WATER SOFT: optimization of water use and Milano, Italy · 2014. 5. 16. · WATER SOFT:...

WATER SOFT: optimization of water use and

reuse in power plants

F. Sigon/ C. Zagano,* M. Rovaglio^

°ENEL Spa, R&D Division, Environment and Materials Research

Center, ViaRubattino 54, 20134 Milano, Italy

D̂ipartimento di Chimica Industrial edlngegneria Chimica, "G.

Natta" Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133

Milano, Italy

Abstract

The most challenging target in the industrialized countries will be thedevelopment of an effective management of the environmental impact due toindustrial activities. At the RIO Conference a precise statement, on theoptimization and prioritization of the water uses, was approved in the Agenda21: human needs being to be preserved. A new aptitude in designing industrialprocesses and plants is required. ENEL therefore developed theWATER SOFT code to analyze and to foresee the performances of existing"water system" of its power plant. This code is providing the capability toassess the impact of alternative technologies and processes and to re-designadvanced configurations with equivalent performances and betterenvironmental impact (lower water requirements and minimum wasteproduction). Comparison between predicted and experimental data has beenreported for a complex industrial application. Such results confirm thereliability of the simulation model here presented. Extension of this code tostudy alternative process configurations are also investigated.

1 Introduction

Water is the most used fluid for energy production all over the world. Thewater need can be estimated around 0.5-2 1/kWh for power plants based oncooling tower technology, while for applications using "through-condenser" thewater requirement grows up to 100-110 1/kWh. However, such amount cannotbe considered a real consumption since the water, after use and minor chemicaltreatments, is entirely released with only a negligible temperature increase.Along the cycle water consumption can be generally estimated in 0.17 1/kWhfor conventional plants but such value can be strongly reduced to 0.025-0.051/kWh by improving the technology related to the adopted physicochemical

Transactions on Ecology and the Environment vol 10, © 1996 WIT Press, www.witpress.com, ISSN 1743-3541

564 Computer Techniques in Environmental Studies

treatments (Queirazza et al., 1995). Such decrease allows to reduce the kWhoperating costs and to follow the environmental politics about consumptionminimization of natural utilities for industrial production.From these considerations, the greatest interest for such investigating tools isexpected to analyze, improve and optimize the adoption of water relatedtechnologies in the power industry and generally in the process industry.With particular reference to power plants, the "water-system" can be defined asthe complex of fluxes and treatments finalized to the production of operatingfluids (industrial water and demineralized water), to the use of such fluids(cleaning, conservation treatments, etc.) and to the waste water disposal. Thesequence of the process treatments is generally based on an "open-cycle"configuration where the inlet water is completely returned after a single use inthe water system. Such a structure can be adopted only when the followingconditions are satisfied:• total and unlimited water sources of low cost;• outlet streams easy to clean before their draining off;moreover, the following features must be also taken into account:• high consumption of water and chemical reactants;• high sludge production.The water system optimization can be achieved by different topological choiceswhich can lead progressively to a configuration named "closed-cycle". For suchpurpose the following aspects are of a specific interest:• optimization of the water treatments plant management;• reuse of process water and/or use of alternative sources (e.g.: rainwater);• new technologies for water treatments to be added or substituted to the

existing ones.Since the number of alternative plant configurations to be evaluated becomesvery high and moreover there is a large number of data to be consideredtogether with a complex plant structure, related to the presence of internalrecycles, a suitable simulation tool is strongly recommended.WATER_SOFT is a specific software designed and developed to simulate thesteady-state conditions of any plant configuration with the aim of finding outthe optimal solution related to the minimization of water need, reactantsconsumption and amount of waste and sludge produced. The analysis throughsuch a simulation tool has the following advantages:• to compare several process configurations on the basis of the prediction of

their performances;• to reduce time and developing costs for new process configurations

supporting the experimental validation through pilot plant only for the mostpromising technologies;

• to solve complex plant structure where the presence of an high degree ofrecycles requires a robust and reliable numerical algorithm for the evaluationof each single unit capability together with the global plant performance.


