Understanding the Value of Net Metering Outcomes for Different Averaging Time Steps

The installation of distributed energy resources (DER) heavily impacts on the power patterns of the prosumers. In fact, the variability of the generation, together with the technical characteristics of the storage systems, may introduce a huge variety in the shape of the net power curves seen from the point of common coupling (PCC). This leads to completely rethink the definition of the time series required to create homogeneous group of prosumers, for providing useful tools to manage the emerging paradigms in the electricity system, such as energy communities and local energy markets. Moreover, the differences between the local energy production and consumption at the PCC could become hidden, if the local energy management has to be considered as a private decision of the local user. In this case, only net metering (that implies a unique measurement of the net electricity taken from the grid) will be used to evaluate the impact on the network of the net power curves. Hence, new approaches are required to properly measure the electricity exchange at the PCC. This paper addresses how the net metering outcomes depend on the time resolution of the measured data, and how the information taken from net metering can be valued by giving different price rates to positive and negative values. Specific examples are provided to remark the importance of the time resolution to properly characterise the prosumers.

[1]  Ole Langniss,et al.  Renewable Energy in Europe , 2003 .

[2]  Gianfranco Chicco,et al.  Probabilistic generation of time-coupled aggregate residential demand patterns , 2015 .

[3]  Ahti Salo,et al.  Strategic offering of a flexible producer in day-ahead and intraday power markets , 2020, Eur. J. Oper. Res..

[4]  Clark W Gellings,et al.  The Smart Grid: Enabling Energy Efficiency and Demand Response , 2020 .

[5]  Andrea Mazza,et al.  Impact of the Time Resolution for Data Gathering on Loss Calculation and Demand Side Flexibility , 2020, 2020 International Conference on Smart Energy Systems and Technologies (SEST).

[6]  Gianfranco Chicco,et al.  Determination of the Relevant Time Periods for Intra-Day Distribution System Minimum Loss Reconfiguration , 2015 .

[7]  Mohammed H. Albadi,et al.  A summary of demand response in electricity markets , 2008 .

[8]  G. Chicco,et al.  Net-Metering Benefits for Residential Customers: The Economic Advantages of a Proposed User-Centric Model in Italy , 2018, IEEE Industry Applications Magazine.

[9]  Gianfranco Chicco,et al.  Data pre-processing and representation for energy calculations in net metering conditions , 2014, 2014 IEEE International Energy Conference (ENERGYCON).

[10]  Anthony Papavasiliou,et al.  Adaptive Trading in Continuous Intraday Electricity Markets for a Storage Unit , 2020, IEEE Transactions on Power Systems.

[11]  Philipp Grünewald,et al.  Flexibility, dynamism and diversity in energy supply and demand: A critical review , 2018 .

[12]  Pravin Varaiya,et al.  Analysis of Solar Energy Aggregation Under Various Billing Mechanisms , 2017, IEEE Transactions on Smart Grid.

[13]  Iain MacGill,et al.  Typology of future clean energy communities: An exploratory structure, opportunities, and challenges , 2017 .

[14]  Robert Gross,et al.  On demand: Can demand response live up to expectations in managing electricity systems? , 2019, Energy Research & Social Science.

[15]  Joao P. S. Catalao,et al.  An overview of Demand Response: Key-elements and international experience , 2017 .

[16]  Alessandro Ciocia,et al.  Toward the Complete Self-Sufficiency of an nZEBs Microgrid by Photovoltaic Generators and Heat Pumps: Methods and Applications , 2019, IEEE Transactions on Industry Applications.

[17]  Gianfranco Chicco,et al.  New insights for setting up contractual options for demand side flexibility , 2019, ArXiv.

[18]  Archana S. Talhar,et al.  Implementation and Investigation of Net Metering: Proposing Real-Time Tariffs for Residential Consumers in Maharashtra State , 2020, IEEE Industry Applications Magazine.

[19]  Hans Auer,et al.  Profitability of PV sharing in energy communities: Use cases for different settlement patterns , 2019 .

[20]  Paulien M. Herder,et al.  Energetic communities for community energy: A review of key issues and trends shaping integrated community energy systems , 2016 .

[21]  Vimal Bhatia,et al.  Bridging the Digital Divide: Challenges in Opening the Digital World to the Elderly, Poor, and Digitally Illiterate , 2019, IEEE Consumer Electronics Magazine.