Combined analysis of electricity and heat networks

Liu, Xuezhi; Jenkins, Nick; Wu, Jianzhong; Bagdanavičius, Audrius

doi:10.1016/j.apenergy.2015.01.102

Cited by 606 publications

(330 citation statements)

References 25 publications

(42 reference statements)

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“…The consumed electrical power of the ith circulating pump can be calculated as follows [30,43] by (13g). Limits of the generated heat power of CHPs and boilers are defined by (13h) and (13i), respectively while (13j) and (13k) specify temperature margins of the CHPs and boilers, respectively.…”

Section: Equality Constraintsmentioning

confidence: 99%

Simultaneous integrated optimal energy flow of electricity, gas, and heat

Shabanpour-Haghighi

Seifi

2015

Energy Conversion and Management

136

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Section: Equality Constraintsmentioning

confidence: 99%

Simultaneous integrated optimal energy flow of electricity, gas, and heat

Shabanpour-Haghighi

Seifi

2015

Energy Conversion and Management

136

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“…The practical example of site is a commercial, civil, or large residential building with own CHP plant, and the entire system can be regarded as a minimal prototype of practical DHC systems with CHP plants as reported in e.g. [23,3,24]. In the context of electricity supply, the system can be regarded as an extension of the so-called three-node network, for which static and dynamic characteristics have been studied in e.g.…”

Section: Modeling and Problem Formulationmentioning

confidence: 99%

“…[1,2]. For example, the so-called Combined Heat and Power (CHP) technology, which exploits waste heat as a by-product of conversion of fuel into electricity, has established an interaction between electric power systems and District Heating and Cooling (DHC) systems [3]. The above point of view is described as Energy Systems Integration (ESI) [2] and has recently attracted a lot of interest in engineering and science.…”

Section: Introductionmentioning

confidence: 99%

“…For a high-level planner, various systematic methods have been proposed for operational optimization: see e.g. [4,5,6,3]. While the above studies successfully show the effectiveness of ESI in a steady state, design of a low-level controller is a challenging problem because of the complex physics of energy transfer and conversion in a wide range of scales in space and time [7].…”

Section: Introductionmentioning

confidence: 99%

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Structural Analysis and Control of a Model of Two-Site Electricity and Heat Supply

Hoshino

Susuki

Koo

et al. 2019

Journal of Dynamic Systems, Measurement, and Control

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This paper introduces a control problem of regulation of energy flows in a two-site electricity and heat supply system, where two Combined Heat and Power (CHP) plants are interconnected via electricity and heat flows. The control problem is motivated by recent development of fast operation of CHP plants to provide ancillary services of power system on the order of tens of seconds to minutes. Due to the physical constraint that the responses of the heat subsystem are not necessary as fast as those of the electric subsystem, the target controlled state is not represented by any isolated equilibrium point, implying that stability of the system is lost in the long-term sense on the order of hours. In this paper, we first prove in the context of nonlinear control theory that the state-space model of the two-site system is non-minimum phase due to nonexistence of isolated equilibrium points of the associated zero dynamics. Instead, we locate a one-dimensional invariant manifold that represents the target controlled flows completely. Then, by utilizing a virtual output under which the state-space model becomes minimum phase, we synthesize a controller that achieves not only the regulation of energy flows in the short-term regime but also stabilization of an equilibrium point in the long-term regime. Effectiveness of the synthesized controller is established with numerical simulations with a practical set of model parameters.

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“…The performance of district heating networks with multiple sources was studied in [6].Significant effort has also been invested in simplified models of these systems. The steady-state thermal losses of a network can be modelled as an exponential temperature drop along a pipe segment [6,7,8,9].By replacing the exponential by its first order Taylor approximation, the authors of [7] and [9] obtain a polynomial representation of the pipe output temperature. The hydraulic losses, namely the pressure drop along pipes and substations, are mass flow rate dependent and can be characterised implicitly by the nonlinear Colebrook-White equation [6].…”

mentioning

confidence: 99%

A two-stage polynomial approach to stochastic optimization of district heating networks

Hohmann

Warrington

Lygeros

2019

Sustainable Energy, Grids and Networks

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In this paper, we use stochastic polynomial optimization to derive high-performance operating strategies for heating networks with uncertain or variable demand. The heat flow in district heating networks can be regulated by varying the supply temperature, the mass flow rate, or both simultaneously, leading to different operating strategies. The task of choosing the set-points within each strategy that minimize the network losses for a range of demand conditions can be cast as a two-stage stochastic optimization problem with polynomial objective and polynomial constraints. We derive a generalized moment problem (GMP) equivalent to such a two-stage stochastic optimization problem, and describe a hierarchy of moment relaxations approximating the optimal solution of the GMP. Under various network design parameters, we use the method to compute (approximately) optimal strategies when one or both of the mass flow rate and supply temperature for a benchmark heat network. We report that the performance of an optimally-parameterized fixed-temperature variable-mass-flow strategy can approach that of a fully variable strategy. systems tend to have variable mass flow control [2]. Each strategy is subject to a trade-off in terms of losses; higher supply and return temperatures lead to increased heat losses, whereas higher mass flow rates increase the hydraulic losses in the pipes. This trade-off has been studied in different contexts. A comparison of strategies for primary networks 1 can be found in [3]. Hydraulic control strategies for the primary and secondary network were optimized in [4]. New mass flow regulation schemes using pumps were compared to the traditional strategy of controlling the consumer side heat flow using valves in [5]. The performance of district heating networks with multiple sources was studied in [6].Significant effort has also been invested in simplified models of these systems. The steady-state thermal losses of a network can be modelled as an exponential temperature drop along a pipe segment [6,7,8,9].By replacing the exponential by its first order Taylor approximation, the authors of [7] and [9] obtain a polynomial representation of the pipe output temperature. The hydraulic losses, namely the pressure drop along pipes and substations, are mass flow rate dependent and can be characterised implicitly by the nonlinear Colebrook-White equation [6]. To simplify this representation, it is often assumed that a pipe segment has a constant coefficient of resistance [7,9,10], making the absolute pressure losses quadratic in the mass flow rate. Thus, both types of network loss can be modelled using polynomial functions. Two-stage stochastic programsIf the operating strategy keeps a control variable fixed (either temperature or mass flow rate), it is desirable that the fixed choice leads to acceptable performance over a range of demand conditions. Here we define this performance as the expected operational cost incurred by hydraulic and thermal losses with respect to a probability distribution of the heat de...

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Combined analysis of electricity and heat networks

Cited by 606 publications

References 25 publications

Simultaneous integrated optimal energy flow of electricity, gas, and heat

Simultaneous integrated optimal energy flow of electricity, gas, and heat

Structural Analysis and Control of a Model of Two-Site Electricity and Heat Supply

A two-stage polynomial approach to stochastic optimization of district heating networks

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