IEEE Power & Energy Magazine - January/February 2017 - 46
Relevant optimization problems can be used to compute the
optimal energy mix for the hub to minimize operational costs or to
optimize the operation of an interconnected system of energy hubs.
underlying optimization and control problems. Hence, the
introduction of joint optimization and integrated control for
electricity and gas networks could bring substantial benefits
by preventing the rise of such situations (see Figure 3).
On the other hand, joint optimization of electricity and
gas, also through the coordination of market activities,
could improve overall system efficiency and the utilization of resources; this is particularly relevant in terms of
the scheduling of reserves by gas-fired generating units and
access to all the substantial flexibility available in the gas
network. In addition, there are new forms of multi-energy
flexibility that the gas network can enable through emerging technologies, including the power-to-gas processes, that
could be accounted for in the development of integrated
optimization and control strategies considering not only
potential flexibility benefits but also relevant flexibility constraints. These constraints may relate, in particular, to regulatory limits imposed on the volume of hydrogen that can be
blended in natural gas (with an upper physical bound on the
order of 20% in volume to prevent leakages, malfunctioning of devices, etc.) and to the fact that more hydrogen in
the network can reduce the flow capacity and lead to greater
line-pack swing.
Flexibility in distribution systems is related to three main
factors (all of which affect the development of distributed
optimization and control strategies at various time scales):
✔✔ the availability of energy storage, more typically in
forms of energy other than electricity (e.g., TES and
thermal inertia)
✔✔ a significant difference in the value of time constants
between electricity and other processes such as heating or cooling
✔✔ effective user flexibility in the net consumption/generation profile.
While the domestic and industrial sectors contribute equally
to the first two factors, the last option is more pronounced in the
industrial setting, where, for example, production processes can
be rearranged to achieve a given demand curve. In contrast, providing such flexibility at the residential level without impacting
customer comfort may be more challenging, and only a few and
limited options have been proposed, e.g., scheduling of appliances
or heating, ventilation, and air-conditioning (HVAC) systems.
The following sections explain some example applications of multi-energy models to suggest opportunities for
increasing flexibility at the district, neighborhood, and residential levels.
Examples of Distribution-Level
Modeling and Applications
Flexibility from Distributed Multigeneration
Departing from conventional operational settings, the
main goal at the distribution level is to leverage the fastacting capabilities of power-electronics-interfaced DERs,
as well as the flexibility offered by a variety of other controllable assets, to enable sustainable capacity expansion,
respond to service requests precipitated by distribution
and transmission-systems operators, and achieve networklevel coordination-and so ensure reliable operation of the
whole distribution infrastructure. Forward-looking control
strategies for renewable-based DERs are complemented by
load-side optimization mechanisms, with the intention of
providing the necessary flexibility to cope with the volatility of renewable generation and provide services at the bulk
level. Additionally, (micro) CHP units as well as TES can
provide flexibility at the generation side. A coordinated
operation of various controllable energy assets can locally
supply electricity and heat (as well as cooling, if required),
while substantially reducing operational costs and environmental impacts. And such coordination can offer increased
flexibility in providing electricity grid services in the form
of demand response in real or close-to-real time.
46
ieee power & energy magazine
Focusing on multi-energy districts (e.g., downtowns, industrial
areas, and neighborhoods), recent studies have demonstrated
that distributed multigeneration (DMG) plants can offer key
advantages by integrating complementary technologies such
as CHP units, EHPs, and TES. In fact, they can locally supply
electricity and heat (as well as cooling, if required), while substantially reducing operational costs, thus offering enhanced
flexibility in provisioning the electricity grid.
An example of a general electricity-and-heat DMG structure is illustrated in Figure 4, where seven operational configurations are possible:
1) auxiliary boiler (AB), which serves as a reference case
2) EHP
3) EHP + TES
4) CHP
5) CHP + TES
6) CHP + EHP
7) CHP + EHP + TES.
Numerical tests performed with this DMG setting indicate that
the operational cost is expected to significantly decrease when
TES is added to both CHP-only and EHP-only settings, as well as
by operating CHP and EHP synergistically. Case 7) dramatically
january/february 2017
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