Total System Energy Efficiency Research Articles

A Federated Learning-Based Resource Allocation Scheme for Relaying-Assisted Communications in Multicellular Next Generation Network Topologies

Growing and diverse user needs, along with the need for continuous access with minimal delay in densely populated machine-type networks, have led to a significant overhaul of modern mobile communication systems. Within this realm, the integration of advanced physical layer techniques such as relaying-assisted transmission in beyond fifth-generation (B5G) networks aims to not only enhance network performance but also extend coverage across multicellular orientations. However, in cellular environments, the increased interference levels and the complex channel representations introduce a notable rise in the computational complexity associated with radio resource management (RRM) tasks. Machine and deep learning (ML/DL) have been proposed as an efficient way to support the enhanced user demands in densely populated environments since ML/DL models can relax the traffic load that is associated with RRM tasks. There is, however, in these solutions the need for distributed execution of training tasks to accelerate the decision-making process in RRM tasks. For this purpose, federated learning (FL) schemes are considered a promising field of research for next-generation (NG) networks’ RRM. This paper proposes an FL approach to tackle the joint relay node (RN) selection and resource allocation problem subject to power management constraints when in B5G networks. The optimization objective of this approach is to jointly elevate energy (EE) and spectral efficiency (SE) levels. The performance of the proposed approach is evaluated for various relaying-assisted transmission topologies and through comparison with other state-of-the-art ones (both ML and non-ML). In particular, the total system energy efficiency (EE) and spectral efficiency (SE) can be improved by up to approximately 10–20% compared to a state-of-the-art centralized ML scheme. Moreover, achieved accuracy can be improved by up to 10% compared to state-of-the-art non-ML solutions, while training time is reduced by approximately 50%.

A novel multi-generation energy harvesting system integrating photovoltaic and solid oxide fuel cell technologies

This paper designs a new multi-generation system based on solar tower power supply, integrating a solid oxide fuel cell-gas turbine system, a supercritical recompressed carbon dioxide cycle, a Rankine cycle, an organic Rankine cycle, a compressed air energy storage system and a liquefied natural gas system. The aim is to overcome the intermittent and unstable nature of the solar power supply and ensure continuous power generation throughout the day, as well as improving the energy efficiency of the solar power system and minimising exhaust emissions from the integrated system. The system is modelled and evaluated in terms of energy, exergy, environment and economy. The results show the solar system energy efficiency of 10.09%, the total system energy efficiency of 19.28%, a round-trip efficiency of 58.66% and an exergetic round-trip efficiency of 52.06%, preventing the emission of 2090 tons of CO2 (a total of $50175 in environmental fines) per year. Finally, the proposed system was applied to a case study in the Xixiangtang district of Nanning, China, where the system, combined with real data, produced 24.8 MWh of electricity on the day with the highest direct of normal irradiance. In addition, the results of the economic analysis show the dynamic payback period is 6.9 years.

Thermodynamic analysis of a novel tri-generation system integrated with a solar energy storage and solid oxide fuel cell – Gas turbine

The conventional cooling, heating and power tri-generation system still has problems such as high greenhouse gas emissions and high fossil fuel consumption. A new integrated energy system is proposed which includes solar-methanol hydrogen production, energy storage device, solid oxide fuel cell and dual-effect absorption chiller/heat pump with less carbon dioxide emissions, higher energy conversion efficiency and less fossil fuel consumption. The solar energy storage device drives the methanol reformation reaction and the Li-Br chiller/heat pump in parallel, decoupling the power and cooling/heating of the system to simultaneously satisfy the user demands and increases system flexibility. The proposed system is modeled and simulated in Aspen Plus and Fortran. The system thermodynamic performance is analyzed at the design conditions and the results shows the new system obviously enhances the energy conversion efficiency compared with the reference system. The effects of the methanol flow rate on the system output parameters and the thermodynamic performances of the system in different seasons when meeting the cooling, heating and power needs of the district users are studied. The results shows that the maximum system energy efficiency is 92.98% when the system operates in summer, and the system power generation efficiency is 48.03%; in winter, the maximum total system energy efficiency reaches 146.30%, and the system power generation efficiency is 53.26%; in the transition season, the system only needs to provide users with power load and domestic hot water, and the exhaust gas provides the methanol reaction heat. The system power generation efficiency increases to 65.38% and the energy efficiency is 87%.

