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Building thermal mass control has great potentials in saving energy consumption and cost. Optimal control schemes are able to utilize passive thermal mass storage to shift the cooling load from peak hours to off-peak hours to reduce energy costs. As such, this paper explores the idea of model predictive control for building thermal mass control. Specifically, this paper presents a study of developing and evaluating a multi-objective optimization based model predictive control framework for demand response oriented building thermal mass control. This multi-objective optimization framework takes both energy cost and thermal comfort into consideration simultaneously. In this study, the developed model predictive control framework has been applied in six commercial buildings at Boston, Chicago, and Miami, under typical summer weather conditions. Time-of-use electricity prices from these three locations are used to calculate the cooling and reheating energy costs. Pareto curves for optimal temperature setpoints under different thermal comfort requirements are calculated to show the trade-off between the cost saving and thermal comfort maintaining. Comparing with a typical “night setback” operation scheme, this model predictive control schemes are able to save energy costs from 20% to 60% at these three locations under different weather and energy pricing conditions. In addition, the Pareto curves also show that the energy cost saving potentials are highly dependent on the thermal comfort requirements, weather conditions, utility rate structures, and the building constructions. [ABSTRACT FROM AUTHOR]

In order to meet the requirement of frequent start-stop of the units, it is significant to optimize the operation scheme of the unit. A novel optimized mathematical model of a steam turbine was proposed at a previous paper of this study’s authors. In this study the supported vector machine (SVM) stress model of a 320 MW steam turbine was established based on 13 groups of start-up schemes. According to the novel optimized mathematical model and SVM stress model of the turbine, Genetic algorithm-particle swarm optimization was employed to search for the best values of the steam temperature rise rate. The optimization schedule can shorten the start-up time of 170 min in the premise of meeting the stress requirement. It is necessary to testify the feasibility of the optimized schedule, the fatigue, creep, and creep-fatigue life of the steam turbine rotor were analyzed by continuous damage mechanics (CDM) model. The results shown that the life assessment of the rotor from the nonlinear CDM is accordance with the bilinear failure criterion of ASME Section III, and the critical creep-fatigue damage of the rotor is 0.2083, and the life loss of the rotor after working 30 years under the optimized start-up schedule is 19.25%. [ABSTRACT FROM AUTHOR]

Smart district heating integrated various advanced technologies to implement the motivation structures and minimum operation cost. In this paper, an exact mathematical model has developed to describe the thermal and hydraulic characteristics of a district heating system which applied the distributed variable-speed pumps. Afterwards, two associate optimization models have been established and the relevant regulation methods have been introduced to fulfill all customers' heat demands with less operation cost and more rapid regulation response. The proposed two co-operative approaches, which mean “coarse tuning” and “fine tuning”, have been then performed in a district heating system in Dezhou, China as a case study. Results indicate that the economical operating and less response time can be achieved simultaneously when the two proposed approaches are combined together. In contrast to the conventional approach, the total operation costs decreased by 4.99%, 11.39%, and 22.73%, respectively, in the concerned three scenarios. Moreover, the heat losses of the heating scheme can be decreased of 12.72%, 9.73%, and 4.47% at the same time. The results obviously demonstrate the great advantages and potentials of this smart operation approaches in the practical application. [ABSTRACT FROM AUTHOR]

Abstract: The paper's objective is to suggest a model for determining optimal lifetime of passenger car based on minimization of CO2 emission. The life cycle was modeled by eight main life cycle sequences. Combining the mathematical interpretations of the itch life cycle sequence is developed an optimization model. In this paper is suggested a new mathematical interpretation of following sequences: use, repair, distribution of passenger car and distribution of passenger car's parts. Comparison of the obtained numerical results was performed on examples for the data of new passenger car fleet from the EU14 countries. Special attention is given to analysis of dependencies between the optimal lifetime of passenger cars and Directive 2000/53/EC, trends of changing car weight, model year, kilometer driven and regulatory limit of the specific CO2 emission. The optimal lifetime in case where petrol car is replaced by diesel car was analyzed too. [Copyright &y& Elsevier]

