IEEE Electrification - June 2019 - 19

Contractor

Gas DNO

TSO

DNO

Government

Electricity Producer

District

Electricity Generation (MW)

Change in Operational Revenue (k£/Year)

displaces dirty and expensive electricity generation units.
payments. This would have a negative impact in the form
But it can also be harmful if, for instance, it reduces the
of lost revenue (compared with the BAU case) for electricity
revenue of network operators who are responsible for conproducers, the government, and network operators, i.e.,
necting the multienergy resources and enabling the busireduced distribution and transmission use of system chargness of smart districts or if it makes the business case for
es (DUoS and TUoS, respectively). As discussed previously,
generating new firms.
some of these effects can be considered acceptable if, for
To understand the effects that demand-side flexibility
example, carbon-intensive generators are driven out of
(e.g., from the Manchester district) can have, it is convebusiness. However, the reduced revenue may not be acceptnient to map the interactions within the energy sector
able, especially considering that the integration of different
(see Figure 10). Developed using value-flow approaches,
distributed multienergy technologies within the district
the map tracks the energy, cash, and information exchangmay lead to increased network stress and costs.
es between different actors in the
energy sector. These exchanges are
based on
800
1) the physical characteristics of
Wholesale Electricity
the system (e.g., electricity is
600
Imbalance
generated by producers and
Capacity
400
travels through the transmisElectricity DUoS
sion and distribution networks
Electricity TUoS
200
to reach customers)
BSUoS
2) the regulatory framework (e.g.,
0
ESO and VAT
customers pay retailers who
Whole Gas
then pay DNOs, the TSO, and
-200
Gas DUoS
other actors)
O and M
-400
3) emerging business cases (e.g.,
Net
contractors may provide opera-600
tion and maintenance to the
multienergy infrastructure within the smart district).
A main advantage of the valueflow mapping approach is that it
facilitates quantifying the effects of
district optimization on different
revenue flows, for customers with- Figure 11. The business case analysis. BSUoS: balancing services use of system; ESO: environin the district and other actors (see mental and social obligation; VAT: value-added tax.
the quantification of the change of
revenue for selected actors in Figure 11). In this context, the district
250
manager, retailer, aggregators, or
other actors that can represent cus200
tomers in different energy markets
no longer focus only on the provi150
sion of energy vectors but, instead,
concentrate on providing services.
100
These services can be tracked to
the actors who would normally
50
provide them, so that the impact of
the smart district on the business
0
of such actors can be assessed.
1
6
11
16
21
In this example, smart operation
Time
(h)
of the Manchester district in the
extreme case brings about signifiConventional (BAU)
Hydro (BAU)
PV (BAU)
Conventional (Smart)
Hydro (Smart)
PV (Smart)
cant benefits for customers. It takes
advantage of price arbitrage in the
wholesale energy market and Figure 12. The conventional, hydropower, and PV-generation profiles subject to BAU
reduces network charges and tax and smart operation.
IEEE Elec trific ation Magazine / J UNE 2 0 1 9

IEEE Electrification - June 2019

Table of Contents for the Digital Edition of IEEE Electrification - June 2019