a single entity.

Coordinated scheduling looks to have considerable potential value for the wider electricity sector, particularly as the electricity sector transitions to a lower carbon future with high variable renewable penetrations. As just one example, a study on modelling the hybrid EV passenger vehicle charging found that a managed charging strategy that aligned charging with growing penetrations of solar generation saved 2% of overall NEM generation portfolio costs compared to unmanaged charging [10]. New retail tariff structures, for example with the value between the solar Feed-in-Tariff (FiT) and the standard retail consumption tariff [11], or incentives for controlled operation of these distributed resources are likely to be an important part of aligning their integration with industry benefits.

Conclusions

To best facilitate the development of smart communities and smart cities, challenges in the investment and planning, and the integration of distributed community resources must be appropriately addressed. This article provides insights on coordinating and integrating distributed community resources, as well as planning options and design strategies. However, the hard work still lies ahead, as do the opportunities that DERs offer future cities.   

References 

  1. Gui, E.M. and I. MacGill, Typology of future clean energy communities: An exploratory structure, opportunities, and challenges. Energy Res. Social Sci., 2018. 35: p. 94-107.
  2. Gui, E.M., I. MacGill, and R. Betz, Community microgrid investment planning: A conceptual framework, in 4th IEEE International Smart Cities Conference (ISC2). 2018, IEEE: Kansas city, Missouri.
  3. Government of South Australia. Meet the world's largest virtual power plant. 2018  [cited 2018 6/11]; Available from: https://virtualpowerplant.sa.gov.au/.
  4. Willow, A. Victoria announces first microgrid consortium. 2018  [cited 2018 6/11]; Available from: https://www.thefifthestate.com.au/energy-lead/local-government-energy-lead/victoria-announces-first-microgrid-consortium/.
  5. Lai, C.S., et al., Levelized cost of electricity for photovoltaic/biogas power plant hybrid system with electrical energy storage degradation costs. Energy Convers. Manage., 2017. 153: p. 34-47.
  6. Gui, E.M., M. Diesendorf, and I. MacGill, Distributed Energy Infrastructure Paradigm: Community micorgrids in a New Institutional Economics context. Renew. Sustain. Energy Rev., 2017. 72: p. 1355–1365.
  7. Lai, C.S. and M.D. McCulloch, Sizing of stand-alone solar PV and storage system with anaerobic digestion biogas power plants. IEEE Trans. Ind. Electron., 2017. 64(3): p. 2112-2121.
  8. Gui, E.M., Investment planning and institution design of community microgrids as a socio-technical energy system, PhD dissertation in School of Electrical Engineering and Telecommunications. 2019, University of New South Wales: Sydney, Australia.
  9.  Zhao, W., et al., Smart home system: integration of energy facilities and environmental factors, in 7th International Conference: Energy Efficiency in Domestic Appliances and Lighting (EEDAL' 2013), I.G.T.P.B. (Eds.), Editor. 2014: Italy: European Union Luxemborg. p. 1242-1251.
  10. Vithayasrichareon, P., G. Mills, and I. MacGill, Impact of Electric Vehicles and Solar PV on Future Generation Portfolio Investment. IEEE Trans. Sustain. Energy, 2015. 6(3): p. 899-908.
  11.  Marshall, L., A. Bruce, and I. MacGill, Allocation rules and meter timing issues in 'Peer to peer' networks, in 2017 Asia-Pacific Solar Research Conference. 2017: Melbourne, Australia.

Contributors

  • Emi Minghui Guia  (IEEE member) School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney NSW 2052, Australia
  • Iain MacGillb (IEEE member), - Centre for Energy and Environmental Markets and School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney NSW 2052, Australia
  • Regina Betzc (non-member) -  Center for Energy and the Environment, School of Management and Law, Zurich University of Applied Sciences, Winterthur 8401, Switzerland