Multi-objective optimization problems are difficult to solve in that the optimized objectives are usually conflicting with each other. It is usually hard to find an optimal solution that satisfies all objectives from the mathematical point of view. Unlike analytical methods and classical numerical methods, which require strict mathematical calculation or defined initial search values, intelligent optimization algorithms are heuristic algorithms able to find global optimal solutions. In this paper, we make a brief introduction of multi-objective optimization problems and some state-of-the-art intelligent algorithms. In order to get the final optimal solution in the real-world multi-objective optimization problems, trade-off methods including a priori methods, interactive methods, Pareto-dominated methods and new dominance methods are utilized. Moreover, we give a review of multi-objective optimization methods application in the environmental protection fields, for optimization objectives of energy saving, emissions reduction and cost reduction, etc. At last, a whole summary about current difficulties existed in the multi-objective optimization problem is given out, serving as suggestions or guidance for future researches. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a weighted combination of different demand vs. price functions referred to as Composite Demand Function (CDF) is introduced in order to represent the demand model of consuming sectors which comprise different clusters of customers with divergent load profiles and energy use habitudes. Derived from the mathematical representations of demand, dynamic price elasticities are proposed to demonstrate the customers’ demand sensitivity with respect to the hourly price. Based on the proposed CDF and dynamic elasticities, a comprehensive demand response (CDR) model is developed in this paper for the purpose of representing customer response to time-based and incentive-based demand response (DR) programs. The above model helps a Retail Energy Provider (REP) agent in an agent-based retail environment to offer day-ahead real time prices to its customers. The most beneficial real time prices are determined through an economically optimized manner represented by REP agent’s learning capability based on the principles of Q-learning method incorporating different aspects of the problem such as price caps and customer response to real time pricing as a time-based demand response program represented by the CDR model. Numerical studies are conducted based on New England day-ahead market’s data to investigate the performance of the proposed model. [Copyright &y& Elsevier]

Abstract: Combined cycle power plants have been studied in this paper with the aim of optimizing the heat recovery steam generator using a first and second law approach. To this end, a mathematical model has been developed for determining the optimal steam pressure in a one pressure level heat recovery steam generator, considering that the gas turbine is known. Different objective functions have been analysed in this study, some of which refer only to the exergy balance of the heat recovery steam generator while others involve the whole bottoming cycle. Some constraints for the operating parameters of the power plant have also been taken into account, regarding for instance the steam quality at the turbine outlet and the steam turbine blade height. Some numerical results have been reported in the paper, comparing the different objective functions for heat recovery steam generators coupled with several gas turbines; the developed parametric analysis has been performed in order to evaluate the influence of some parameters on both the heat recovery steam generator and the whole bottoming cycle. [ABSTRACT FROM AUTHOR]

Abstract: Operational optimization models are one of the main streams in modeling energy systems. Agent-based modeling and simulation seem to be another approach getting popular in this field. In either optimization or agent-based modeling practices, technological change in energy systems is a very important and inevitable factor that researchers need to deal with. By introducing three stylized models, namely, a traditional optimization model, an optimization model with endogenous technological change, and an agent-based model, all of which were developed based on the same deliberately simplified energy system, this paper compares how technological change is treated differently in different modeling practices for energy systems, the different philosophies underlying them, and the advantages/disadvantages of each modeling practice. Finally, this paper identifies the different contexts suitable for applying optimization models and agent-based models in decision support regarding energy systems. [Copyright &y& Elsevier]

