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The thermal masses of components influence the performance of many adsorption heat pump systems. However, typically when experimental adsorption systems are reported, data on thermal mass are missing or incomplete. This work provides original measurements of the thermal masses for experimental sorption heat exchanger hardware. Much of this hardware was previously reported in the literature, but without detailed thermal mass data. The data reported in this work are the first values reported in the literature to thoroughly account for all thermal masses, including heat transfer fluid. The impact of thermal mass on system performance is also discussed, with detailed calculation left for future work. The degree to which heat transfer fluid contributes to overall effective thermal mass is also discussed, with detailed calculation left for future work. This work provides a framework for future reporting of experimental thermal masses. The utilization of this framework will enrich the data available for model validation and provide a more thorough accounting of adsorption heat pumps.

The flow developed on a tidal site can be characterized by combinations of turbulence, shear flows, and waves. Horizontal-axis tidal turbines are therefore subjected to dynamic loadings that may compromise the working life of the rotor and drive train components. To this end, a series of experiments were carried out using a 0.9 m horizontal-axis tidal turbine in a tow tank facility. The experiments included two types of regular waveforms, one of them simulating an extreme wave case, the other simulating a more moderate wave case. The second regular wave was designed to match the peak period and significant wave height of an irregular wave which was also tested. Measurements of torque, thrust, and blade-bending moments were taken during the testing campaign. Speed and torque control strategies were implemented for a range of operational points to investigate the influence that a control mode had in the performance of a tidal stream turbine. The results showed similar average power and thrust values were not affected by the control strategy, nor the influence of either the regular or irregular wave cases. However, it was observed that using torque control resulted in an increase of thrust and blade root bending moment fluctuations per wave period. The increase in fluctuations was in the order of 40% when compared to the speed control cases.

The paper develops a multi-objective planning framework for distribution network expansion with electric vehicle charging stations. Charging loads are modeled in the first place, and then integrated into the optimal distribution network expansion planning. The formulation is extended from the single objective of the economic cost minimization into three objectives with the additional maximization of the charging station utilization, and maximization of the reliability level. Compared with the existing models, it captures the interactive impacts between charging infrastructures planning and distribution network planning from the aspects of economy, utilization, and reliability. A multi-stage search strategy is designed to solve the multi-objective problem. The models and the strategy are demonstrated by the test case. The results show that the proposed planning framework can make a trade-off among the three objectives, and offer a perspective to effectively integrate the network constraints from both the transportation network and distribution network.

Effects of oxygen content of fuels on combustion characteristics and emissions were investigated on both an optical single cylinder direct injection (DI) diesel engine and a multi-cylinder engine. Three fuels were derived from conventional diesel fuel (Finnish City diesel summer grade) by blending Rapeseed Methyl Ester (RME) or Diglyme and Butyl-Diglyme of different quantities to make their oxygen content 3%, 3% and 9%, respectively. The experimental results with three tested fuels show that the fuel spray development was not affected apparently by the oxygenating. Compared with the base fuel, the ignition delay to pilot injection was shortened by 0%, 11% and 19% for three oxygenated fuels, respectively. The ignition delay to main injection was shortened by 10%, 19% and 38%, respectively. With regard to emissions, the smoke level was reduced by 24% to 90%, depending on fuel properties and engine running conditions. The penalties of increased NOx emissions and fuel consumption were up to 19% and 24%, respectively.

In this paper, a bi-level energy management framework based on Conditional Value at Risk (CVaR) and game theory is presented in the context of different ownership of multiple microgrid systems (MMGS) and microgrid aggregators (MAs). The energy interaction between MMGS and MAs can be regarded as a master–slave game, where microgrid aggregators as the leaders set the differentiated tariff for each MG to maximize its benefits, and MMGS as the follower responds to the tariff decision specified by the leader through peer-to-peer (P2P) energy sharing. The P2P energy sharing of MMGS can be regarded as a co-operative game, employing asymmetric Nash bargaining theory to allocate the co-operative surplus. The Conditional Value at Risk model was used to characterize the expected losses by microgrid aggregators due to the uncertainties of renewable energy resources. The Karush–Kuhn–Tucker conditions, Big-M method, and strong duality theory were employed to transform the bi-level nonlinear model of energy management into a single-level mixed integer linear programming model. The simulation results show that when MGs adopt the P2P energy-sharing operation mode, the total operating cost of MMGS can be reduced by 7.82%. The simulation results show that the proposed co-operative optimization framework can make the multiple microgrid systems obtain extra benefits and improve the risk resistance of microgrid aggregators.

With renewable power sources and new topology structures being widely introduced into the power system, the current local information-based power generation-side protection cannot fully guarantee the protection performance and the safety coordination with the power grid. This paper proposes an improved hierarchical protection system on the power generation-side. The proposed system takes advantage of the fusion of multi-information provided by the system, station and local layers. The system layer provides the information such as system voltage control and power regulation demand, so that the generation-side protection and control system can adapt to the system operation mode and power regulation demand. The station layer realizes the coordination of the protection principle and action strategy among the related units through information interaction with the power grid, the automatic control system and the local layer protection. The local layer introduces the condition monitoring information and more abundant protection information to enhance the protection performance and master the generation units’ safety condition. To illustrate the hierarchical protection system construction method and actual application mode, the multi-information fusion-based comprehensive local layer protection method and the multi-generators information fusion-based hierarchical protection method are taken as examples. Case analysis shows that the proposed methods can reflect more slight internal fault forms and can adaptively determine the protection action characteristic and tripping strategy according to the system operating conditions and other generators’ fault conditions, which effectively improve the protection sensitivity and coordination capability. To provide reference and inspiration for follow-up research, the hierarchical protection system construction mode, communication technology and research approaches of new protection methods are further pointed out.

