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Abstract: Innovative analytically based method to calculate corrected fuel consumption of parallel and series hybrid electric vehicles (HEVs) at balanced energy content of the electric storage devices is proposed and validated in the paper. The proposed analytical method is generally applicable and features highly accurate corrected fuel consumption results. It enables calculation of the corrected fuel consumption out of a single fuel consumption test run in a single analytic post-processing step. An additional fuel consumption test run might be needed to obtain highly accurate results if ratio of the energy content deviation of the electric storage devices to the energy used for vehicle propulsion over the test cycle is high. Proposed method enables consideration of non-linear energy flow changes and non-linear HEV component efficiency changes caused by the energy management strategy or by the component characteristics. The method therefore features highly accurate results out of the minimum number of fuel consumption test runs and thus optimizes workload for development or optimization of HEVs. The input data of the method are characteristic energy flows and efficiencies that are derived from the energy flows on selected energy paths of HEVs. [ABSTRACT FROM AUTHOR]

Abstract: Separation processes account for more than half of capital and operating costs in chemical manufacturing. Separations are the energy intensive operations in the chemical industry. Rising energy consumption combined with the environmental impact increases the need for energy saving separation processes. Fortunately complex column networks have the potential for major energy savings estimated to range between 30 and 70% over simple column configuration. In this paper, a computer-aided synthesis method is introduced to synthesize optimal complex column arrangements which encode the cost and states of global solutions with minimum user input. A robust feasibility criterion helps select design and operating conditions for the entire network that can be realized in practice. Our method builds on thermodynamic transformations entitled temperature collocation which provides crucial advantages to determine the operating conditions, structure, and size of the separation network for achieving the desired product cuts. The computational approach guarantees realizable column profiles, which can be validated with industrially accepted simulation software such as AspenHysys and AspenPlus. [Copyright &y& Elsevier]

Abstract: Cryogenic air separation, while widely used in industry, is an energy intensive process. Effective design can improve efficiency and reduce energy consumption, however, uncertainties can make determination of the optimal design difficult. This paper addresses the conceptual design of cryogenic air separation process under uncertainty. A rigorous, highly nonlinear model of three integrated columns is developed to capture the coupled nature of the process. The multi-scenario approach is used to incorporate the uncertainty, giving rise to a nonlinear programming problem with over half a million variables. Nevertheless, this problem is solved efficiently using Ipopt, demonstrating the effectiveness of interior-point methods on complex, large-scale nonlinear programming problems. The optimal design from the multi-scenario approach is compared against the optimal design using nominal parameter values. As expected, the results using the multi-scenario approach are more conservative than the nominal case; however, they may be less conservative than traditional overdesign factors. [Copyright &y& Elsevier]

Abstract: Coalbed methane (CBM) is an important global energy resource and liquefaction is suggested to best utilize it. Different from ordinary natural gas, CBM usually contains a high proportion of nitrogen, which cannot be removed by purification procedures applied in ordinary natural gas liquefaction processes. One approach for separating nitrogen from CBM is by distillation after liquefaction. In this way, nitrogen is liquefied together with methane, and the liquefaction system performance may change along with the nitrogen content of CBM feed gas. The liquefaction process adopting nitrogen expansion with propane pre-cooling is usually considered suitable for small-scale liquefaction plants due to its simplicity and is the focus of this paper. Taking the unit product liquefaction power consumption as the major index for analysis, optimum parameters of the liquefaction process for CBM feed gas containing different nitrogen contents are calculated. Based on the optimization results, the effects of nitrogen content as well as the other two important technical indexes (liquefaction rate and methane recovery rate) on system performance are also investigated. [Copyright &y& Elsevier]

Abstract: Several authors have pointed out the need to identify the optimum operating conditions (OCs) of autothermal thermophilic aerobic digestion (ATAD). This study proves the hypothesis that the OCs have the potential to substantially improve the energy efficiency and plant capacity of established ATAD systems. As ATAD is a semi-batch process, its energy efficiency has to be optimized via dynamic optimization (DO). This methodology requires an adequate mathematical model, and appropriate selection of optimization variables. The paper presents an improved mathematical ATAD model based on previous models found in the literature. A global sensitivity analysis (GSA) was performed in order to identify variables with significant influence upon energy efficiency and plant capacity, thus paving the way for the DO of ATAD systems. The results of the GSA show that reactor volume, reactor temperature, and aeration flowrate are significant variables, which is consistent with reported literature. The results of the GSA also show that both energy efficiency and plant capacity of ATAD systems can be substantially improved by altering reactor volume and OCs. [Copyright &y& Elsevier]