Complex turbine (i.e., steam turbine with multiple controlled and uncontrolled extractions) is one of the most important components in industrial utility system. The function of complex turbine is to generate power electricity, provide steam for the processes, and heat boiler feedwater using uncontrolled extraction steam. Although many studies have focused on the modeling and optimization of utility systems of different scales, few works have been reported on the modeling and operation optimization for utility system containing multiple complex steam turbines. In this paper, a superstructure of utility network consists of multiple interconnected various types of complex turbines (ICSTUN) is constructed. The superstructure demonstrates not only an external utility network that supplies utility energy for the processes but also an internal utility network that supplies boiler feedwater. A systematic modeling approach is developed for robust simulation, validation and operation optimization of ICSTUN. A mixed-integer nonlinear programming (MINLP) model based on an improved modeling principle of complex turbine is formulated for the operation optimization of ICSTUN. The MINLP model is able to simultaneously optimize the external and internal utility networks. A solving strategy incorporating model decomposition, model relaxation and case initialization is proposed to find a feasible solution. A large utility network in a petrochemical complex is studied to test the accuracy of the complex turbine model and the effectiveness of the proposed operation optimization methodology. The validation results of the complex turbine model show that the mean relative error between field operation data and simulation data is less than 1.18% and is acceptable in engineering application. The optimization of a single utility plant yields a maximum coal reduction rate of 4.59%, and the optimization of the total utility system consisting of two utility plants yields a maximum coal reduction rate of 6.01%. The optimization contribution is discussed in detail, and several conclusions and suggestions are presented. [ABSTRACT FROM AUTHOR]

The aim of this article is to present the reason and the process of creating new modified mathematical model of heat pump plate condenser. The fundamental mathematical model is modified according to analytical optimization procedure. The adaptation is carried out by applying the procedure of elimination. The modified mathematical model include 2 governing equations instead of 6. The two governing equations contain 2 unknown dependent variables and 6 known parameters. The modified mathematical model is validated using the comparative method. The compared data are obtained by numerical simulation using fundamental and modified mathematical models. Applying both models the obtained data fully coincided. By using the new modified mathematical model and implementing the optimization process may lead to the determination of the maximum energy efficiency of hot water subsystem. The subsystem comprises a condenser, a circulation pump, a connecting pipeline and the heating units. The objective function in the optimization process is the coefficient of performance, COP, as a function of the mass flow rate of the hot water or of the circulation pump power. The paper offers the implementation of modeling the circulation pump power to achieve the maximum value of the COP. [ABSTRACT FROM AUTHOR]

Abstract: Against the background of the ambitious German targets for renewable energy and energy efficiency, this paper investigates the economic potential for thermal load management with virtual power plants consisting of micro-cogeneration plants, heat pumps and thermal storage within the residential sector. An optimising energy system model of the electricity and residential heat supply in Germany is developed in the TIMES (The Integrated MARKAL EFOM System) modelling framework and used to determine capacity developments and dispatch of electricity and residential heat generation technologies until 2050. The analysed scenarios differ with respect to the rate of technological development of heat and power devices, fuel and CO2 prices as well as renewable electricity expansion. Results show that high fuel prices and a high renewable electricity expansion favour heat pumps and insulation measures over micro-cogeneration, whereas lower fuel prices and lower renewable electricity expansion relatively favour the expansion of micro-cogeneration. In the former case heat pump capacities increase to around 67 GWel, whereas in the latter case the total capacity of micro-cogeneration reaches 8 GWel. With the aid of thermal storage, this provides considerable flexibility for electrical load shifting through heat pumps and electricity generation from micro-cogeneration in residential applications, needed for the integration of fluctuating renewable electricity technologies. [Copyright &y& Elsevier]

Abstract: In China, the energy pricing mechanism has an insufficient linkage with other energy prices. As a result of the unreasonable price level, it is impossible to exploit fully the substitution elasticity among energy resources and there is a negative impact on achieving energy conservation and energy efficiency. This paper proposes an optimized mechanism for residential energy prices in China, which maximizes the total social surplus subject to some related constraints. Three types of energy pricing mechanisms are designed based on China's low-carbon targets and the optimization of residential energy price policies through the dynamic CGE model. Compared with the energy price linkage method, the results show that the market netback value mechanism has a greater impact on the total social surplus. In order to achieve further low-carbon targets, the proportion of second and third tier residents can be expanded, while the energy prices could be deregulated to some degree. In addition, considering residential affordability, the government may take into account different electricity pricing mechanisms for different tiers of residents. Electricity pricing for the first tier, the second tier and the third tier should be based respectively on cost, the integration of energy price linkage and the market netback value mechanism. [Copyright &y& Elsevier]