Various combinations of ship propulsion systems have been developed with low-carbon-emission technologies to meet regulations and policies related to climate change, one of which is the combined gas turbine and steam turbine integrated electric drive system (COGES), which is claimed to be a promising ship propulsion system for the future. The objective of this paper is to perform a techno-economic and environmental assessment of the COGES propulsion system applied to liquefied natural gas (LNG) carriers. A propulsion system design for a 7500 m3 LNG carrier was evaluated through the thermodynamics approach of the energy system. Subsequently, carbon emissions and environmental impact analyses were carried out through a life cycle assessment based on the power and fuel input of the system. Afterwards, a techno-economic analysis was carried out by considering the use of boil-off gas for fuel and additional income from carbon emission incentives. The proposed propulsion system design produces 1832 kilowatts of power for a service speed of 12 knots with the total efficiency of the system in the range of 30.1%. The results of the environmental evaluation resulted an overall environmental impact of 10.01 mPts/s. The results of the economic evaluation resulted in a positive net present value and a logical payback period for investment within 8 years of operation. The impact of this result shows that the COGES has a promising technological commercial application as an environmentally friendly propulsion system. Last, for the economy of the propulsion system, the COGES design has a positive net present value, an internal rate return in the range of 12–18%, and a payback period between 6 and 8 years, depending on the charter rate of the LNG carrier.

This paper introduces the concept, theory of operation and applications of soft open points for direct current networks (DCSOPs). The DCSOP is based on a bidirectional DC–DC converter actively controlled to behave like a normal conductor. Unlike the normal conductor, the DCSOP can transfer the electric power between nodes at different voltage levels. With this advantage, the DCSOP can effectively control the power flow direction. Thus, DCSOPs can play a vital role in the reconfiguration of DC distribution networks. The operation and control of the DCSOP device was investigated, both in transient and steady-state conditions. Then, a DCSOP was integrated into a DC microgrid model to validate its ability to change the power flow through the modelled feeders. In addition, a set of reliability indicators was calculated for the DC microgrid under different reconfiguration scenarios. It was shown that reliability is improved when the DCSOP device implements network reconfiguration. Finally, an agent-based framework for controlling the DCSOP in a DC microgrid is presented. A fundamental implementation was created for reconfiguring a DC microgrid with a DCSOP controlled by an agent, proving that the agent-based system can effectively control the DCSOP device for reconfiguration and voltage regulation.

Globally, rising population and rapid urbanisation have resulted in the dual issues of increased electricity demand and waste generation. These exacerbate diverse global problems, ranging from irregular electricity supply and inadequate waste management systems to water/air/soil pollution, climate change, etc. Waste-to-Energy (WtE) approaches have been proposed and developed to address simultaneously these two issues through energy recovery from waste. However, the variety of available waste materials and different WtE technologies make the choice of an appropriate technology challenging for decision-makers. The evaluation of the different WtE technologies in terms of their sustainability could provide a solid comparative base for strategic decision making in the power and waste management domains. This paper presents research conducted using a multidimensional Life Cycle Sustainability Assessment (LCSA) approach to estimate and compare the environmental, economic, and social impacts associated with the generation of electricity from Municipal Solid Waste (MSW) in two major cities, Lagos and Abuja, in Nigeria. These cities provide case studies in a developing world context to explore how their similarities and differences may influence the LCSA impacts for four WtE systems (Anaerobic Digestion, Incineration, Gasification, and Landfill Gas to Energy), and this is the first research of its kind. An LCSA ranking and scoring system and a muti-attribute value theory (MAVT) multi-criteria decision analysis (MCDA) were employed to evaluate the overall sustainability of the prospective use of WtE over a 20-year timeframe. The results from both approaches indicated that the adoption of WtE offered sustainability benefits for both cities, marginally more so for Lagos than Abuja. It was concluded that, for optimal benefits to be achieved, it is vital for decision-makers to think about the various trade-offs revealed by this type of analysis and the varying priorities of relevant stakeholders.

Due to the rapid advancement in the use of photovoltaic (PV) energy systems, it has become critical to look for ways to improve the energy generated by them. The extracted power from the PV modules is proportional to the output voltage. The relationship between output power and array voltage has only one peak under uniform irradiance, whereas it has multiple peaks under partial shade conditions (PSCs). There is only one global peak (GP) and many local peaks (LPs), where the typical maximum power point trackers (MPPTs) may become locked in one of the LPs, significantly reducing the PV system’s generated power and efficiency. The metaheuristic optimization algorithms (MOAs) solved this problem, albeit at the expense of the convergence time, which is one of these algorithms’ key shortcomings. Most MOAs attempt to lower the convergence time at the cost of the failure rate and the accuracy of the findings because these two factors are interdependent. To address these issues, this work introduces the dandelion optimization algorithm (DOA), a novel optimization algorithm. The DOA’s convergence time and failure rate are compared to other modern MOAs in critical scenarios of partial shade PV systems to demonstrate the DOA’s superiority. The results obtained from this study showed substantial performance improvement compared to other MOAs, where the convergence time was reduced to 0.4 s with zero failure rate compared to 0.9 s, 1.25 s, and 0.43 s for other MOAs under study. The optimal number of search agents in the swarm, the best initialization of search agents, and the optimal design of the dc–dc converter are introduced for optimal MPPT performance.