Bogumil Ulanicki | De Montfort University (original) (raw)

Papers by Bogumil Ulanicki

This output presents implementation results from EPSRC grant (GR/M67360, £108k), “Optimised Press... more This output presents implementation results from EPSRC grant (GR/M67360, £108k), “Optimised Pressure Control for Networks with Multiple Pressure Reducing Valves Inputs” and the follow-on EPSRC RAIS grant (GR/S14382). The findings were implemented by South Staffordshire Water Company in 15 district metering areas reducing water losses by 20% (Nigel Shipley, South Staffordshire Water, nigelshipley@south-staffordshire.com). Similar strategies are now being implemented by Yorkshire Water and United Utilities as an aspect of the EPSRC NEPTUNE project (EP/E003192/1, www.neptune.ac.uk/). Follow on paper “Improved Control of Pressure Reducing Valves in Water Distribution Networks” will be published in Journal of Hydraulic Engineering, vol. 134(1) January, 2008.

Journal of Hydroinformatics

Pipe re-sizing of water distribution networks (WDNs) aims at improving the service performance to... more Pipe re-sizing of water distribution networks (WDNs) aims at improving the service performance to the required level, while minimizing the cost of replacing pipes in the network. The main challenge comes from the identification of the most effective pipes to re-size from a large number of interacting components. Performing a global search over all pipes in large WDNs does not guarantee a feasible and efficient solution due to the enormous search space, even by employing advanced algorithms, e.g., evolutionary algorithms. This paper proposes a novel method to reduce the search space for optimal re-sizing based on topological metrics from Complex Network Theory and hydraulic metrics, while providing suboptimal solutions comparable to the full search solutions, i.e., considering all pipes as candidates. The topological metrics are based on the edge-betweenness tailored for WDN analysis. Hydraulic metrics are unit head loss and flow rates of pipes computed based on simulation of the WDN...

Journal of Water Resources Planning and Management, 2021

IFAC Proceedings Volumes, 1980

IFAC Proceedings Volumes, 1987

IFAC Proceedings Volumes, 1989

Consideration is given to the problem of evaluating optimized control schedules for a class of mu... more Consideration is given to the problem of evaluating optimized control schedules for a class of multi-source and mult i-reservoir water supply systems. The systems are characterized by having only fixed speed pumps and by weak hydraulic interactions. For these systems the major operating costs are associated wit h electr i city charges for pumped source supplies and with the operation of treatment plants. A complete theory of a solver for the optimal scheduling problem i s presented. Numerical results of the solver application to Yorkshire Water Gr i d are shown and discussed.

Measurement and Control, 1999

ing and treating water. The formula for pump energy cost includes a pump efficiency factor. The p... more ing and treating water. The formula for pump energy cost includes a pump efficiency factor. The pumping cost also depends on the electricity tariff. There are different pricing options offered by the power utilities, the simplest being a unit electricity tariff where a price is paid for a unit of electrical energy. The tariff is usually a function of time with cheaper and more expensive periods. Sometimes maximum demand tariffs are also applied where a cost is incurred for the peak power consumption within a period (e.g. one month). Clearly, the type of tariff affects the time horizon of the scheduling task. The time horizon is typically 24 hours for unit tariffs, and I month for maximum demand tariffs. Objective functions may also include other cost terms for pump switching, penalties for deviation from the final target reservoir levels, etc. The optimisation problem will be considered over a given time horizon. The operational cost is represented by a unit electricity charge and a unit water treatment cost, but other costs can be added as required: (6) 1. 1 r/J = ~ fy~(t)f/qi(t), d(t))dt + ~ Hit) x rlit)dt jEfp to jEf,. to (I) where [ ~~ ] is a vector of node heads, hf is a vector of heads at reservoir nodes (fixed grade nodes) and he is a vector of heads at connection nodes; q is a vector of branch flows; qf and qs are vectors of reservoir flows and source flows respectively (both occurring at network nodes); d is a vector of nodal demands; and Ae,!''J are node branch incidence matrices for connection nodes and reservoir nodes respectively. The system of equations (2) to (5) can be classified as a system of differential-algebraic equations where equation (2) represents the differential part and equations (3) to (5) are the algebraic part. The vector variable e(t}, which appears in the component equation (3) is a decision variable and represents pump and valve control. The vector of source flows qs in (5) is another decision variable. Most of the components do not include decision variables (eg, equation 6 for pipe sections): Ri I qi(t} 10.852 x qi(l} =hLiit} hjeslt) Vector function hJt}, hf.t}, q(t}, q,(t} are internal variables of the model, vector hf is a differential variable and he' q, qf are algebraic variables. Operational Constraints Transformation of the network scheduling problem into a non-linear programming problem Operational constraints are applied in operational scheduling problems to keep the system-state within its feasible range. Practical requirements are translated from the linguistic statements into mathematical inequalities. The typical requirements of network scheduling are concerned with reservoir levels (water network state variables) in order to prevent emptying or overflowing, and to maintain adequate storage for emergency purposes. Similar constraints must be applied to the heads at critical connection nodes in order to maintain required pressures throughout the water network. The control variables, such as the number of pumps switched on, pump speeds or valve positions, are also constrained by lower and upper constraints determined by the features of the control components. The constraints on the control variable corresponding to water production reflect the properties of the water treatment processes. The constraints may be instantaneous or functional constraints covering a period of time. The functional constraints can represent, for example, total water production, or a limitation on the rate of change in water production. (7) min /11ax hf s hjt} S hf for lE [ to, If 1 Network Model where i p is the set of indices for pump stations and is is the set of indices for treatment works. The term Jj(qJ(t) , cl(t)) represents the electrical power consumed by pump station j. The potential energy of the water is obtained by multiplying the flow (q) and the head increase across the pump station. The consumed electrical power can then be calculated from the pump efficiency. The head increase variable flhi(l) can be expressed in terms of flow in the pump hydraulic equation, so that the cost term depends only on the pump station flow qi(t) and the control variable d(t) as illustrated in equation (1). The d(t) vector represents the nl,lmber of pumps on and/or pump speed. The function yt(t) represents the electrical tariff. The treatment cost for each treatment works is proportional to the flow output with the unit price of yf(t). The ontology of the hydraulic model is formulated in the paper by Ulanicka et a14 . The fundamental requirement in an optimal scheduling problem is that all calculated variables satisfy the hydraulic model equation.s. The network equations are non-linear and play the role of equality constraints in the optimisation problem. It is convenient to use a compact vector-matrix notation for writing down the network equations (see references4&5) as follows: dhf d1 = -S-1 qjt) reservoir dynamics (2) R(q(t), e)q = f,T h(l) component equations (3) Ae q(l) = -d(t) mass…