Abstract: Landscape constraints inevitably cause the irregularity of the shape or boundary of a wind farm, which was not fully considered in previous literature. In this paper, a single-boundary constraint model and a novel multi-boundary constraint model incorporated with ray intersection method are developed to quantify the irregular boundary constraint for wind farm micro-siting optimization. In order to obtain high-fidelity wind farm shape information, an edge detection algorithm is employed to extract wind farm contour data from digital maps, and an optimal polygonal approximation algorithm is applied to compress the contour data so as to make the computation of boundary constraints less time-consuming. Simulations of four commercial wind farms comprehensively demonstrate the effectiveness of the proposed boundary constraint models and the significance of irregular-shape wind farm micro-siting optimization. [Copyright &y& Elsevier]

Abstract: Several factors support more deployment of real-time pricing (RTP); including recent developments in the area of smart metering, regulators interest in promoting demand response programs and well-organized electricity markets. This paper first reviews time-based electricity pricing and the main barriers and issues to fully unleash benefits of RTP programs. Then, a day-ahead real-time pricing (DA-RTP) model is proposed, which addresses some of these issues. The proposed model can assist a retail energy provider and/or a distribution company (DISCO) to offer optimal DA hourly prices using smart metering. The real-time prices are determined through an optimization problem which seeks to maximize the electricity provider''s profit, while considering consumers'' benefit, minimum daily energy consumption, consumer response to posted electricity prices, and distribution network constraints. The numerical results associated with Ontario electricity tariffs indicate that instead of directly posting DA market prices to consumers, it would be better to calculate optimal prices which would yield higher benefit both for the energy provider and consumers. [Copyright &y& Elsevier]

Abstract: This paper deals with the simultaneously optimization of operating conditions (pressures, temperatures and flow-rates) and dimensions (diameter and height) of the amine regeneration unit in the post-combustion CO2 capture process. The proposed model takes into account the effect of kinetic reactions on the mass transfer, the hydraulics of the random packing and the pressure drop along the column. In addition, profiles of temperature, composition and flow-rate along the height of the regenerator are also predicted. The resulting mathematical model is implemented into the optimization environment General Algebraic Modeling System (GAMS) which is a high-level modeling system for mathematical programming and optimization. The benefits of the mathematical programming techniques (equation-oriented modeling tools) are exploited for the simultaneous optimization not only of the operating conditions but also the dimensions of the all piece of equipments (heat exchangers, regeneration unit, condenser and reboiler). The mathematical model was successfully verified by comparison of the obtained results with published experimental data and simulated solutions obtained by a process simulator (HYSYS). Once validated, the model was used for optimization purpose. Finally, in order to study the effect of the main process parameters on the optimized results a sensitivity analysis is also investigated and discussed in detail. [Copyright &y& Elsevier]

Abstract: Optimizing oil production rate is one of the main challenges in designing development plan of oilfield in international cooperation projects. This paper establishes an oil production rate optimization model to maximize economic benefits within constraints of geological conditions and technology factors as well as oil contracts. This analysis describes the effects of contract terms on parameters of inputs and outputs, quantifies the relationships among production rate and production time, production, investment and costs. The oil exploration and production (E&P) project is illustrated for example, in which the optimal production rate under its own geological conditions and contract terms is calculated. The results reflect that the contract terms exert a tremendous influence on optimal production rate, at which the production in plateau phase occurs on the boundary of sliding scales provided in the contract. Simultaneously, changes in oil prices do not affect the optimal production rate. This study is important for companies to negotiate some elastic terms in contracts and design reasonable development strategies for resource distribution. [Copyright &y& Elsevier]

A Stirling engine configuration consisting of two cylinders, a regenerator and a sliding disc actuating mechanism (“swashplate”) is considered in this paper. A mathematical model, which combines fundamental and empirical correlations, and principles of classical thermodynamics, mass and heat transfer accounting for variable heat transfer coefficients, is developed. The proposed model is then utilized to simulate numerically the system transient and steady state response under different operating and design conditions. A system global optimization for maximum performance in the search for optimal parameters that lead to maximum cycle efficiency is performed with low computational time. Appropriate dimensionless groups are identified and the results presented in normalized charts for general application. The numerical results show that the two-way maximized system efficiency, , occurs when two system characteristic parameters, the ratio between the total swept volume during the expansion, and the total swept volume, , and the ratio between the heat transfer area of the hot side heat exchanger and the total heat exchange area, y, are optimally selected, i.e., . The two-way maximized cycle efficiency found with respect to the optimized parameters is sharp, in the sense that a 225% variation of the calculated efficiency values was observed within the range of tested configurations in this study, and “robust” (i.e., relatively insensitive) to the variation of several parameters, thus stressing the importance to be considered in actual design. It is also found that the twice-maximized cycle efficiency and the total engine work output increase monotonically with the temperature of the hot source, T h. As a result, the model is expected to be a useful tool for simulation, design, and optimization of Stirling engines. [ABSTRACT FROM AUTHOR]

