An original multi-objective criterion for the design of small-scale polygeneration systems based on realistic operating conditions

An original multi-objective criterion for the design of small-scale polygeneration systems based on realistic operating conditions
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  Copy accepted for publication. Reference for the article:   A. Piacentino, F. Cardona.  An srcinal multi-objective criterion for the design of small-scale  polygeneration systems based on realistic operating conditions . Applied Thermal Engineering, 2008, Vol. 28, Issues 17-18, p. 2391-2404.   An srcinal multi-objective criterion for the design of small-scale polygeneration systems based on realistic operating conditions A. Piacentino * , F. Cardona DREAM – Department of Energetic and Environmental Research Engineering Faculty – Università di Palermo Viale delle Scienze, 90128 Palermo Abstract The optimal design and operation of cogeneration and trigeneration systems for buildings applications is a complex issue, which has been investigated by several different approaches. Both the two basic management strategies, namely heat-tracking and electricity-tracking, have advantages and drawbacks in terms of operating results and may lead the plant designer either to undersize or oversize the CHP unit with respect to the optimal lay-out. Experimental works have demonstrated how the actual on-site performance of small scale polygeneration systems significantly differs from their expected operation, due to the need for a regular plant operation and the effects of outages for scheduled or unscheduled maintenance activities. After pointing out that heuristic approaches based on demand duration curve are weak instruments for plant design optimization, a more refined method is proposed, based on realistic operating conditions. The method integrates results of previous researches, like the proven convenience in using a duration curve of the “aggregate thermal demand” and in adopting flexible and techno-economically feasible management strategies; it is also based on srcinal indicators to be used for the real time optimization of plant operation. The proposed hybrid management criterion represents a good compromise between  profit oriented   and energo-environment    oriented   solutions, ensuring the combined production system to be eligible for support mechanisms. Finally, the method is applied for demonstrative purposes to a large hotel situated in Italy; implementing the innovative phases of the method by successive steps allowed to recognize what margins for profitability and energy saving each phase provides. Keywords : cogeneration, trigeneration, management strategy, energy saving, optimization, plant design * Corresponding author. Tel: +39 091 236302, Fax: +39 091 484425 E-mail address: piacentino@dream.unipa.it (A. Piacentino)  Nomenclature ATD Aggregate thermal demand [kW] TSS Total supply spread ATD *  Modified aggr. thermal demand [kW] C Cooling Greek letters  CHCP Combined Heat, Cooling and Power η  Efficiency, dimensionless CHP Combined Heat and Power Γ  Surplus heat production factor CHP prof   CHP profitability [€/hour] CHP prof,unit  Specific CHP profitability [€/kWh t ] Subscripts  COP Coefficient of performance abs Absorption chiller E Electricity [kW] CHP-min Minimum acceptable CHP size ESFL Energy supply at full load e, t, c Electrical, thermal and cooling ET Electricity tracking fuel Fuel consumed by the CHP unit F Chemical energy associated to fuel flow [kW] hp Reversible heat pump for cooling H Heat i Referring to the i-th hour HLV Heat Low Value [kJ/Sm 3 ] indirect For indirect uses, i.e. for feeding the absorption chiller HT Heat tracking min, max Minimum and maximum value LL Load level of the CHP unit, dimensionless prod Produced MP Market price ref Reference value for separate production P x  Capacity of the x-th component tot total PES Primary energy saving PHR CHP  Power to heat ratio of the CHP unit, dimensionless Symbols SS Spark spread ⋅ X Rated output of the X type of energy [kW] 1.   Introduction Despite the recognized potential for Combined Heat and Power (CHP) and Combined Heat, Cooling and Power (CHCP) applications in buildings, such systems actually cover a negligible share of the installed capacity, even in large buildings of the tertiary sector where a major profitability could be achieved. Difficulties in making small-scale polygeneration viable have a various nature: tariff volatility, legislation dynamics at the initial stages of the free energy market and non-deterministic behaviour of internal energy demand. Also, the profitability of polygeneration systems heavily depends on plant lay-out, size of components, management strategy, control system effectiveness and energy prices, that is why the optimization of small scale cogeneration and trigeneration systems is not a trivial issue, which has been widely investigated adopting different approaches. Optimization procedures can be found based on thermodynamic analysis and energy consumption calculations [1,2] and linear programming models which adopt economic objective functions, eventually including different scenarios for the stochastic  variables involved [3,4]. Also, heuristic approaches have been adopted, based on the cumulative curve of energy demand [5] or on enhanced immune algorithms coupled with appropriate rules [6]; such approaches are usually oriented to determine “physically meaningful” solutions which do no result from a pure mathematical optimization. The choice of an appropriate objective function is complex too: a main difficulty consists of finding a good compromise between a profit-oriented plant design, which may be determined basing on the Internal Rate of Return (IRR), the Net Present Value (NPV) or the Payback Time (PT), and a design oriented to maximize the social-   benefits , i.e. the primary energy saving or the reduction in pollutant emissions. Furthermore, being assessed as “high efficiency CHP” (no specific legislation for CHCP plants exist) becomes more and more important under the growing regulatory framework and support mechanisms concerning cogeneration [7]; in fact, energy/pollutant-emissions saving oriented and profit oriented optimizations actually interact, because depending on the magnitude of the incentives to be fixed on harmonized bases in European Union (EU) countries, the internalization of “social cost” is expected to influence increasingly the profit-oriented optimizations. Hence, the need for a multi-objective decision function or a constrained optimization (constraints expressed by minimum energy savings to be assessed as environment-friendly system) is evident. In this paper an srcinal approach to the optimization of polygeneration systems is proposed, which takes srcins from the analysis of few basic concepts: 1.   