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[en] Highlights: ► Analyze mutual interactions and restrictions within energy management systems. ► Tackle uncertainties expressed as fuzzy sets, and regular and radial intervals. ► Obtain optimal solutions under preferred satisfaction degrees and system benefits. ► Use protection level to reflect tradeoffs between constraint-violation and system reliability. ► Provide decision makers with effective energy management schemes. - Abstract: In this study, a fuzzy radial interval linear programming (FRILP) model was developed for supporting robust planning of energy management systems with environmental and constraint-conservative considerations, facilitating the reflecting of multiple uncertainties that are existing in energy activities and environmental emissions and could be expressed as fuzzy sets, and regular and radial intervals. Particularly, it could ensure the generation of robust solutions that would be feasible with high probability under input data variations, reflecting tradeoffs between the conservatism levels of solutions and probability levels of constraint violation. Specifically, 24 radial intervals associated with the electricity generation efficiency and electricity demands under different protection levels based on the natural and technologic conditions, as well as decision makers’ expectation were determined. Totally, 30 scenarios under the combinations of five protection levels were analyzed. Through solving the developed model, the results showed that decision variables would be rising with the increase of protection levels and higher radii fluctuation levels of radial intervals would cause higher system cost and lower satisfaction degree. The generated solutions could offer detail energy management plans (e.g., energy conversion technology capacity expansions) for decision makers, and thus could guarantee optimal economic and environmental benefits under desirable system reliability.
[en] Highlights: • In this paper an expert energy management system (EEMS) is presented. • A power forecasting module for wind generation capacity is presented. • The objective functions that must be minimized are operating cost and net emission. • A smart energy storage system (EES) for electrochemical batteries is presented. • A new modified Bacterial Foraging Optimization (MBFO) algorithm is presented. - Abstract: Recently, the use of wind generation has rapidly increased in micro-grids. Due to the fluctuation of wind power, it is difficult to schedule wind turbines (WTs) with other distributed energy resources (DERs). In this paper, we propose an expert energy management system (EEMS) for optimal operation of WTs and other DERs in an interconnected micro-grid. The main purpose of the proposed EEMS is to find the optimal set points of DERs and storage devices, in such a way that the total operation cost and the net emission are simultaneously minimized. The EEMS consists of wind power forecasting module, smart energy storage system (ESS) module and optimization module. For optimal scheduling of WTs, the power forecasting module determines the possible available capacity of wind generation in the micro-grid. To do this, first, an artificial neural network (ANN) is used to forecast wind speed. Then, the obtaining results are used considering forecasting uncertainty by the probabilistic concept of confidence interval. To reduce the fluctuations of wind power generation and improve the micro-grid performances, a smart energy storage system (ESS) module is used. For optimal management of the ESS, the comprehensive mathematical model with practical constraints is extracted. Finally, an efficient modified Bacterial Foraging Optimization (MBFO) module is proposed to solve the multi-objective problem. An interactive fuzzy satisfying method is also used to simulate the trade-off between the conflicting objectives (cost and emission). To evaluate the proposed algorithm, the EEMS is applied to a typical micro-grid which consists of various DERs, smart ESS and electrical loads. The results show that the EEMS can effectively coordinate the power generation of DERs and ESS with respect to economic and environmental considerations
[en] An energy management system with an electronic gearshift and regenerative braking is presented to improve the gross efficiency and driving range of an electric scooter, driven directly by a four-phase axial-flux DC brushless wheel motor. The integration of stator windings, batteries, ultracapacitors, and a digital controller constitutes an energy management system, which features smooth electronic gear shifting and regenerative braking. The gross efficiency of the experimental scooter is improved in the drivable range by 20% with respect to that without regenerative braking. The battery-to-wheel efficiency was also above 70% for both low- and high-speed gears.
[en] Highlights: • A new multi-agent based distributed control architecture for energy management. • Multi-agent coordination based on non-cooperative game theory. • A microgrid model comprised of renewable energy generation systems. • Performance comparison of distributed with conventional centralized control. - Abstract: Most energy management systems are based on a centralized controller that is difficult to satisfy criteria such as fault tolerance and adaptability. Therefore, a new multi-agent based distributed energy management system architecture is proposed in this paper. The distributed generation system is composed of several distributed energy resources and a group of loads. A multi-agent system based decentralized control architecture was developed in order to provide control for the complex energy management of the distributed generation system. Then, non-cooperative game theory was used for the multi-agent coordination in the system. The distributed generation system was assessed by simulation under renewable resource fluctuations, seasonal load demand and grid disturbances. The simulation results show that the implementation of the new energy management system proved to provide more robust and high performance controls than conventional centralized energy management systems.
[en] Research highlights: → A new FMCS architecture with an energy management system was developed. → The new coupling system was demonstrated feasible during in situ experiments. → A survey found that HVAC is the most energy intensive system in IT industries. → A 9.6% chiller efficiency increase and total 23.2% annual energy saving were reached. - Abstract: A commissioning unit with an energy management system (EMS) was developed to be used together with facility monitoring and control systems (FMCS). This paper describes the testing of the new coupling system, in which a detailed management program is embedded for real time control decision making. First, a survey was conducted to evaluate the current power consumption of the facility systems, and found that HVAC is the most energy intensive system. Then a case study was performed, while the plant was in operation, to demonstrate the feasibility of the new coupling system, and a 9.6% chiller efficiency increase and total 23.2% annual energy saving for the chillers were reached, by optimizing the part load ratio condition of chillers and pumps. The results from in situ experiments show that applying this energy management system to the IT industry is feasible. A better custom-made FMCS with EMS, and full scale testing to greatly increase the overall energy efficiency, is recommended.
