With the increasing application of distributed energy resources and novel information technologies in the electricity infrastructure, innovative possibilities to incorporate the demand side more actively in power system operation are enabled. A promising, controllable, residential distributed generation technology is a microcombined heat and power system (micro-CHP). Micro-CHP is an energy-efficient technology that simultaneously provides heat and electricity to households. In this paper, we investigate to what extent domestic energy costs could be reduced with intelligent, price-based control concepts (demand response). Hereby, first the performance of a standard, so-called heat-led micro-CHP system is analyzed. Then, a model-predictive control (MPC) strategy aimed at demand response is proposed for more intelligent control of micro-CHP systems. Simulation studies illustrate the added value of the proposed intelligent control approach over the standard approach in terms of reduced variable energy costs. Demand response with micro-CHP lowers variable costs for households by about 1%-14%. The cost reductions are highest with the most strongly fluctuating real-time pricing scheme.

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Demand Response With Micro-CHP Systems

Irrigation canals are large-scale systems, consisting of many
 interacting components, and spanning vast geographical areas. For
 safe and efficient operation of these canals, maintaining the levels
 of the water flows close to pre-specified reference values is crucial,
 both under normal operating conditions as well as in extreme situations.    Irrigation canals are equipped with local controllers, to control
 the flow of water by adjusting the settings of control structures
 such as gates and pumps. Traditionally, the local controllers
 operate in a decentralized way in the sense that they use local
 information only, that they are not explicitly aware of the
 presence of other controllers or subsystems, and that no
 communication among them takes place. Hence, an obvious drawback of
 such a decentralized control scheme is that adequate performance at
 a system-wide level may be jeopardized, due to the unexpected and
 unanticipated interactions among the subsystems and the actions of
 the local controllers.    In this paper we survey the state-of-the-art literature on
 distributed control of water systems in general, and irrigation
 canals in particular. We focus on the model predictive control
 (MPC) strategy, which is a model-based control strategy in which
 prediction models are used in an optimization to determine optimal
 control inputs over a given horizon. We discuss how communication
 among local MPC controllers can be included to improve the
 performance of the overall system. We present a distributed
 control scheme in which each controller employs MPC to determine
 those actions that maintain water levels after disturbances close
 to pre-specified reference values. Using the presented scheme the
 local controllers cooperatively strive for obtaining the best
 system-wide performance. A simulation study on an irrigation canal
 with seven reaches illustrates the potential of the approach.

https://www.dcsc.tudelft.nl/~bdeschutter/pub/rep/08_032.pdf

Distributed model predictive control of irrigation canals

The management of the urban water cycle (UWC) is a subject of increasing interest because of its social, economic, and environmental impact. The most important issues include the sustainable use of limited resources and the reliability of service to consumers with adequate quality and pressure levels, as well as the urban drainage management to prevent flooding and polluting discharges to the environment.

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Application of predictive control strategies to the management of complex networks in the urban water cycle [Applications of Control]

Human life depends on water daily, especially for drinking and food production. Also, human life needs to be protected against excess of water caused by heavy precipitation and floods. People have formed water management organizations to guarantee these necessities of life for communities. These organizations manage a water system within the community and manipulate the water flows in this system to fulfill the water related requirements. To do so, controllable structures, such as gates and pumps are used. The way these structures are controlled, depending on the requirements of the communities, is part of the research field of control on water systems, often referred to as operational water management. In the research "Model Predictive Control on Open Water Systems", the relatively new control methodology Model Predictive Control is configured for application of water quantity control on open water systems, especially on irrigation canals and large drainage systems. The methodology applies an internal model of the open water system, by which optimal control actions are calculated over a prediction horizon.

/pdf/model-predictive-control-on-open-water-systems-44is676n9x.pdf

Model Predictive Control on Open Water Systems

https://digital.csic.es/bitstream/10261/133063/1/Modeling-Real-Time-Review.pdf

Modeling and real-time control of urban drainage systems: A review☆

Canals or open channels that convey water often consist of pools in series separated by control structures. Successful implementation of water-level control with these structures using decentralized proportional integral (PI) controllers depends heavily on the tuning of the control parameters. These parameters are hard to determine due to the interactions between the pools and the varying flow conditions in the canal. This paper presents a procedure for tuning any linear controller (including decentralized PI controllers) that guarantees stability of the controlled canal. It minimizes a cost function that weights the water-level deviations from the target level against control efforts at both low- and high-flow conditions. The procedure is tested on a model of the Umatilla Stanfield Branch Furnish Canal in Oregon. The tests show the capability of the procedure to deal with the pool interactions. The results of a realistic turnout schedule applied to the controlled canal show the high performance of the controllers (small water-level deviations in all pools) over varying flow conditions.

/pdf/multiple-model-optimization-of-proportional-integral-2sina90qre.pdf

Multiple-Model Optimization of Proportional Integral Controllers on Canals

Short-term optimal operation of water systems using ensemble forecasts

Water resources are limited in many agricultural areas. One method to improve the effective use of water is to improve delivery service from irrigation canals. This can be done by applying automatic control methods that control the gates in an irrigation canal. The model predictive control (MPC) is one such advanced control method. In this article, the MPC is used to deliver irrigation water to the WM Canal at the Maricopa-Stanfield Irrigation and Drainage District. The tests show that the water is efficiently delivered to the users and water level deviations at all locations are small. The control is compared to the results from an advanced Linear Quadratic Regulator control method, also tested on the actual canal.

Real-time implementation of model predictive control on Maricopa-Stanfield Irrigation and Drainage District's WM Canal.

The river delta in The Netherlands consists of interconnected rivers and large water bodies Structures, such as large sluices and pumps, are available to control the local water levels and flows The national water board is responsible for the management of the system Its main management objectives are: protection against overtopping of dikes due to high river flows and high sea tides, supply of water during dry periods, and navigation The system is, due to its size, divided into several subsystems that are managed by separate regional divisions of the national water board Due to changes in local land-use, local climate, and the need for energy savings, the currently existing control systems have to be upgraded from local manual control schemes to regional model predictive control (MPC) schemes In principle, the national objectives for the total delta require a centralized control approach integrating all regional MPC schemes However, such centralized control is on the one hand not feasible, due to computational limitations, and on the other hand unwanted, due to the existing regional structure of the organization of the national water board In this chapter the application of MPC is discussed for both individual regional control and coordinated national control Results of a local MPC scheme applied to the actual water system of the North Sea Canal/Amsterdam-Rhine Canal are presented and a framework for coordination between several distributed MPC schemes is proposed

/pdf/predictive-control-for-national-water-flow-optimization-in-23ah6wtq2r.pdf

P. J. van Overloop

Papers

Model Predictive Control on Open Water Systems

Multiple-Model Optimization of Proportional Integral Controllers on Canals

Short-term optimal operation of water systems using ensemble forecasts

Real-time implementation of model predictive control on Maricopa-Stanfield Irrigation and Drainage District's WM Canal.

Predictive Control for National Water Flow Optimization in The Netherlands