Abstract: The aim of this paper is to optimize the number of collectors for PV/T hybrid active solar still. The number of PV/T collectors connected in series has been integrated with the basin of solar still. The optimization of number of collectors for different heat capacity of water has been carried out on the basis of energy and exergy. Expressions of inner glass, outer glass and water temperature have been derived for the hybrid active solar system. For the numerical computations data of a summer day (May 22, 2008) for Delhi climatic condition have been used. It has been observed that with increase of the mass of water in the basin increases the optimum number of collector. However the daily and exergy efficiency decreases linearly and nonlinearly with increase of water mass. It has been observed that the maximum yield occurs at N =4 for 50kg of water mass on the basis of exergy efficiency. The thermal model has also been experimentally validated. [Copyright &y& Elsevier]

Abstract: In order to gain an extra increment of efficiency to compensate for capital costs, one of the main issues in the design of advanced supercritical power plants is the reduction of boiler exit gas temperature below typical values of conventional, subcritical units. Currently, the use of heat exchange surfaces made of plastic has become feasible, thereby avoiding corrosion and fouling problems derived from cold-end acid condensate. In this manner, flue gas temperature can be reduced down to typically 90°C, which obviously leads to an increase of boiler efficiency. Besides, there is an additional energy available for heating the main condensate flow of the power cycle. If modification of air–gas rotary heaters is also considered, a manifold of possibilities opens up for plant optimization and integration of components. The objective of this paper is to analyze this class of schemes for increasing power output and net efficiency of a reference supercritical plant. A complete simulation of the steam cycle is assembled using Aspen Plus and different plant configurations are examined under reduced exit gas temperatures. Several uses of flue gas energy are considered, taking into account limits of temperature and realistic efficiencies of heat exchangers. Mass flow rates, point of extraction of condensate, pressures and temperatures are selected heuristically to optimize performance. Finally, required exchange areas are estimated, and a cost analysis is carried out in order to economically assess the new configurations and estimate the additional profit for the plant. [Copyright &y& Elsevier]

Abstract: A parametric study and optimization is performed on a transcritical power cycle using six performance indicators: thermal efficiency, specific net output, exergetic efficiency, total UA and surface of the heat exchangers as well as the relative cost of the system. The independent parameters are the maximum temperature and pressure of the cycle as well as the net power output. Results show that it is impossible to simultaneously optimise all six performance indicators, i.e. that the values of the independent parameters are not the same for all the optimizations. The design value for these parameters is therefore a matter of choice, or compromise, among the combinations optimising the performance indicators. For a limited low temperature heat source the parametric studies reveal the existence of a maximum value for the net power output of the system and of another net power output minimising the cost per kW. A comparison of optimised results for three working fluids (CO2, ethane, R125) shows that the better fluid depends on the optimised indicator and clearly indicates that a simple first law analysis is not sufficient for the selection of a working fluid. In summary, this paper demonstrates the need to achieve a multi-point optimization and comparison in order to study adequately a transcritical power system. [Copyright &y& Elsevier]

Abstract: Control of energy flows within a building is critical to achieving optimal performance of heating, ventilation and air-conditioning (HVAC) systems. To design optimal HVAC control strategies, a dynamic model of the HVAC system – particularly the building zones that it services – is essential. As analysis of building energy consumption is facilitated by the accurate prediction of indoor environmental conditions, techniques that dynamically model HVAC zones are crucial, and as such, is an active area of research. This paper focuses on real-time HVAC zone model fitting and prediction techniques based on physical principles, as well as the use of genetic algorithms for optimization. The proposed approach is validated by comparing real-time HVAC zone model fitting and prediction against the corresponding experimental measurements. In addition, comparison with prediction results using an algorithm based on feedback-delayed Kalman filters has demonstrated the superiority of the proposed approach in terms of prediction accuracy. [Copyright &y& Elsevier]

