IEEE Power & Energy Magazine - January/February 2017 - 49
water-quality requirements. MWSs
and WWSs are operated in a pricetaking setting, with tasks such as
pump scheduling aimed at minimizMin g (Power)
Min h (Gas)
ing operation costs based on the price
Min f (Water)
s.t Power
s.t Gas
s.t Water
of electricity. On the other hand, the
Constraints
Constraints
Constraints
power consumption of MWSs and
WWSs is used as an input to the optimal power-flow problems utilized by
Adjacent
power-systems operators.
Systems Solar
Industrial
However, it is increasingly recArea
ognized that a synergistic control
of power and water systems may
Residential
H1
H2
bring significant benefits from
Area
operational, reliability, and societal
Pumped Hydro
(Storage)
standpoints. In particular, controllable assets in MWSs and WWSs
can provide valuable services to the
power grid at multiple spatial scales
to enhance reliability and efficiency,
Commercial
H3
H4
Wind
as well as to cope with the volatility
Area
of distributed renewable-based genHeating
Natural Gas
Electricity
Water
eration; services include frequency
regulation, regulating reserves, or
even contingency reserves.
figure 6. Traditional operations, where optimization and control tasks are typically
On the other hand, the incen- used to operate power, natural gas, water, and district heating systems in an
tives for provisioning grid services independent and decoupled way. One system's demand is used as a fixed input for
to electric utilities could be used by relevant optimization and control problems of the other systems. s.t: subject to.
water-system operators for capital
improvements and capacity expansion, while operational savings emerging from joint optimiza- power networks to compute the optimal steady-state set
tion and control would lower costs for water-utility customers points of (renewable) generation units, controllable loads, and
while meeting stringent water-quality standards. Pumping in an storage devices; optimal pump-scheduling and water-flow
MWS accounts for the majority of the power consumption; a problems; and gas load-flow problems.
joint water-pump scheduling and power-flow task could, thereHowever, these optimization and control strategies
fore, be used to provide optimal regulating and contingency are typically used to operate power, natural gas, water, and
reserves to the power grid while maximizing the economic district heating systems in an independent and decoupled
benefits to MWS operators.
way (see Figure 6). Grounded on the understanding that joint
Overall, the envisioned control architecture would enable optimization and control of multi-energy systems enables siga seamless system-level coordination of controllable assets at nificant benefits from socioeconomic, flexibility, operational
multiple temporal scales to enable flexible and efficient oper- efficiency, and environmental perspectives (see the examples
ation of the multi-energy infrastructure, while systematically given earlier), the objective of recent research is to formulate
addressing customer needs and well-defined performance (and solve) global optimization problems where a variety of
objectives as set forth by system operators. Core challenges performance objectives and (economic) indicators that pertain
in this direction are outlined in the following section.
to single-energy and multi-energy providers as well as end
customers are optimized, while intrinsic interdependencies
among systems and operational constraints are acknowledged
Technical Challenges in the
(see Figure 7).
Optimization and Control
Inheriting the characteristics of, e.g., ac optimal power
of Integrated Multi-Energy Systems
flow,
water flow, and gas load-flow settings, the resulting
Core optimization tasks in the domains of power, water, thermal, and gas system operations and control enable operators multi-energy optimization problems are, unfortunately, hard
to compute the set points of controllable assets that are "op- to solve for global or local optimization in a computationtimal" in a well-defined sense, while concurrently satisfy- ally efficient manner. Problem complexity is primarily due
ing operational, quality-of-service, and security constraints. to the nonlinear equations that govern the underlying physExamples include optimal power flow-type problems for ics of power, water, heat, and gas networks and the curse of
january/february 2017
ieee power & energy magazine
49
Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - January/February 2017
IEEE Power & Energy Magazine - January/February 2017 - Cover1
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IEEE Power & Energy Magazine - January/February 2017 - Cover3
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