Computer Techniques in Environmental Studies 565

2 Solution approach

Before any description of the unit models adopted, it is important to specify theobjectives which must be reached through the simulation model itself. Namely,three are interesting for a specific mention:• model capability to represent existing apparatuses and new solutions

proposed by the end-user;• choice of the correct description scale which allows to verify the unit

performances in terms of outlet composition streams without introducingdetailed phenomenologies related to the internal system behavior;

• input/output models which can be easily introduced in a more generalprogram able to simulate, in a reasonable computing time, a complexscheme.

The achievement of such objectives is strictly related to the "solution approach"adopted to numerically solve the problem here examined.In literature two main approaches are often mentioned: "Sequential Modular"and "Equation Oriented". They have been analyzed, discussed and compared inseveral application examples typical for chemical plant flowsheeting. For detailssee reviews of Pierucci (1978), Westerberg (1979), Evans (1984).WATER_SOFT is based on a sequential modular approach where in an openfunctional architecture, "modules" and "connecting lines" can be used torepresent a water system through simple block schemes. Modules can be easilyassembled to build any plant configuration.Each module represents one apparatus related to the water treatments: filters,deareators, clarifiers, reverse osmosis, etc.. The connecting lines correspond toinlet and outlet fluxes represented by information vectors (flowrate,composition, pH, temperature, enthalpy, etc.).

Table 1: WATER_SOFT unit modules categorized on the speciestreated/removed

TOTAL DISSOLVED SOLIDS TOTAL SUSPENDED SOLIDSreverse osmosis gravity separationmechanical evaporation coagulation, flocculation, clarificationstaged evaporation granular media filtrationion exchange membrane filtration

DISSOLVED ORGANICS HEAVY METALSaerobic biological oxidation chemical precipitationanaerobic biological oxidation ion exchangechemical oxidation reverse osmosis

DISSOLVED GASESair strippingsteam strippingion exchangebiological nitrification



The simulation model for the different units have been developed on boththeoretical base and information derived on experience and the technicalspecifications supplied by vendors. With the aim of reducing the computingtime, the model has been generally derived from simple equations which allowthe evaluation of the whole system performances (reactants and energyconsumption, outlet composition, operating costs, etc.). However, somealgorithms are more complex and consequently the corresponding modelsdeveloped require specific attention (e.g.: pH and precipitation which involvesthe evaluation of chemical equilibria). A list of modules (representing unitoperations) and their use is summarized in Table 1.Since the global algorithm is based on a sequential modular approach, eachsingle module can be updated, modified or changed without compromising orinfluencing the basic code structure.For the solution of the recycle problems, WATER_SOFT adopts a sequentialsolution strategy using a convergence algorithm based on evolutionary models(Boston 1980, Rosen 1980, Westerberg 1981). They enable an approximatedrepresentation of the overall block scheme through reduced simulation modelswhich contain evolutionary parameters updatable along the convergence loop.This solution technique has been chosen for its greater efficiency andconvergence velocity with respect to alternative methodologies (Pierucci,1982).During a simulation, the operating conditions of each unit are verified andautomatically compared with the nominal design conditions. Warnings andother messages highlight when process constraints are violated (minimum ormaximum pH, maximum temperature, maximum pressure drops, etc.).Unit and plant performances are summarized through three different indexes:• Merit function which is related to the functional condition of the unit

assuming as optimal the average point equidistant from process constraints.A weighted sum of the units merit function allows to define the global plantmerit function.

• Water quality given in terms of composition and compared with operatingspecifications or law limits.

• Operating costs corresponding to unit and plant costs evaluated on the basisof reactants and energy consumption.

3 Experimental Validation

The effectiveness of the developed software and its applicability as a reliableand useful tool in correctly simulating the performances of a real plant areillustrated by the analysis of a typical water system of a thermoelectrical powerplant located on a river and of some alternatives for its configurations.The complete plant, sketched in fig. 1, can be schematically divided in fivesubsystems:1. Industrial water production. A clarifier/softener allows a first water hardness

reduction then followed by sand filters which retain most of the suspendedsolids.



8

1

Ife

•SP



2. Demineralized water production. A train of different ion exchanger resins(cation exchangers, anion exchangers and mixed beds) and a vacuumdeaerator drastically lower the silica and ion presence inside the main waterstream.

3. Industrial water utilities especially required for washing most of filters anddevices.

4. Demineralized water utilities, used at 90% to make up the boiler feed water.In this section the washing water from the filters of the boiler system isadded. Before, the washing water is purified by a cake filter and a mixed bedion exchanger.