Thermo-economic assessment of a novel trigeneration system based on coupling of organic Rankine cycle and absorption-compression cooling and power system for waste heat recovery

A novel trigeneration system consisting of organic Rankine cycle (ORC) and absorption-compression cooling and power system (ACCPS) is proposed to recover diesel engine waste heat. A compressor is used between evaporator and absorber in ACCPS. Moreover, a screw expander is applied in ACCPS to increase power generation and domestic hot water (DHW) is prepared by DHW heat exchanger (HX) in ORC. Exergoeconomic analysis using the specific exergy costing (SPECO) method is implemented for system assessment. Base case and parametric analysis as well as the effects of using expander and compressor in ACCPS on total performance of the system are examined. The results show that the best thermo-economic performance of the system is achieved when ORC condensation temperature and generator outlet temperature have respectively the lowest (85 °C) and the highest (80 °C) values. It is difficult to select the proper ORC evaporation temperature, because the lower this temperature is, the higher net power output is obtained while higher ORC evaporation temperature leads to less total cost rate and more total energy efficiency of system. Moreover, system exergy efficiency has an optimum point versus variation of ORC evaporation temperature. By increasing expander inlet steam quality, ACCPS coefficient of performance (COP) and total energy efficiency of system decrease; however, due to increase in net power output and system exergy efficiency respectively equal to 18.23% and 3%, total system performance improves from exergy viewpoint. By utilizing a compressor in ACCPS and increasing its pressure ratio, the performance of ACCPS improves from energy viewpoint; however, system thermo-economic performance decreases.

An Alternating Optimization Algorithm for Energy Efficiency in Heterogeneous Networks

This paper studies the problems of precoding designs to achieve the energy efficiency (EE) in the uplink heterogeneous networks in which the multiple small cells are deployed in a macro-cell. We consider two design problems which maximize either the total system energy efficiency (SEE) or the minimum energy efficiency (MinEE) among users subject to the transmit power constraints at each user and interference constraints caused to the macro base station. Since the optimization problems are non-convex fractional programming in matrix variables, it cannot be straightforward to obtain the optimal solutions. To tackle with the non-convexity challenges of the design problems, we adopt the relationships between the minimum mean square error (MMSE) and achievable data rate to recast the EE problems into ones more amenable. Then, we employ the block coordinate ascent (BCA) and the Dinkelbach methods to develop efficient iterative algorithms in which the closed form solutions are obtained or the semi-definite programming (SDP) problems are solved at each iteration. Simulation results are provided to investigate the EE performance of the EE optimization as compared to those of the spectral efficiency (SE) optimization.

Robust optimal design of distributed energy systems based on life-cycle performance analysis using a probabilistic approach considering uncertainties of design inputs and equipment degradations

Uncertainties in design inputs (i.e. energy demand and energy price) and equipment degradations in operation result in that the actual performance of distributed energy systems (DESs) deviates from the design expectations significantly. To ensure that DESs designed can operate at high performance when the actual working environment and equipment performance change over a large range, a robust optimal design method based on life-cycle performance analysis is developed. This method adopts a probabilistic approach, which is based on qualifying the uncertainties of design inputs and equipment degradations, while Monte Carlo simulation method is adopted to model the uncertainty propagation and generate the probability distribution of the predicted DES performance in the design process. The “probabilistic” life-cycle performance of DES is therefore obtained and used for the robust optimal design. The method further identifies the optimum DES which has the best life-cycle performance expectation under the above conditions concerned. A case study is conducted on the DES design in a district in Hong Kong to test the application of this method. It is found that, compared with other schemes, the optimum DES has least life-cycle total cost and better robustness of performance under different operating conditions. The DES identified by this method achieves economic benefits and higher total system energy efficiency in the latter years of its life-cycle compared with the DES identified by optimal design method without considering the life-cycle performance. Conclusions of this study can be also used as references for DES life-cycle performance assessment for DES designers.

