Comparison of the cost of electricity in a highly distributed energy future cell for feed-in tariffs and free market community aggregated trading of microgeneration sourced electricity.

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• Comparison of the cost of electricity in a highly
  distributed energy future cell for feed-in
  tariffs and free market community aggregated
  trading of microgeneration sourced electricity.
• Gordon McKinstry, Stuart Galloway, Bruce Stephen
• Department of Electronic Electrical Engineering
• University of Strathclyde
• Glasgow, United Kingdom

Gordon McKinstry United Kingdom RIF Session 5
Paper 1092
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Overview

• Introduction
• Need for Research Utilisation of DER
• Market Participation of Microgenerators
• Simulation Procedure
• Results
• Conclusion Further Work

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Introduction

• Drivers for change supporting the HiDEF vision
• Many sources, many loads, many market
  participants
• Decentralised energy system 2025 2050
• Research focused on participation through market
  design
• Large scale market reform
• Remuneration schemes support individuals or
  communities

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Need for Research

• Increasing microgeneration increases market
  participation
• Could a community of microgenerators drive down
  prices?
• Reduced demand resulting in expensive plant
  remaining off
• Would existing feed-in tariffs be a better
  option?
• How much should be paid under FiT?
• Is another option required altogether?
• Future Work

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Market Participation of Microgenerators.

• One body sells all community energy to market
• Reduce prices by stopping switch-in of peak
  plant.
• All energy must still be purchased from market.
• Community takes Feed-In Tariff
• Energy consumed locally and deferral payments
  received.
• What level of FiT payment makes this attractive?

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Test Network

• Representative of intermediate HiDEF Cell
• One virtual power plant / negative load to
  represent FiT takers
• Aggregator modelled as first dispatched generator
• Modelled using agent-based learning techniques

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Simulation Procedure Selling To Market

• Level of microgeneration sourced energy at bus 2
• 0 to 1 peak demand in 0.1 increments
• Selling energy to market
• First dispatch generator of size described above
• Objective to limit expensive plant being
  switched-in
• Simulation run for 50 days utilising agent
  learning

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Simulation Procedure Feed-In Tariffs

• Microgeneration now modelled as negative load
• 0 to 1 peak demand in 0.1 increments
• 0 to 200 of MCP paid for FiT sourced energy.
• Simulation run for 50 days with agent learning as
  before
• Cost calculated on per-unit basis, as shown below

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Results

• Payment free FiT can reduce overall price paid
• Why invest without promise of return?
• Increasing provision of DER reduces price per
  unit
• Community VPP FiT prices will ultimately
  converge

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Results

• Equilibrium points found
• FiT pays MCP Community VPP price paid
• FiT paying more than MCP is unviable
• Increasing FiT qualifying participants makes
  aggregation more viable.

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Discussions

• No capital costs considered, only operational.
• Ownership
• Feasibility of enforcing mass participation?
• Technological
• Aggregation requires significant storage media
  development

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Conclusion Further Work

• Community VPP schemes offer viable alternative to
  FiT
• FiT schemes paying over 100 MCP potentially
  very expensive
• Research opportunities exist within
• Assessment of non per-unit schemes.
• The impacts of micro-scale storage on markets.
• The Impacts of macro-scale storage on markets.