5. Waste water treatment. All the water streams from the utilities and processunits are collected and treated to match the law constraints before theirdischarge.

The complete scheme to be solved results of a very large dimension:• 90 different units, considering mixers and splitters;• more than 200 streams containing about 30 different species;The difficulties in the numerical solution are increased by the presence ofrecycling streams.Another problem to be faced is the correct definition of all the inlet streams, notonly in terms of quantity, but mainly of composition. As a matter of facts,together with the river water, whose average composition can be consideredsufficiently constant, and the known chemical reactants introduced by theoperators, there is the need of identifying the species coming from the differentutilities (both from plant and domestic uses). This last contribution to the totalamount of water treatment must be carefully managed, changing periodically ina drastic way. Boiler or filter washing occurs only sometimes and for shorttime. It is then necessary to individuate an appropriate operation average timeto average these conditions. In our analysis one year average has been chosen.Of course, this approximation can give wrong information in different localsituations, particularly when strongly non linear models are involved (likechemical equilibrium). Table 2 shows a schematic comparison of the predictedand measured values for the water and sludge released to the environment froman hipothetic power plant. Despite the necessary approximations, assumptionsand the difficulties in measuring all the inlet compositions, a fine agreement hasbeen obtained. It is worthwhile remembering that, as above discussed, reactantspecies (for instance Ca(OH)2, FeClg, HC1) are averaged on the yearconsumption and that the salt precipitation equilibrium is often very sensitive tothe solution pH: small variations in the operative conditions can bring to verydifferent equilibrium conditions. Moreover, it is important to predict therelative presence of each specie and the trends of their amounts with respect todifferent operating conditions or process alternatives.It must be underlined, even though there is an high number of equations andrecycles, a single simulation of the whole plant can be performed in about 300 sCPU on an Alpha Vax workstation.



Tab. 2: Experimental and WA TER_SOFTpredicted compositionof the water and sludge released from an hypothetic plant

Chemical species

Na+K+Ca^Mg++Fe"+Cu*+Ni*+Zn^Co=+Mi%2+Pb=+V"Al"+Cr^cr

COz+HCOs+CO]NOg"P04'-sorNH/SiOz

TOTAL

Experimental data:Water Sludge(%) (%)17.430.4920.722.510.03


By the simulations, we derive three evidences:• 30% increase of inlet river water• 20% decrease of discharged salts• 15% increase of sludge disposal.The increase of water need is due to the larger amount of water to betreated by the reverse osmosis treatment to get the same output flowrate.Nevertheless, the discharge stream contains a significant salt reductionbecause of the lesser use of chemical reactants.Alternative 2: Water ReuseTo reduce the water inlet from the river, the 90% of the stream sent to theneutralization (fig. 1) is recycled back to the initial clarifier /softener.By thesimulation we derive the following:• 60% decrease of inlet river water• 280% increase of discharged salts• 20% decrease of sludge disposal.The sludge reduction is a direct consequence of the lower need of riverwater. The substantial salt increase in the discharge stream is determined bythe chemical reactants for the ion exchange resin regeneration. As a matterof facts, the river water presents about 320 ppm of salts inside, while therecycled stream contains more than 20,000 ppm of ions in solution. Thatmeans a reduction of ion exchanger run time and a consequent morefrequent regeneration.Alternative 3: Reverse Osmosis and Water ReuseThis configuration is the sum of the previous ones. The rationale of thischoice is that the recycle stream can decrease the river water feed andcompensate for the water need of the membrane system. Moreover, the lackof chemical reactants in the reverse osmosis allows to avoid the growth ofthe salt presence inside the plant. The benefit of the introduction of thewater reuse is not any more damaged by the need of large amounts ofchemical reactants. The new input/output conditions, in respect with theactual configuration, are then evaluated by the simulation results:• 45% decrease of inlet river water• 70% decrease of discharged salts• 30% decrease of sludge disposal.The advantages of alternatives 1 and 2 are maintained, while disadvantagesare almost canceled by their combined use. Only membrane exhaustion ismore rapid in comparison with the simple introduction of reverse osmosis:the recycle stream in the present configuration contains about 2000 ppm ofsalts in solution (about 10 times higher than river water).