Abstract: In this paper, the simulation of the performance of solar-assisted heating and cooling systems is analyzed. Three different plant layouts are considered: (i) the first one consists of evacuated solar collectors and a single-stage LiBr–H2O absorption chiller; here in order to integrate the system in case of insufficient solar radiation, an electric water-cooled chiller is activated; (ii) configuration of the secondly considered system is similar to the first one, but the absorption chiller and the solar collector area are sized for balancing about 30% of the building cooling load only; (iii) the layout of the thirdly considered system differs from the first one since the auxiliary electric chiller is replaced by a gas-fired heater. Such system configurations also include: circulation pumps, storage tanks, feedback controllers, mixers, diverters and on/off hysteresis controllers. All such devices are modelled for maximizing the system energy efficiency. In order to simulate the systems’ performance for dynamic heating/cooling loads, a single-lumped capacitance building is also modelled and implemented in the computer code. A cost model is also developed in order to calculate the systems’ operating and capital costs. All the models and the relative simulations are carried out by TRNSYS. A design of experiment procedure is also included. By such tool the effects of the system operating parameters’ variation on the relative energy efficiency are analyzed. In addition, the set of synthesis/design variables maximizing the system’s energetic performance can be also identified. The annual primary energy saving is chosen as the optimization objective function, whereas collector slope, pump flows, set-point temperatures and tank volume are selected as optimizing system design variables. A case study was developed for an office building located in South Italy. Here, the energetic and the economic analysis for all the three considered system layouts are carried out. The simulations’ results are referred to both the initial and the optimized systems configurations. The highest primary energy saving vs. the reference traditional HVAC system is reached by the first considered system layout. The economic performance of the investigated solar heating/cooling systems is still unsatisfactory. The economical profitability of the considered solar heating and cooling systems can be improved only by significant public finding. From this point of view, the best results were achieved by the second above mentioned system configuration. [Copyright &y& Elsevier]

Abstract: In this paper, we study the scheduling problem of jobs with multiple active intervals. Each job in the problem instance has disjoint active time intervals where it can be executed and a workload characterized by the required number of CPU cycles. Previously, people studied multiple interval job scheduling problem where each job must be assigned enough CPU cycles in one of its active intervals. We study a different practical version where the partial work done by the end of an interval remains valid and each job is considered finished if total CPU cycles assigned to it in all its active intervals reach the requirement. The goal is to find a feasible schedule that minimizes energy consumption. By adapting the algorithm for single interval jobs proposed in Yao, Demers and Shenker (1995) , one can still obtain an optimal schedule. However, the two phases in that algorithm (critical interval finding and scheduling the critical interval) can no longer be carried out directly. We present polynomial time algorithms to solve the two phases for jobs with multiple active intervals and therefore can still compute the optimal schedule in polynomial time. [Copyright &y& Elsevier]

Abstract: This paper presents, for the first time, a full custom layout design for a Data Dependent Permutation (DDP)-Cobra H64-bit cipher, using pipelining techniques in the internal rounds blocks to increase the throughput of the design. As a result, the silicon area and the power dissipation are reduced too. The design achieves a small area by simplifying the complex design by simpler designs. Low power consumption is satisfied by using low power logic gates. The throughput ranges from 5.5 to 8.4Gbps. Simulation results based on the layout level have confirmed the validity of the proposed technique, as well as have confirmed that low power, speed and performance can be optimized through design at the layout level. [Copyright &y& Elsevier]

Abstract: The design and optimization of a coupled multicomponent distillation system is a non-linear and multivariable problem. The complexity of this kind of problem results in high solving difficulty. This paper addresses the application of genetic algorithms to the optimization of intensified distillation systems for quaternary distillations. We used a multiobjective genetic algorithm with restrictions coupled to the Aspen Plus™ process simulator for the evaluation of the objective function. Several mixtures to test the effect of relative volatilities of feed mixtures on energy consumption, second law efficiency, total annual cost and theoretical control properties have been studied. Numerical performance shows that this design tool is robust and suitable for the design of coupled multicomponent distillation sequences. [Copyright &y& Elsevier]

Abstract: Most current research using optimization with building performance was restricted to simple geometry. It considered the building form as a box, polygonal shape, or simple curvature, restricting its applicability and integration with the design process. Generally, geometry variables including length, height, and depth usually control the objective values such as the area and volume of the building. Using these variables, the energy consumption data or simulation results per area or volume are compared to find the optimal form of the building. In addition, the algorithms used to predict performance in most of optimization studies are rather unsophisticated. There are technical constraints that are caused by specific problems that building simulation and optimization tools currently pose. For example, one major constraint can be lack of automated comparisons between different conditions and sharing geometry and boundaries with ease of operability. If the technical constraints can be overcome, building performance will much more easily be integrated into the design process. This paper introduces new method to control building forms by defining hierarchical relationship between geometry points to allow the user to explore the building geometry without being restricted to a box or simple form. It illustrates how the methodology allows the generation of optimized site-specific building form by integrating advanced simulation and optimization algorithm. [Copyright &y& Elsevier]