Design of grid connected CHP or CHCP systems covering a variable energy demand cannot be effectively optimized with no regard to the optimization of management philosophy; these two aspects are strongly interrelated [8] and algorithms for the integrated optimization of design and operation are needed; 2.   The internal demand variability plays a primary role in polygeneration applications for buildings, as evident in [9] where a rigorous approach to model the fluctuations from the average load and compute the effects on system’s performance is presented; 3.   Being electricity price highly variable on hourly basis, in order to maximise the profit a flexible management strategy should be pursued, to be optimized hour by hour. Thus, the adoption of a heat-tracking or an electricity-tracking operation should not represent a binding constraint. In this paper, appropriate indicators will be proposed to deal with hourly optimization of management strategy; 4.   A technically feasible operation should be ensured and kept into account since the optimization of design and operation. In this sense, the conventional approach to heuristic methods like the  maximization of the energy supplied at full load operation on the duration curve of heat demand [10] will be conveniently adjusted; 5.   The bi-directional power exchange with the grid, the dispatching priority for CHP electricity and the expected growth of Distributed Generation in energy supply of developed countries suggest more and more to focus on polygeneration systems as power producer and not only as “system dedicated to a single costumer”. This approach, usually adopted for large industrial applications with low demand variability [11], may reveal effective in extending CHP/CHCP viability even for small scale applications; obviously, it could be exploited only in case of favourable tariff context; 6.   A sufficient overall efficiency to have the polygeneration system assessed as “highly efficient” according to the legislation in force should be achieved. It could be noted that, in this paper, many general assumptions on economic viability refer to both CHP and CHCP plants, here indicated with the general term of  polygeneration ; on the contrary, when we will talk about the “combined production unit” or “prime mover” in particular (either gas turbine or reciprocate engine), the term “CHP unit” will be used. Solutions are available in literature for several specific problems. The optimization of plant operation, for instance, has been accurately investigated: a methodology based on genetic algorithms was proposed in [12], while a different approach was suggested in [13,14], based on the definition of a discrete number of “operation modes” and on their scheduling in strict relation to the variable price of electricity. However, the integrate optimization concept indicated as “item 1” in the above list has been rarely implemented. This paper focuses on a very relevant aspect for polygeneration applications, that is the CHP unit sizing. In [15] the assessment of CHP feasibility was shown to represent a complex and multidisciplinary task; in the same work, the problem of plant sizing was said to be solvable by choosing between “thermal match” and “power match” approaches. However, being evidently inconvenient to size the CHP unit on the peak of either thermal or electrical loads, the “thermal match” and “power match” sizing concepts offer different practical sizing options. In the following of this paper, data concerning electricity, cooling and heat demand are assumed known on hourly basis; in real world applications, in fact, performing accurate energy audits is always recommended to achieve reliable results, thus reducing the risk related to the high cost of polygeneration systems.  2.   Duration curve-based plant design: main drawbacks The capabilities of heuristic methods based on demand duration curve are well recognized: by relating each demand level range with the annual number of hours where such a demand may be observed, it allows to predict roughly the possibility for an effective operation of systems of different sizes and the amounts of energy they could supply. A common practice, oriented to the selection of a CHP capacity corresponding to the maximum amount of energy annually supplied at full load (ESFL), may be simply implemented by plotting the  full load energy curve described in [10]. This approach is usually applied to the “heat load duration curve” for a clear reason: being the power to heat ratio of the prime mover (PHR CHP ) constant or slightly variable and being the corresponding ratio on the demand side PHR dem  highly variable, sizing and operating the system on the heat load (heat-tracking management) ensures to maintain a high overall efficiency and not to reject large amount of surplus heat (that could result by an electricity-tracking management). The use of the full load energy curve prevents dramatic undersize or oversize of the CHP unit, providing a good compromise between the requirements for a high capacity system capable to cover a good fraction of annual heat demand and for a sufficient annual operation at high load levels. However, a plant design based essentially on the duration curve can be considered quite rough, due to the several limits of this method which may be summarized as follows: –   Its exclusive use is in contrast with the need for an integrated optimization of plant design and operation. Sizing on the base of heat load duration curve and assessing the annual operation time is equivalent to impose “a priori” a heat-tracking operation for the whole year; –   Being heat and electrical load profiles independent one each other, if a heat-tracking operating mode is assumed it will not be possible to predict net power exchanges with the grid. In fig. 1 this concept is put into evidence. For the x-th hour of a day, a prime mover with rated thermal and electrical capacities max H ⋅ and max E ⋅ (represented on the right in figure) is assumed to be HT-operated, resulting in an 80% load level; depending on the shape of the electrical profile (two cases are plotted in figure), this could lead either to large surplus or deficit (case b  and a , respectively) power production and, consequently, large amounts of energy to be sold or purchased from the grid. This aspect would not emerge from the analysis of the heat load duration curve only; –   The last item has relevant economical effects, being the unit price of electricity highly variable between peak and off-peak hours. Heat demand duration curve does not provide any information concerning “if and when (i.e. at which price)” energy exchanges take place; evidently, this is the
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