Simulation results of the different process alternatives is summarized in Tables3-5.Table 3 shows the unit and plant merit index (Queirazza et al., 1996) scaledbetween 0 (bad operating conditions) and 1 (optimal operating conditions).From these results it can be underlined that the plant merit index does notchange significantly if all the units work within the correct operating range. In



particular, the merit index of alternative 2 and 3 shows that the process designis flexible enough to face a large amount of internal water reuse.

Table 3 : Units and Plant Merit functions

UNITClarifier /softenerSand filtersCation exchangersVacuum deacratorAnion exchangersMixed bed exchan.Cake filtersClarificrReverse OsmosisPlant

Actual Configuration1.00.630.840.710.740.670.611.0

0.72

Alternative 11.00.63

0.780.611.00.430.71

Alternative 21.00.630.600.710.600.670.611.0

0.67

Alternative 31.00.63

0.650.611.00.410.67

The quality index of the different water types are reported in table 4. This indexis related to the check between the water composition and the operating or lawlimits and rapidly approaches zero when one or more constraints are violated.WATERJSOFT simulations indicate that the primary clarify/softener is not ableto correctly operate in presence of a high recycle stream. As a matter of facts,alternatives 2 and 3 show a reduction of the industrial water quality index. Thissuggests either to reduce and optimize the recycle amount or to substitute theclarifier with a different unit (e.g. electrodialysis).

Table 4: Water quality index

Water typeindustrialdemineralizedwaste

Actual Configuration0.810.990.96

Alternative 10.810.950.97



Finally, table 5 compares the operating costs (reactants and energy) and clearlyindicate the significant reduction obtained through the use of reverse osmosiseven in presence of high internal recycles.

Table 5 : Plant Operating Cost Estimations

Operating costsdeminer. water

(Lit/m')

Actual Configuration

390.

Alternative 1

185.

Alternative 2

2390.

Alternative 3

145.

5 Conclusions

The optimization of the water system in a power plant is a very challengingproblem because it needs to proceed by multiple objectives (water quality,system operability, process costs) and to choose among multiple choices(processes, technologies, operating conditions). Therefore, the availability of a



suitable tool becomes necessary to analyze and to identify the best processalternative.As reported above, WATER_SOFT seems to be a reliable simulation toolwhich allows to represent qualitatively and quantitatively a complex watersystem.Moreover, synthetic information as the merit function and the water qualityindex or the operating costs evaluation allow to compare complex processstructure in a very simple and easy way. Simulation results clearly show that,with reference to a real application, significant improvements can be obtainedthrough the use of the WATER_SOFT analysis so reducing the environmentalimpact of the plant and the process operating costs.

References

• Queirazza G., F. Sigon, C. Zagano "L'esperienza straniera nel riuso delleacque nelle central! termoelettriche", ATI - Sezione Lombarda, Camogli (I),31 Maggio - 2 Giugno 1995

• Westerberg A. W. "Optimization in Computer-Aided Design", Foundationof Computer Aided Process Design, AIChE, New York, 1981

• Evans L. B. "Proceedings Symposium: Simulation et Conception Assisteespar Ordinateur des Precedes Chimiques", Institut du Genie Chimique,Toulouse (F), 1984

• Pierucci S., G. Biardi, E. Ranzi, M. Dente "Proceedings Symposium:Contribution des calculateurs electroniques au development du geniechimique et de la chemie industrielle", Paris (F), 1978

• Pierucci S., E. Ranzi, G. Biardi "Solution of Recycle Problems in aSequential Amodular Approach", AIChE journal, 28, 820, 1982

• Boston J. F. " Inside-out Algorithms for Multicomponent Separationcalculations", Computer Application to Chemical Engineering, ACSsymposium Series No. 124, 1980

• Rosen E. M. "Steady-state Chemical Process simulation: state of the artreview", Computer Application to Chemical Engineering, ACS symposiumSeries No. 124, 1980

• Westerberg A. W., H. P. Hutchison, R.L. Motard, P. Winter " ProcessFlowsheeting", Cambridge, (UK), 1979


WATER SOFT: optimization of water use and Milano, Italy · 2014. 5. 16. · WATER SOFT:...

Documents

Transcript of WATER SOFT: optimization of water use and Milano, Italy · 2014. 5. 16. · WATER SOFT:...