Abstract: In this paper, the problem of finding optimal paths in mobile ad hoc networks is addressed. More specifically, a novel bicriteria optimization model, which allows the energy consumption and the link stability of mobile nodes to be taken into account simultaneously, is presented. In order to evaluate the validity of the proposed model, a greedy approach is devised. Some preliminary computational experiments have been carried out, in a simulation environment. The numerical results are very encouraging, showing the correctness of the proposed model. Indeed, the selection of a shorter route leads to a more stable route, but to a greater energy consumption. On the other hand, if longer routes are selected the route fragility is increased, but the average energy consumption is reduced. [Copyright &y& Elsevier]

Abstract: This paper presents an optimization approach applied to a whole fuel cell (FC) air supply system including its geometry and its control. The aim is to optimize its power consumption along with its mass. Particle swarm optimization (PSO) algorithm is used to define the design parameters of both permanent magnet synchronous motor (PMSM) and a fuzzy logic controller (FLC). The results are compared with those obtained by a sequential optimization process and advantages of co-design optimization approach are clearly shown. Indeed, a significant reduction of the objective function (made up on both motor mass and energy consumption) on a considered operating cycle can be obtained. [Copyright &y& Elsevier]

Abstract: While it is possible to check the energy performance of a given building by means of several available methods, the inverse problem of determining the optimum configuration given a desired performance is more difficult to solve. In the Mediterranean region this problem is more complex due to the following two reasons: the air-conditioning load is as important as the heating load, and the energy needs depend on a high number of architectural parameters which have different, even contradictory, effects on summer and winter loads. In this paper we present an optimization algorithm that couples pseudo-random optimization techniques, the genetic algorithms (GA), with a simplified tool for building thermal evaluation (CHEOPS) for the purpose of minimizing the energy consumption of Mediterranean buildings. Since increasing the energy performance usually requires the use of special devices resulting in a high construction cost, we also propose to use GA for the purpose of economical optimization. [Copyright &y& Elsevier]

Abstract: Redundant thrusters are generally used for a reliable attitude control system. Also, redundant thrusters yield a better performance if they are used appropriately. In this paper, the authors propose an efficient redundancy management algorithm to reduce the fuel consumption. The algorithm is based on a linear programming problem which is a constrained optimization problem. For the algorithm, a cost function is defined as a quantity related to the fuel consumption for a maneuver. The independent variables are the thrusters'' on-times which are control input variables of a satellite dynamic model. The advantage of the proposed method is verified by numerical examples. The examples show that the proposed method consumes less fuel than an existing method for a given maneuvering command. A sub-optimal algorithm is also discussed for an onboard computation. The proposed algorithm is applied to two maneuvers: move-to-rest and rest-to-rest. This is verified by a numerical simulation. [Copyright &y& Elsevier]

Abstract: Performance optimization of a gas turbine engine can be expressed in terms of minimizing fuel consumption while maintaining nominal thrust output, maximizing thrust for the same fuel consumption and minimizing turbine blade temperature. Additional control layers are used to improve engine performance. This paper presents an evolutionary approach called the StudGA as the optimization framework to design for optimal performance in terms of the three criteria above. This approach converges fast and can potentially save on computing cost. Model-based experimental results are used to illustrate this approach. [Copyright &y& Elsevier]

Turbulent flow has a significantly higher drag than the corresponding laminar flow at the same flow conditions. The presence of turbulent flow over a large part of an aircraft therefore incurs a significant penalty of increased fuel consumption due to the extra thrust required. One possible way of decreasing the drag is to apply surface suction to delay the transition from laminar to turbulent flow. However, in order for the gain from the reduction in drag to outweigh the extra costs associated with the suction system, the suction must be distributed in an optimum, or near optimum, manner. In this paper two practical cases are considered. In the first of these a flat plate with panels whose positions are adjustable but do not overlap is treated. Since the cost function in this case is multi-modal, non-smooth and non-convex, methods for solving the optimisation problems necessary to design multi-panel suction systems based on direct search techniques are developed. In the second case considered the problem is that of linear distributed suction over the front part of an aerofoil. For this case, the computational load increases so significantly that in some cases it is not really feasible to continue the investigation using a single processor code. To overcome this, three parallel global optimisation algorithms are developed for the design of multi-panel suction systems on an aerofoil and it is shown that good solutions can be found efficiently. [Copyright &y& Elsevier]