Abstract: Dynamic economic dispatch (DED) aims to schedule the committed generating units'' output active power economically over a certain period of time, satisfying operating constraints and load demand in each interval. Valve-point effect, the ramp rate limits, prohibited operation zones (POZs), and transmission losses make the DED a complicated, non-linear constrained problem. Hence, in this paper, imperialist competitive algorithm (ICA) is proposed to solve such complicated problem. The feasibility of the proposed method is validated on five and ten units test system for a 24 h time interval. The results obtained by the ICA are compared with other techniques of the literature. These results substantiate the applicability of the proposed method for solving the constrained DED with non-smooth cost functions. Besides, to examine the applicability of the proposed ICA on large power systems, a test case with 54 units is studied. The results confirm the suitability of the ICA for large-scale DED problem. [Copyright &y& Elsevier]

Abstract: Oxy-fuel combustion is considered as one of promising options for carbon dioxide capture in future coal power plants. Currently models available in CFD codes fail to predict accurately the radiative heat transfer in oxy-fuel cases due to higher pressure of carbon dioxide and water vapor. This paper concerns numerical investigation applying three band formulations aiming an accurate prediction of radiative properties. The radiative heat transfer is calculated by discrete ordinate method coupled with a weighted sum of gray gases model. The first case relates to the domain-based approach using air-fired parameters. In the last two cases, the optimized parameters of 3 and 4 gray gases fitted to oxy-fired conditions are implemented through a non-gray gases approach. Results applying these set of parameters are evaluated through a comparison with experimental data. Discrepancies between the predicted and measured velocity and O2 concentration are found mainly close to the burner due to shortcomings of the turbulence model and inaccurate thermochemical closure. The gas flame temperatures are better predicted by the optimized parameters for oxy-fuel conditions, which are considerably lower than the values calculated by the air-fired parameters. Similar trends are observed when the radiative heat fluxes at the lateral wall are compared. [Copyright &y& Elsevier]

Abstract: Biofuels supply chain comprises a wide set of activities involving a rather complex set of parameters. Cultivation of the raw materials is closely related to the agricultural sector whereas the production of the final product presumes the operation of a conversion plant. The distribution network aims at delivering the final product close to the consumption. The extent of the involvement of each one of the previously mentioned sectors is the result of strategic and operational planning of the whole supply chain and, in the general case, determines the efficiency of the biofuels sector. Taking also into account the very rapidly changing opinions related to the environmental behaviour of the whole biofuels supply chain, it becomes very clear that the parameters in the sector are continuously changing. Therefore, the consideration of an integrated supply chain appropriately modelled is believed to be very critical and could result in the optimal solution per case, economically and/or environmentally speaking. In this paper the development of a mathematical model for the optimal design and operation of Biofuels Supply Chain is proposed as an integrated approach that can take into account both technical and economic parameters affecting the performance of the whole value chain. Model implementation would facilitate and support the decision taking in various planning and operational issues such as infrastructure investments, the quantities of raw materials to be cultivated, the quantities of biofuels to be produced in the domestic market or imported, identifying the best available solution for the optimal design and operation of the biofuels supply chain. [Copyright &y& Elsevier]