Cooled solar PV panels for output energy efficiency optimisation

As working temperature plays a critical role in influencing solar PV’s electrical output and efficacy, it is necessary to examine possible way for maintaining the appropriate temperature for solar panels. This research is aiming to investigate practical effects of solar PV surface temperature on output performance, in particular efficiency. Experimental works were carried out under different radiation condition for exploring the variation of the output voltage, current, output power and efficiency. After that, the cooling test was conducted to find how much efficiency improvement can be achieved with the cooling condition. As test results show the efficiency of solar PV can have an increasing rate of 47% with the cooled condition, a cooling system is proposed for possible system setup of residential solar PV application. The system performance and life cycle assessment suggest that the annual PV electric output efficiencies can increase up to 35%, and the annual total system energy efficiency including electric output and hot water energy output can increase up to 107%. The cost payback time can be reduced to 12.1years, compared to 15years of the baseline of a similar system without cooling sub-system.

Energy efficient resource allocation in two-tier OFDMA networks with QoS guarantees

In this paper, we introduce the joint power and subchannel allocations techniques for OFDMA based femtocell networks with focus on uplink direction. These techniques minimize the aggregate power of all Femto user equipment and maximize the total system energy efficiency while satisfying the minimum required rate of all users. An interference limit constraint is also considered to protect the QoS of macrocells . The original problem is a mixed-integer non-convex optimization problem which is converted to a convex problem using the time-sharing concept. Furthermore, Three algorithms are proposed to provide a scheme to optimize the goal function while meeting the constraints. The complexity order of all algorithms was investigated and was compared to other alternative solutions. The analytic and simulation results have demonstrated that the proposed algorithms could achieve significant power saving and better energy efficiency compared to existing algorithms.

A 0.79 pJ/K-Gate, 83% Efficient Unified Core and Voltage Regulator Architecture for Sub/Near-Threshold Operation in 130 nm CMOS

This paper presents the compute voltage regulator module (C-VRM), an architecture that embeds the information processing subsystem into the energy delivery subsystem for ultra-low power (ULP) platforms. The C-VRM employs multiple voltage domain stacking and core swapping to achieve high total system energy efficiency in near/sub-threshold region. Energy models for the C-VRM are derived, and employed in system simulations to compare the energy efficiency benefits of the C-VRM over a switched capacitor VRM (SC-VRM). A prototype IC incorporating a C-VRM and a SC-VRM supplying energy to an 8-tap fully folded FIR filter core is implemented in a 1.2 V, 130 nm CMOS process. Measured results indicate that the C-VRM has up to 44.8% savings in system-level energy per operation (E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">op</sub> ) compared to the SC-VRM system, and an efficiency η ranging from 79% to 83% over an output voltage range of 0.52 V to 0.6 V. Measured values of the E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">op</sub> and η match those predicted by system simulations thereby validating the energy models.

A feasible system integrating combined heating and power system with ground-source heat pump

A system integrating CHP (combined heating and power) subsystem based on natural gas and GSHP (ground-source heat pump subsystem) in series is proposed. By help of simulation software-Aspen Plus, the energy performance of a typical CHP&GSHP-S (S refers to ‘in series’) system was analyzed. The results show that the system can make a better use of waste heat in flue gas from CHP (combined heating and power subsystem). The total system energy efficiency is 123% and the COP (coefficient of performance) of GSHP (ground-source heat pump) subsystem is 5.3. A referenced CHP&GSHP-P (P refers to ‘in parallel’) system is used for comparison; its total system energy efficiency and COP of GSHP subsystem are 118.6% and 3.5 respectively. Compared with CHP&GSHP-P system with different operating parameters, the CHP&GSHP-S system can increase total system energy efficiency by 0.8–34.7%, with related output ratio of heat to power (R) from 1.9 to 18.3. Furthermore, the COP of GSHP subsystem can be increased between the range 3.6 and 6, which is much higher than that in conventional CHP&GSHP-P system. This study will be helpful for other efficient GSHP systems integrating if there is waste heat or other heat resources with low temperature.