This paper deals with the sink placement and anycast routing to increase the lifetime of multi-sink wireless sensor networks. Two algorithms are proposed, namely "Multi-sink Placement and Anycast Routing (MPAR)" and "Extended Multi-sink Placement and Anycast Routing (EMPAR)", to jointly address the problems of clustering, multi-sink placement, and load-balanced anycast routing. MPAR and EMPAR rely on a two-level architecture in which sensors are clustered at the lower level. Each sensor transmits its data to the corresponding Cluster Head (CH) via a load-balanced data aggregation routing tree. At the upper level, both schemes use a modified particle swarm optimization algorithm to determine the best location of sinks. For each sink, a high-level anycast routing tree is developed using the ant colony optimization algorithm. Each anycast tree uses the hybrid Compressive Sensing (CS) method to forward the aggregated data from CHs to sinks. Extensive simulations are conducted to illustrate the efficiency of the proposed algorithms in terms of energy consumption, energy consumption variance, and network lifetime. The results show that EMPAR has a better performance than MPAR due to its CH selection strategy. As an advantage, EMPAR considers both remaining energy and distance criteria along with a rest factor to select the best CH for each cluster. For an average number of clusters, EMPAR reduces the energy consumption by 5.98% and 12.20%, respectively, compared to the MPAR algorithm and the energy-aware CS-based data aggregation algorithm. It also increases the network lifetime in comparison with the aforementioned algorithms by 12.26% and 30.38%, respectively. [ABSTRACT FROM AUTHOR]

• A double MRT-LBM is used for studying active micromixing with an oscillating stirrer at a high Peclet number of 10000. • A cylinder viscous micropump system is used for the flow production, for the first time at the above-mentioned micromixer. • Effects of the stirrer diameter, maximum linear velocity, and oscillation amplitude are investigated. • Response Surface Method (RSM) is used for the system optimization. • Multiple response optimization is performed for simultaneous optimization of the integrated system. In the present paper, a double multiple-relaxation-time lattice Boltzmann simulation and response surface optimization are performed to optimize the performance of a novel active micropump-mixer at high-Peclet number flows. The micropump-mixer is comprised of rotationally oscillating rectangular stirrer and two identical square rotors. Effects of three important non-dimensional parameters of the stirrer, including its diameter (D S) , maximum velocity (U S) , and amplitude (K) are investigated on the mean mixing efficiency (ε o u t) , time-averaged of the instantaneous dimensionless averaged velocity (U a v e) , mixing energy cost (m e c) and pumping energy cost (p e c). All calculations are carried out for the non-dimensional U S and K in the range of 0.1 - 1 , and for D S in the range of 0.5−0.9, at fixed Reynolds and Peclet numbers of R e = 1 and P e = 10000. Results indicated that ε o u t increases with D S , and especially with K , while it displays a non-monotonic behavior with U S. Furthermore, U a v e and m e c decrease with increasing D S and K. However, U a v e is not influenced by U S variations, but m e c shows a decrease-increase trend with increasing U S. The p e c increases with increasing of all three parameters. Finally, optimization results indicated that non-dimensional values of 0.5, 0.702 and 1 respectively for D s , U s and K are optimum values for multiple-response optimization. [ABSTRACT FROM AUTHOR]

• Maximize renewable energy penetration through coordinated re-phasing of solar photovoltaic. • An automatic photovoltaic re-phasing switch that can connect to single-phase photovoltaic inverters. • A modified discrete bacterial foraging optimization to determine the optimum phase combination of photovoltaic systems. • The key mechanisms of discrete bacterial foraging optimization are modified to cater to photovoltaic re-phasing problem. • A contextually optimized initializer to improve the convergence speed of discrete bacterial foraging optimization. As combating climate change has become a top priority and as many countries are taking steps to make their power generation sustainable, there is a marked increase in the use of renewable energy sources (RESs) for electricity generation. Among these RESs, solar photovoltaics (PV) is one of the most popular sources of energy connected to LV distribution networks. With the greater integration of solar PV into LV distribution networks, utility providers impose caps to solar penetration in order to operate their network safely and within acceptable norms. One parameter that restricts solar PV penetration is unbalances created by loads and single-phase rooftop schemes connected to LV distribution grids. In this paper, a novel method is proposed to mitigate voltage unbalance in LV distribution grids by optimally re-phasing grid-connected rooftop PV systems. A modified version of the discrete bacterial foraging optimization algorithm (DBFOA) is introduced as the optimization technique to minimize the overall voltage unbalance of the network as the objective function, subjected to various network and operating parameters. The impact of utilizing the proposed PV re-phasing technique as opposed to a fixed phase configuration are compared based on overall voltage unbalance, which was observed hourly throughout the day. The case studies show that the proposed approach can significantly mitigate the overall voltage unbalance during the daytime and can facilitate to increase the usable PV capacity of the considered network by 77%. [ABSTRACT FROM AUTHOR]

