Multi-criteria decision analysis (MCDA) methods have become increasingly popular in decision-making for sustainable energy because of the multi-dimensionality of the sustainability goal and the complexity of socio-economic and biophysical systems. This article reviewed the corresponding methods in different stages of multi-criteria decision-making for sustainable energy, i.e., criteria selection, criteria weighting, evaluation, and final aggregation. The criteria of energy supply systems are summarized from technical, economic, environmental and social aspects. The weighting methods of criteria are classified into three categories: subjective weighting, objective weighting and combination weighting methods. Several methods based on weighted sum, priority setting, outranking, fuzzy set methodology and their combinations are employed for energy decision-making. It is observed that the investment cost locates the first place in all evaluation criteria and CO2 emission follows closely because of more focuses on environment protection, equal criteria weights are still the most popular weighting method, analytical hierarchy process is the most popular comprehensive MCDA method, and the aggregation methods are helpful to get the rational result in sustainable energy decision-making.

Review on multi-criteria decision analysis aid in sustainable energy decision-making

Energy is a vital input for social and economic development. As a result of the generalization of agricultural, industrial and domestic activities the demand for energy has increased remarkably, especially in emergent countries. This has meant rapid grower in the level of greenhouse gas emissions and the increase in fuel prices, which are the main driving forces behind efforts to utilize renewable energy sources more effectively, i.e. energy which comes from natural resources and is also naturally replenished. Despite the obvious advantages of renewable energy, it presents important drawbacks, such as the discontinuity of generation, as most renewable energy resources depend on the climate, which is why their use requires complex design, planning and control optimization methods. Fortunately, the continuous advances in computer hardware and software are allowing researchers to deal with these optimization problems using computational resources, as can be seen in the large number of optimization methods that have been applied to the renewable and sustainable energy field. This paper presents a review of the current state of the art in computational optimization methods applied to renewable and sustainable energy, offering a clear vision of the latest research advances in this field.

Optimization methods applied to renewable and sustainable energy: A review

MES (multi-energy systems): An overview of concepts and evaluation models

A review on simulation-based optimization methods applied to building performance analysis

Thermal comfort and building energy consumption implications - A review

The controlled objects are modeled in heating, ventilating and air-conditioning (HVAC) system, mainly including the heat exchanger and the air-conditioning space. The HVAC system has large inertia, pure lag and nonlinear characteristic. The uncertain disturbance factors affect the control performance. To obtain better performance in HVAC system, this study proposes a hybrid Cerebellar model articulation controller (CMAC)-PID control system, which combines the CMAC neural network and general PID control. This method realized the feedback control by using traditional PID controller to enhance the stability and reject the disturbance and realized the feed forward control by using CMAC neural network to increase the response speed and control precision in HVAC system. The simulation results show the hybrid CMA-PID control system possesses the advantages of high precision, realtime standard, strong ability of anti-interfere and robustness.

Hybrid CMAC-PID Controller in Heating Ventilating and Air-Conditioning System

Multi-objective energy planning for regional natural gas distributed energy: A case study

In the central air-conditioning system, the control system uses traditionally single loop PID controller. The control structure is simple, but the performance is usually not satisfactory. In this paper, the thermodynamic model of the heat exchanger and air-conditioning space in the central air-conditioning system are modeled in mathematic. Based on the models, we propose a robust cascade control strategy for temperature control of air-conditioning system. The robust cascade control system aims at eliminating the disadvantages of traditional design via complete decoupling of the design and performance of two cascaded control loops. Finally, the three controllers, the designed cascade control, traditional cascade PID control and single PID control are simulated in central air-conditioning system. It is found that the setpoint response, the robust and the performance of the designed robust cascade control system are better than the traditional cascade PID control system and single PID control system.

Robust cascade control system design for central airconditioning system

Solar radiation intensity significantly influences the cooling loads of building, and the two are correlated and accorded to a certain extent. This study proposes a double effect LiBr–H2O absorption cooling system based on the parabolic trough collector (PTC) of solar heat energy. Thermodynamic models including PTC and absorption chiller are constructed, and their accuracy is verified by comparing the simulation results and the experimental data. Subsequently, the impact of variable design parameters on the thermodynamic performance is analyzed and discussed. The analysis of a solar cooling system in a hotel case study is related to its operation in a typical day, the average coefficient of performance of the absorption chiller is approximately 1.195, and the whole solar cooling system achieves 61.98% solar energy utilization efficiency. Furthermore, the performance comparison of a solar cooling system in different types of building indicates that higher matching and a higher correlation coefficient between the transient solar direct normal irradiance and cooling load is helpful in decreasing the heat loss and improving systemic performance. The solar cooling system in the office building exhibits a correlation coefficient of approximately 0.81 and achieves 69.47% systemic thermal efficiency.

Thermal Performance Analysis of an Absorption Cooling System Based on Parabolic Trough Solar Collectors

Six heating, ventilation and air conditioning (HVAC) schemes, constant air volume, variable air volume, fan-coil, induction unit, variable refrigerant volume and distributed HVAC system are evaluated and compared in multi-criteria. Because of the uncertainty of qualitative criteria, this paper presents a fuzzy multi-criteria model to select the optimal HVAC system. The methods of fuzzy set theory, linguistic value, analytic hierarchy process, entropy weighting and optimal weighting are used to obtain the criteria weights. Fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method is employed to get the ranking of HVAC schemes. Finally, the application of the fuzzy multi-criteria evaluation model demonstrates detailedly the computation and evaluation procedure in the selection of HVAC schemes.Practical applications: The fuzzy multi-criteria evaluation model combined with the optimal weighting method in this paper is believed by the authors to contribute to the selection and compar...

Jiangjiang Wang

Papers

Hybrid CMAC-PID Controller in Heating Ventilating and Air-Conditioning System

Multi-objective energy planning for regional natural gas distributed energy: A case study

Robust cascade control system design for central airconditioning system

Thermal Performance Analysis of an Absorption Cooling System Based on Parabolic Trough Solar Collectors

Fuzzy multi-criteria evaluation model of HVAC schemes in optimal combination weighting method