4.6 Article

Agent Based Modelling of a Local Energy Market: A Study of the Economic Interactions between Autonomous PV Owners within a Micro-Grid

Journal

BUILDINGS
Volume 11, Issue 4, Pages -

Publisher

MDPI
DOI: 10.3390/buildings11040160

Keywords

urban photovoltaic systems; energy communities; agent based modelling; techno-economic modelling; market design; distributed renewable energy

Funding

  1. European Union [768766]
  2. J. Gust. Richert foundation in Sweden [2020-00586]
  3. Swedish Research Council [2020-00586] Funding Source: Swedish Research Council

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Urban PV systems can meet a significant portion of residential electrical demand at a cost below consumer prices, and the profitability of the system as a whole is demonstrable. However, financing and managing a shared system remains an unsolved issue.
Urban Photovoltaic (PV) systems can provide large fractions of the residential electric demand at socket parity (i.e., a cost below the household consumer price). This is obtained without necessarily installing electric storage or exploiting tax funded incentives. The benefits of aggregating the electric demand and renewable output of multiple households are known and established; in fact, regulations and pilot energy communities are being implemented worldwide. Financing and managing a shared urban PV system remains an unsolved issue, even when the profitability of the system as a whole is demonstrable. For this reason, an agent-based modelling environment has been developed and is presented in this study. It is assumed that an optimal system (optimized for self-sufficiency) is shared between 48 households in a local grid of a positive energy district. Different scenarios are explored and discussed, each varying in number of owners (agents who own a PV system) and their pricing behaviour. It has been found that a smaller number of investors (i.e., someone refuse to join) provokes an increase of the earnings for the remaining investors (from 8 to 74% of the baseline). Furthermore, the pricing strategy of an agent shows improvement potential without knowledge of the demand of others, and thus it has no privacy violations.

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