Mapping multi-form flows in smart multi-energy districts to facilitate new business cases



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Mapping multi-form flows in smart multi-energy districts to facilitate new business cases Pierluigi Mancarella Nicholas Good, Alex Martinez-Cesena The University of Manchester p.mancarella@manchester.ac.uk SUSTAINABLE PLACEs Workshop Nice 1 st October 2014 1

2 Contents Vision to create a business model for an EPN Setting up a business case framework External and internal market frameworks Business case multi-commodity mapping Business Case study applications Concluding remarks and next Work carried out within the FP7 COOPERATE Project

Vision: from retail electricity markets to Smart Grid(s) and Energy Positive Neighborhoods (EPN) Going beyond retail electricity markets Multiple electricity services Beyond electricity Synergies with gas, heat, cooling, transport, water Facilitated by and along with ICT 3

4 Setting up a business case framework Where is value extracted from How is flexibility extracted from the EPN How is the value allocated across the actors Externally to the EPN (focus of this work) Internally to the EPN How are enabling facilities invested into?

5 External market frameworks Examples: Real time prices Ancillary services Bespoke markets Network related markets Active network management

6 Who are the actors involved? An example: who is the Aggregator? Which actor? Aggregator role An actor who may exploit an existing relationship with the EPN An actor who may be able to benefit from economies of scale and economies of scope 1. Retailer-aggregator Bespoke company AggrESCo Facilities management company 2. Independent aggregator NEM? DNO/DSO?

7 What more actors in the value chain? External actors Transmission system operator Distribution network/system operator Producers EPN Retailer ICT providers Gas supplier Aggregators

How do I figure out the complexity? 8

Example: interaction matrix 9

10 Business case examples Different possible business cases discussed Energy services Network services

Case study application: the EPN 50 well insulated flats 50% with an ASHP 50% with a CHP COP 1.97/3.51 at 0/20 C air temperature 145 litre thermal energy store 40-55 C 700m 2 PV panels 20% efficiency 78% thermal efficiency 13% electrical efficiency 145 litre thermal energy store 55-80 C 11

Case study application: Investigated Business Cases 12

13 Business case general info Wholesale prices - UK market index prices Imbalance prices UK imbalance prices DUoS prices Based on Electricity North West s LV halfhourly metered rate TUoS prices Based on the average UK TUoS fees and assumes 15 TRIAD warnings per year OR prices Based on recent prices for the UK STOR product

Value mapping and business cases 14

Business case results: EPN aggregator s benefits 15

Effect of commodity price coincidence 16

Concluding remarks on the business case The developed methodology allows identification of all benefits (and costs) associated to different commodities (energy, reserve, network, etc) Most benefits come from networked effects of multicommodities Full mapping is thus critically needed to have a full understanding of the available business case opportunities and not to miss any Also key to identify in advance possible issues Trade-offs can be optimally estimated Network and energy services have different impact on users (frequency of utilization as a key point) Results are case specific 1 st and 2 nd order network effects to be considered too in the value chain 17

Next: Cost benefit analysis (CBA) CBA to be undertaken For various actors Under different market frameworks Considering different EPN attributes Considering different indicators (economic, environmental, etc) Who will invest? Contract modelling for EPN users Benefit sharing Incentives Contract structure 18

19 Thank you! Any Questions? p.mancarella@manchester.ac.uk

Relevant references N. Good, E.A. Martinez Cesena and P. Mancarella, Mapping multi-form flows in smart multi-energy districts to facilitate new business cases, Sustainable Places conference, Nice, France, 2014 N. Good, L. Zhang, A. N. Espinosa, and P. Mancarella, High resolution modelling of multi-energy domestic demand profiles, Applied Energy, accepted for publication, 2014 T. Capuder and P. Mancarella, Techno-economic and environmental modelling and optimization of flexible distributed multi-generation options, Energy, Vol. 71, 2014, pages 516-533 P. Mancarella and G.Chicco, Real-time demand response from energy shifting in Distributed Multi-Generation, IEEE Transactions on Smart Grid, vol. 4, no. 4, Dec. 2013, pp. 1928-1938 P.Mancarella, Multi-energy systems: an overview of models and evaluation concepts, Energy, Vol. 65, 2014, 1-17, Invited paper A. Ahmed and P. Mancarella, Strategic techno-economic assessment of heat network options in distributed energy systems in the UK, Energy 75 (2014) 182-193 A. Navarro Espinosa and P. Mancarella, Probabilistic modeling and assessment of the impact of electric heat pumps on low voltage distribution networks, Applied Energy, Vol. 127, 2014, pag. 249 266 G.Chicco and P.Mancarella, From cogeneration to trigeneration: profitable alternatives in a competitive market, IEEE Transactions on Energy Conversion, Vol.21, No.1, March 2006, pp.265-272 20

Mapping multi-form flows in smart multi-energy districts to facilitate new business cases Pierluigi Mancarella Nicholas Good, Alex Martinez-Cesena The University of Manchester p.mancarella@manchester.ac.uk SUSTAINABLE PLACEs Workshop Nice 1 st October 2014 21