Abstract: Due to their non-polluting nature and environment friendliness, Renewable Energies have gained great deal of attention and deserve a substantial body of both theoretical and empirical research. Amongst other factors, the low operational cost and simple maintenance procedures attributed the Oscillating Water Column (OWC) are perhaps the main reasons why this system is the most used concept for the ocean wave energy capture. In this paper, through extensive experimental research various geometrical designs of an OWC system is investigated and the optimized set up for the maximum energy harness is obtained. The initial chamber dimensions were 10 × 50 × 53 cm with the chamber being placed in an open channel with wave-simulating equipment with dimensions of 16 × 0.7 × .05 m. For various chamber geometries, with the aid of a air rotameter and a Pitot tube equipped with a digital manometer, the outlet air flow and velocity from the chamber was measured and registered. The measurements were then interpreted to provide design data for the optimal geometry of the chamber that may yield the maximum conversion of wave energy to useful energy. [Copyright &y& Elsevier]

Abstract: To determine the optimal size, location and also the proper technology of distributed generation (DG) units in distribution systems, a static fuzzy multiobjective model is proposed in this paper. The proposed model can concurrently optimize a number of conflicting and competing objective functions including economic, technical and environmental attributes. The economic function is the profit of a distribution company (DisCo) from selling the DG output power to its customers. The contribution of this model is the consideration of some DG marginal revenues in the economic function. Inclusion of marginal revenues would not only reduce the investment risks of DG technologies, but also would enable the optimal penetration of DG units. The proposed DG planning framework considers various DG technologies such as photovoltaic (PV), wind turbine (WT), fuel cell (FC), micro-turbine (MT), gas turbine (GT) and diesel engine (DE). The system uncertainties (including those for the energy demand, energy price and DG technologies operating and investment costs) are modeled using fuzzy numbers. The numerical case studies have been carried out using the IEEE 37-node distribution test system to demonstrate the performance of the proposed DG planning model. [Copyright &y& Elsevier]

Abstract: The heat exchanger network (HEN) can be optimized using the stage-wise model of superstructure representation, as proposed by Yee and Grossmann. This model can be easily solved regarding both trivial problems, and serious and complex new industrial design plants. In this paper, a stage-wise model for new designs is extended for retrofits by using a stage-wise model for a retrofitted HEN. This method using a stage-wise model is very general; it can be used in new designs as well as during existing process integration. The methodology of the stage-wise model for retrofitted HEN can be used to solve HENs easily and well enough, over a short time, and simultaneously. A mathematical model of stage-wise for retrofit HEN can include additional equations and limitations for retrofits. This model was tested by using a retrofitted methanol process generating an additional profit of 189,200 EUR/a. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a linear mixed-integer modeling approach for basic components in a biomass supply chain including supply, processing, storage and demand of different types of biomass. The main focus in the biomass models lies on the representation of the relationship between moisture and energy content in a discretized framework and on handling of long-term processes like storage with passive drying effects in the optimization. The biomass models are formulated consistently with current models for gas, electricity and heat infrastructures in the optimization model ‘eTransport’, which is designed for planning of energy systems with multiple energy carriers. To keep track of the varying moisture content in the models and its impact on other biomass properties, the current node structure in eTransport has been expanded with a special set of biomass nodes. The Node, Supply, Dryer and Storage models are presented in detail as examples of the approach. A sample case study is included to illustrate the functionality implemented in the models. [Copyright &y& Elsevier]

Abstract: This paper describes the development of a mathematical model to determine the optimized energy losses for a set of boilers (with a wide operating margin) supplying a common load. The model can be applied to steam systems that have a group of liquid- or gas-fired shell boilers available for use. The study shows that when the model is applied, the total energy losses of a few boilers working in unison are lower than when a traditional cascade system is used. The differences in energy loss can even reach approximately 12%. The model shows that increasing the heat load from 0 to 30% yields increasing differences in the energy losses between the standard (traditional) and optimized conditions, up to a maximum value of 79kJ/s. As the steam demand grows from 30 to 100%, the total difference in energy losses between the standard and optimized conditions decreases systematically. When the multi-boiler system operates at full thermal power (100%), there are no differences in the energy losses. The greatest energy loss differences occur in the heat load range from 10 to 80%. There will be a reduction in the primary fuel used by about 40,300Nm3 per year if the model is applied. The optimization system can be put into operation in existing and proposed plants. The payback period on investment for the optimization controller is less than half a year. [Copyright &y& Elsevier]