The application of the analytic hierarchy process (AHP) to help select the best option for the lo... more The application of the analytic hierarchy process (AHP) to help select the best option for the long-term design and upgrading of a water distribution network is described and applied to a sample network. The main criteria used are: reliability-based network performance; present value of construction, upgrading, failure and repair costs; and social and environmental issues. The AHP is a versatile and robust tool which can handle both qualitative and quantitative data, based on a simple method of pair-wise comparisons. It has been applied elsewhere on various problems, but not on the long-term upgrading of water distribution networks. Herein, the pipes are sized to carry maximum entropy flows using linear programming while the best upgrading sequence is identified using dynamic programming. The results demonstrate that the cheapest option is not necessarily the best when other factors e.g. performance and socio-environmental concerns are considered in an explicit way.

Proceedings of the CCWI '03 Conference, London, 15-17 September 2003, 2003

Journal of Optimization Theory and Applications, 1991

A theory for the optimization of nonlinear hydraulic systems is presented. The problem has been s... more A theory for the optimization of nonlinear hydraulic systems is presented. The problem has been solved in spite of the nonlinear system model and the mixed-integer nature of the decision variables. The optimization problem is formulated in terms of the time-distribution-function concept. This leads to a numerically efficient two-level algorithm. No specific control model is needed: the algorithm employs a system simulator. The general approach is also applicable to other nonlinear systems. The paper concludes with a practical application, together with numerical results.

In today's developed society it is fully expected that every household is provided with general u... more In today's developed society it is fully expected that every household is provided with general utility products such as heating, lighting, water supply, communication, and waste removal. Provision of these utility products requires large and complex physical, economic and social structures that interact and are interdependent. Furthermore, we underline that each distinct utility product (communication, transportation, water, etc.) provided to our households incurs similar material and embodied energy expenses. But are such structures and their respective expenses really necessary? Or could energy (and other resources) be saved by reducing redundant utility infrastructures, while still maintaining services to the households? Conventional approaches to improved utility provision focus on better management models with optimization, enhanced handling, and increased efficiency in organisations. This paper, on the other hand, presents a novel and radical idea to address this complex problem, by moving from the management level to the scientific & technological level. The paper challenges the need for distinct utility infrastructures for household utility products provision. In particular, the paper discusses the emerging scientific and technological options for using a single energy-provision infrastructure, which would potentially deliver the full set of household utility services.

IFAC Proceedings Volumes, 1998

Operational control systems and management information systems have traditionally been designed a... more Operational control systems and management information systems have traditionally been designed and implemented separately, despite the fact that both systems serve the same strategic objectives. Water companies operate physical processes and infrastructures in order to provide water to customers in terms of water quantity and quality, and to satisfy economic objectives. This is achieved by taking decisions and executing activities. The set of decisions and activities which are directly related to the control of the physical processes is called the Production Management System (PMS). The paper proposes an approach for considering management activities and operational control activities within a common framework and a new technique is proposed for modelling and design of an integrated Production Management System in a water company.

Civil Engineering and Environmental Systems, 2001

Fouling is a term describing progressive reduction of membrane permeability during filtration of ... more Fouling is a term describing progressive reduction of membrane permeability during filtration of solutes and suspensions. The problem with fouling lies in its complexity and our lack of under- standing of the science behind it. In wastewater treatment applications the problem is addition- ally magnified by polydispersity of wastewater suspensions. For these reasons fouling models in wastewater treatment applications are usually black-box or grey-box. Theoretical/classical fouling models are available but are applied predominantly to monodisperse suspensions where one fouling mechanism dominates and hence, only one classical fouling equation suffices to describe the filtration process. In wastewater applications we need to solve several equations simultaneously in order to be able to predict different stages of the filtration process. This paper presents such a model which combines three classical fouling mechanisms: blocking, constriction and cake growth. The paper shows successful ...