Fast Pump Scheduling Method for Optimum Energy Cost and Water Quality in Water Distribution Networks with Fixed and Variable Speed Pumps

Abdallah, Mouin; Kapelan, Zoran

doi:10.1061/(asce)wr.1943-5452.0001123

Cited by 40 publications

(15 citation statements)

References 60 publications

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“…Decentralised fixed speed centrifugal pumps are considered within the current MILP framework. Centralised variable speed pumps could be accommodated if their range of operation is restricted (see [21]). However, the ability to model decentralised variable speed pumps requires non-convex modelling of network pressure.…”

Section: B Framework Extension: Multi-energy Networkmentioning

confidence: 99%

Model Predictive Control of Smart Districts With Fifth Generation Heating and Cooling Networks

Taylor

Long

Marjanović

et al. 2021

IEEE Trans. Energy Convers.

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Fifth Generation District Heating and Cooling (5GDHC) networks, in which low temperature water is distributed to water-source heat pumps (WSHPs) in order to meet thermal demands, are expected to have a significant impact on the decarbonisation of energy supply. Thermal storage installed in these networks offers operational flexibility that can be leveraged to integrate renewable electrical and thermal energy sources. Thus, when considered as part of a smart multi-energy district, 5GDHC substation devices (e.g. WSHPs, storage) may be optimally operated using Model Predictive Control (MPC) in order to match demand with low-cost supply of electricity. However, the application of MPC requires the ability to model 5GDHC networks within the context of a multi-energy system. Hence, this paper extends an existing, generalised control-oriented modelling framework for multi-energy systems to accommodate 5GDHC networks. Additions include the ability to represent hydraulic pumps, thermodynamic cycle devices (such as WSHPs) and multienergy networks within the framework. Furthermore, an economic MPC (eMPC) scheme is proposed for energy management of 5GDHC-based smart districts. Finally, a case study is presented in which the proposed eMPC controller is compared with rulebased control for economic operation of a smart district. Index Terms-model predictive control, smart districts, district heating and cooling, multi-energy systems.

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Section: B Framework Extension: Multi-energy Networkmentioning

confidence: 99%

Model Predictive Control of Smart Districts With Fifth Generation Heating and Cooling Networks

Taylor

Long

Marjanović

et al. 2021

IEEE Trans. Energy Convers.

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“…The objective function, Equation ( 28) is minimized by deciding on the pump's curve parameters a p and b p . The individual pumps' flows are estimated in Equation (29). To obtain the total estimated flow of the pumping station, the individual pumps' flows are summed in Equation ( 30) and the horizontal error can be calculated in Equation (31), while maintaining the non-negativity of the parameters in Equations ( 32) and (33).…”

Section: Variable Speed Pumpsmentioning

confidence: 99%

“…Next, using each pump's speed, their estimated individual flows (Q est,1 , Q est,2 ) are estimated (at Points C and D) by inverting Equation (24). In the optimization model, these operations are lumped together in Equation (29). Finally, the estimated flows are summed in Equation ( 30) to obtain the total estimated flow Q est , which is then used in calculating the horizontal error in Equation (31).…”

Section: Variable Speed Pumpsmentioning

confidence: 99%

“…With the VSPs gaining popularity in practice, they have been modelled in most simulation software, such as EPANET [22], and their modelling and simulation continue to be an active research topic [23][24][25][26]. Many studies of VSPs address the operation of WDSs and optimization of pumps scheduling [27][28][29][30][31]. In a recent review, Wu et al [32] report improved system efficiency due to the use of VSPs, as well as other benefits of increased levels of flexibility in controlling WDSs in real time.…”

Section: Introductionmentioning

confidence: 99%

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Optimization Methodology for Estimating Pump Curves Using SCADA Data

Salomons

Shamir

Housh

2021

Water

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Water distribution systems (WDSs) deliver water from sources to consumers. These systems are made of hydraulic elements such as reservoirs, tanks, pipes, valves, and pumps. A pump is characterized by curves which define the relationship of the pump’s head gain and efficiency with its flow. For a new pump, the curves are provided by the manufacturer. However, due to its operating history, the performance of a pump deteriorates, and its curves decline at an estimated rate of about 1% per year. Pump curves are key elements for planning and management of WDSs and for monitoring system efficiency, to determine when a pump should be rehabilitated or replaced. In practice, determining pump curves is done by field tests, which are conducted every few years. This leaves the pump’s performance unmonitored for long time periods. Moreover, these tests often cover only a small range of the curves. This study demonstrates that in the era of IoT and big data, the data collected by Supervisory Control And Data Acquisition (SCADA) systems can be used to continuously monitor pumps’ performance and derive updated pump characteristic curves. We present and demonstrate a practical methodology to estimate fixed and variable speed pump curves in pumping stations. The proposed method can estimate individual pump curves even when the measurements are given only for the pumping station as a whole (i.e., total flow, pumping station head gain). The methodology is demonstrated in a real-world case study of a pumping station in southern Israel.

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“…Furthermore, other optimization methods are highlighted, such as ant colony optimization [27] or particle swarm solution [28]. In order to improve computational time, Rao and Salmons [29] combined artificial neural networks (ANNs) with a GA. Then, Abdallah and Kapelan [30] developed a fast VSP scheduling method through an improved goal programming algorithm to optimize the energy cost in a computationally efficient manner.…”

Section: Introductionmentioning

confidence: 99%

Use of Fixed and Variable Speed Pumps in Water Distribution Networks with Different Control Strategies

Briceño-León

Iglesias-Rey

Martínez-Solano

et al. 2021

Water

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The control system’s point is to bring the pumping curve close to the set-point curve. That concept is essential for proper design of a pumping station. An adequate design is focused not only on selecting the total number of pumps and the type of control to use (flow or pressure), but it also is important to determine the optimal number of fixed speed pumps (FSPs) and variable speed pumps (VSPs) for each flow rate. This work discusses the most common methods and procedures for control systems on a design of pumping stations with a proposed methodology. This methodology consists of expressing the characteristics of the pumping curve and the set-point curve in a dimensionless form so that the methodology is standardized for any pump model and set-point curve. These formulations allow us to discuss how the characteristic of a pump and the set-point curve of the network influence the optimal number of FSPs and VSPs in energy terms. In general, the objective of this work is to determine the most suitable total number of pumps in a pumping station design and to determine the optimal pumping configuration in every flow rate, thus the consumed energy would be the minimum. Additionally, this methodology develops an expression to estimate the performance of a frequency inverter when a VSP operates at different rotational speeds. This work will be applied to different study cases, and the obtained results allow us to question several usual procedures for pumping control system. In general, it can be concluded that the number of pumps of a pumping system cannot be inferred in a simple form without a deep analysis of a control system.

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Fast Pump Scheduling Method for Optimum Energy Cost and Water Quality in Water Distribution Networks with Fixed and Variable Speed Pumps

Cited by 40 publications

References 60 publications

Model Predictive Control of Smart Districts With Fifth Generation Heating and Cooling Networks

Model Predictive Control of Smart Districts With Fifth Generation Heating and Cooling Networks

Optimization Methodology for Estimating Pump Curves Using SCADA Data

Use of Fixed and Variable Speed Pumps in Water Distribution Networks with Different Control Strategies

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