• AGSO algorithm is proposed and implemented on economic cooling-load dispatch of multi-chiller plants. • Energy-saving capability of AGSO based OCL strategy is proved. • Numerical results of AGSO approach are compared with best solutions of recently published algorithms. • AGSO with fast convergence finds better solutions in lower calculation times. Improper operation of a multi-chiller plant would significantly increase associated electric consumption. This paper introduces a new model to determine the optimal loading point of the chillers. To do so, optimal dispatching of multi-chiller plant is expressed as an optimization problem and associated constraints are all together accommodated in the process of optimization. The problem is tackled by a new version of a metaheuristics approach. The proposed approach is entitled as augmented group search optimization (AGSO) algorithm, which is devised to avoid drawbacks of conventional group search optimization algorithm such as trapping in the local minima. The effectiveness and robustness of the proposed approach in comparison with available methods are studied through three well-known test cases. Numerical results demonstrate that AGSO with its strong exploration capability achieves a lower energy consumption than that of recently published methods with higher convergence speed. [ABSTRACT FROM AUTHOR]

• ICA is used for solving optimal chiller loading problem and saving energy. • Robustness and effectiveness of ICA is proved using simulations on three well-known test systems. • ICA based optimization process is compared with recently published methods. • ICA with fast convergence capability achieves better solutions in lower calculation time. The hour-ahead optimization of the multi-chiller systems is necessary in order to minimize their power consumption and save energy. In this paper, an imperialistic competitive algorithm based optimal chiller loading problem is solved to find the partial load ratio, cooling flux, and the electricity requirement of the chillers and minimize the energy consumption of the whole system. The proposed approach simulates the socio-political competition using the initial population composed of the colonies and imperialists. The empires with their relative colonies and imperialists compete with each other to collapse the weakest empire and dominate the most powerful one achieving the minimum power consumption. The cooling capacity of the chillers and balance constraint are satisfied in hourly economic dispatch process. The optimization problem is tested on three standard systems. The imperialistic competitive algorithm based optimal chiller loading method finds better operating points for chillers than those obtained by recently published strategies. [ABSTRACT FROM AUTHOR]

• A probabilistic optimal design method for cleanroom air-conditioning systems. • A probabilistic diversity factor method for quantifying uncertain space load diversities. • The design method offers optimal alternatives facilitating different ventilation strategies. • Proposed design method is validated in a case study referring to a practical building system. • Systems with least life-cycle costs and superior satisfaction of services can be obtained. Buildings with spaces requiring strict temperature and humidity controls, such as pharmaceutical cleanrooms and semiconductor/microchip factories, have been growing very quickly in terms of total floor area and energy consumption. In such buildings, much of the energy is unnecessarily wasted due to the incoordination of system design and operation/control, especially under "off-design" and ever-changing ambient and load conditions. This paper, therefore, proposes a probabilistic optimal design method for cleanroom air-conditioning systems facilitating optimal ventilation control under uncertainties. To consider the effects of asynchronous loads in different zones/spaces with reduced computation demand, a probabilistic diversity factor method is proposed which is a simplified method to quantify the effects of uncertainties of space load diversities in multiple zones/spaces using diversity factors. The proposed design method is implemented and validated in the design optimization of air-conditioning systems for implementing four different ventilation control strategies considering possible and uncertain off-design conditions. The energy and economic performance as well as service satisfaction of the air-conditioning systems are also evaluated and compared. Results show that the proposed design method can obtain the optimal air-conditioning systems with minimum life-cycle cost and superior satisfaction of service. [ABSTRACT FROM AUTHOR]