Design Of Combined Cooling, Heating And Power System Research Articles

Optimised MOPSO with the grey relationship analysis for the multi-criteria objective energy dispatch of a novel SOFC-solar hybrid CCHP residential system in the UK

In the quest to achieve home comfort with the highest possible efficiency, there is an increasing interest in combined cooling, heating and power (CCHP) systems. These can be fuelled by natural gas and potentially by hydrogen enriched natural gas and ultimately by hydrogen. The optimised designs largely depend on the energy dispatch algorithms that take into account aspects of economic and environmental impacts as well as system efficiency. This paper details a new algorithm to optimise the operation of a novel hybrid solid oxide fuel cell (SOFC)-solar hybrid CCHP residential system. The proposed algorithm is based on the multi-objective particle swarm optimization (MOPSO) and the grey relationship analysis (GRA) (named as MOPSO-GRA) with the capability of resolving the objective energy dispatch issues within the system by effectively avoiding local optimum problem. More specifically, the grey incidences are first integrated into MOPSO to analyse the degree of closeness between non-ideal solutions and the ideal solution. Then, the relationship of degree is introduced to give objective energy dispatch in order to maximise the efficiency of energy utilization while minimising the system capital cost, operating costs, maintenance costs, fuel costs and emissions. Finally, the new algorithm is validated on the proposed new design of CCHP system. Ten cases are studied to evaluate the technical, economic and environmental performance of the MOPSO-GRA algorithm when being applied to an SOFC-based CCHP system under both the grid-connected and the island modes. A comparison is made with the conventional MOPSO method and system structure, and the impact of a plug-in EV is also evaluated. Based on a detailed cost and emissions analysis, the results indicate the environmental and economic advantages, in addition to the higher efficiency of the proposed methodology and system structure. The impact of these results and observations leads to the promotion of intelligent FC-based multi-energy system technologies for residential use.

Optimal design, operation and analytical criteria for determining optimal operating modes of a CCHP with fired HRSG, boiler, electric chiller and absorption chiller

The configuration, design and operation strategy are the main factors that can affect the technical, economic and environmental performances of combined cooling, heating and power (CCHP) system. In this paper, the operation of a CCHP system with fired heat recovery steam generator (HRSG), electric chiller, absorption chiller and a boiler is classified into one of three scenarios which are determined by gas turbine size and magnitude of thermal and electric loads. The optimal operating strategies are presented for these scenarios. For scenario with high cooling loads, we derive analytical expressions for calculation of ratio (electricity price/natural gas price) values which delimit three optimal modes for providing cooling demand in summer, thereby enabling selection of optimal operating strategy without numerical optimization. We examine the optimal design of CCHP system in three climate zones based on the proposed strategy. Supplementary firing as well as a higher coefficient of performance (COP) of the absorption chiller increase system efficiency and enable reduction of gas turbine size. Our case studies show that supplementary firing, (for some values of price ratio, absorption chiller COP and climate zone) the electric chiller and/or the boiler are necessary components to achieve optimal system performance.

An illustration of the optimization of combined cooling heating and power systems using genetic algorithm

The performances of combined cooling, heating and power (CCHP) system are greatly dependent on its design, operation strategy and thermal and electric demands. This paper illustrates how the use of a genetic algorithm can provide speedy optimization, by applying it to two styles of buildings operated in different operation strategies. The primary energy consumptions of CCHP system following electric demand management (EDM) and thermal demand management (TDM) are firstly analyzed respectively. Then, sixteen hypothetical buildings are constructed to represent various energy demands. Primary energy saving (PES), annual total cost saving (ATCS), and CO2 emission reduction (CO2ER), are weighted to evaluate the integrated performances of CCHP system in comparison to separation production system. Finally, the optimized CCHP system for sixteen scenarios using GA are compared. Practical application: This paper provides an optimization design method for CCHP system. The performance analysis of CCHP systems running different operation modes for different buildings is believed by the authors to contribute to a significant guide for the fundamental design of CCHP systems. Although sensitivity to a number of other important design considerations such equipment performance, possible future changes in operating conditions, changes to the price or carbon intensity of grid-supplied energy etc are not addressed, the conclusions present a simple and effective direction and the proposed optimization algorithm and the evaluation method for CCHP system can be extended to other buildings.

