Frankfurt (Germany), 6-9 June 2011 Gordon McKinstry – United Kingdom – RIF Session 5 – Paper 1092 Comparison of the cost of electricity in a highly distributed.

Frankfurt (Germany), 6-9 June 2011

Gordon McKinstry – United Kingdom – RIF Session 5 – Paper 1092

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


Overview

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


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


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


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?


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


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


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


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


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.


Discussions

No capital costs considered, only operational.

Ownership Feasibility of enforcing mass participation?

Technological Aggregation requires significant storage media development


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.

Frankfurt (Germany), 6-9 June 2011 Gordon McKinstry – United Kingdom – RIF Session 5 – Paper 1092 Comparison of the cost of electricity in a highly distributed.

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