A Novel Optimal Planning Method for Combined Cooling, Heating, and Power (CCHP) System

Planning of combined cooling, heating and power (CCHP) systems are complicated due to the diversity of energy demands. Some mathematical models for the design of CCHP systems have been developed, most of which adopt a one-third peak load strategy. In this paper, we present a novel optimal planning method for CCHP systems, which is divided into two levels, the system level and the equipment level, each of which has a mathematical model. Minimizing the total annual cost is the optimal object of the system level, while minimizing system life-cycle cost is the optimal object of equipment level. Results show that the CCHP system planned by the novel optimal planning method can achieve better economy and energy efficiency, and the running costs are pretty lower.

Design and optimization of CCHP system incorporated into kraft process, using Pinch Analysis with pressure drop consideration

Combined Cooling, Heating and Power (CCHP) system is a cogeneration technology (CHP) that integrates an absorption cycle to produce power, heating and cooling, simultaneously. In this research, the implementation of a CCHP system in a pulp and paper industry is studied. We consider this system as two parts in design and optimization steps. One is a CHP system, which consists of a gas turbine cycle, and a HRSG system and another part is an absorption heat pump (AHP) driven by the discharged steam from a steam turbine. Pinch analysis is applied to find the appropriate placement of the proposed CCHP system. Aspen plus software is used to simulate the basic design of this CCHP system. Afterward, genetic algorithm is used for optimization of the proposed CCHP system with minimum total annual cost (TAC) and highest exergy efficiency. Having implemented the proposed CCHP system, both power and heating requirements of the pulp and paper mill can be supplied and cooling requirements can be reduced with the payback of 3.2 years.

Impacts of equipment off-design characteristics on the optimal design and operation of combined cooling, heating and power systems

Optimal design and operation of combined cooling, heating and power (CCHP) systems are complicated due to the fluctuating energy demands. Many mathematical models for the design and/or operation of CCHP systems have been developed. Most of them adopt a constant efficiency assumption, whilst others take equipment off-design characteristics into account. In this paper, we present two mathematical models for the optimal design and operation of CCHP systems with the target of minimising the total annual cost. One model is formulated using the constant efficiency assumption. In the other model, off-design characteristics of all equipments are considered. Comparative studies using different models were performed to examine the impacts of equipment off-design characteristics on the accuracy of the optimal design of CCHP systems. Results show that introduction of thermal storage facilities, connection to power grid and well designed operation strategies can diminish the negative impacts of adopting the constant efficiency assumption.

Emission operational strategy for combined cooling, heating, and power systems

Integrated Energy Systems (IES), as technology that use thermal activated components to recover waste heat, are energy systems that offer key solution to global warming and energy security through high overall energy efficiency and better fuel use. Combined Cooling, Heating, and Power (CCHP) Systems are IES that use recovered thermal energy from the prime mover to produce heating and cooling for the building. The CCHP operational strategy is critical and it has to be considered in a well designed system since it defines the ultimate goal for the benefits expected from the system. One of the most common operational strategies is the cost-oriented strategy, which allows the system to operate at the lowest cost. A primary energy strategy (PES) optimizes energy consumption instead of cost. However, as a result of the worldwide concern about global warming, projects that target reduction of greenhouse gas (GHG) emissions have gained a lot of interest. Therefore, for a CCHP system, an emission strategy (ES) would be an operational strategy oriented to minimize emission of pollutants. In this study, the use of an ES is proposed for CCHP systems targeted to reduce emission of pollutants. The primary energy consumption (PEC) reduction and carbon dioxide (CO 2) emission reduction obtained using the proposed ES are compared with results obtained from the use of a PES. Results show that lower emission of CO 2 is achieved with the ES when compared with the PES, which prove the advantage of the ES for the design of CCHP systems targeted to emissions reduction.