[en] Highlights: • Instantaneous optimization method based on efficiency maps is proposed. • The energy sent to or supplied from the hybrid energy source is focused. • The efficiency of this energy is introduced as a new cost function to be maximized. • The results of our method are compared to that of DP, ECMS and MPC methods. • Our method provides competitive results with a lower computational load. - Abstract: This paper presents an instantaneous optimization algorithm based on the knowledge of the efficiency maps of the internal combustion engine (ICE) and the generator for the energy management system in hybrid electric vehicles. The proposed method formulates a new cost function representing the analytical expression of the overall energy efficiency of the hybrid energy source (i.e. ICE/generator set + battery pack) which is calculated based on the energy flow at the DC bus. Engine operating points are determined by assessing not only the efficiency map of the engine but also the efficiency map of the generator and the charge/discharge efficiency of the battery pack in order to maximize the efficiency of the energy delivered from the hybrid energy source to the drive system. The performance of the proposed method is analyzed and demonstrated on a hybrid electric bus developed in MATLAB/Simulink for different driving cycle conditions and the results have been compared with alternative optimization methods such as equivalent consumption minimization strategy (ECMS), model predictive control (MPC) and dynamic programming (DP) approach. The simulation results show that the proposed method provides a competitive performance with a lower computational burden compared to the alternative methods for different state of charge (SOC) ranges and drive cycle conditions
[en] Highlights: • We used AHP method to prioritize manufacturing sectors in Serbia. • Priorities for energy management improvement according to five criteria. • Rank 1 – “Manufacture of food products”. • Rank 2 – “Manufacture of motor vehicles, trailers and semi-trailers”. • Rank 3 – “Manufacture of other non-metallic mineral products”. - Abstract: Manufacturing, which is destined to play the most significant role in the reindustrialization of Serbia is also one of the largest energy consumers and environmental polluters. In accordance with this, a large number of energy and environment management initiatives have been implemented over the years. In developed countries, these initiatives are at an advanced level, but not in Serbia. A group of manufacturers in Serbia has recognized the significance of the environmental initiatives implementation, but the interest in energy management improvement has remained low. Although these initiatives can be used to achieve cost reduction in industry, not all the manufacturing sectors equally value the importance of energy management improvement. Among all the manufacturing sectors, it is necessary to prioritize those with the potentials for energy management improvement, which can be done using different methods. In this paper, the AHP (Analytic Hierarchy Process) method was used to prioritize manufacturing sectors in Serbia in the area of energy management improvement. Using a created AHP questionnaires criteria weights were selected. These questionnaires were completed by the experts from the Serbian Chamber of Commerce and Industry, providing us with the opportunity to evaluate the Serbian manufacturing sectors based on the real life data. The results of the AHP method, which was used as the prioritization instrument, and their analysis are presented in the paper. As a part of a wider study, aimed at the improvement of the energy management in Serbia, the three manufacturing sectors with the highest priority (“Manufacture of food products”, “Manufacture of motor vehicles, trailers and semi-trailers”, “Manufacture of other non-metallic mineral products”) will be analyzed in the future research in terms of energy process flows, energy management system implementation and other relevant issues
[en] Highlights: • A coordinated multi-agent system is proposed for reactive power management. • A linear quadratic regulator with a proportional integral controller is designed. • Proposed multi-agent scheme provides accurate estimation and control of the system. • Voltage stability is improved with proper power management for different scenarios. • Results obtained from the proposed scheme is compared to the traditional approach. - Abstract: In this paper, a new agent-based distributed reactive power management scheme is proposed to improve the voltage stability of energy distribution systems with distributed generation units. Three types of agents – distribution system agent, estimator agent, and control agent are developed within the multi-agent framework. The agents simultaneously coordinated their activities through the online information and energy flow. The overall achievement of the proposed scheme depends on the coordination between two tasks – (i) estimation of reactive power using voltage variation formula and (ii) necessary control actions to provide the estimated reactive power to the distribution networks through the distributed static synchronous compensators. A linear quadratic regulator with a proportional integrator is designed for the control agent in order to control the reactive component of the current and the DC voltage of the compensators. The performance of the proposed scheme is tested on a 10-bus power distribution network under various scenarios. The effectiveness is validated by comparing the proposed approach to the conventional proportional integral control approach. It is found that, the agent-based scheme provides excellent robust performance under various operating conditions of the power distribution network.
[en] Highlights: • An energy management system is proposed for off-grid PV systems, based on fuzzy logic. • The proposal guarantees the energy balance and battery protection. • The approach is demonstrated using data measured at the target location. - Abstract: A fuzzy-logic based methodology is proposed and evaluated for energy management in off-grid installations with photovoltaic panels as the source of energy and a limited storage capacity in batteries. The decision on the connection or disconnection of components is based on fuzzy rules on the basis of the Photovoltaic Panel Generation measurement, the measured power required by the load, and the estimation of the stored energy in the batteries (this last is obtained from the estimation of the Depth-of-Discharge). The algorithm aims to ensure the system’s autonomy by controlling the switches linking the system components with respect to a multi-objective management criterion developed from the requirements (supply of the load, protection of the battery, etc.). Detailed tests of the proposed system are carried out using data (irradiation, temperature, power consumption, etc.) measured in a household at the target area at several days of the year. The results demonstrate that the proposed approach achieves the objectives of system autonomy, battery protection and power supply stability. Compared with a basic algorithm, the proposed algorithm is not sensitive to sudden changes in atmospheric parameters and avoids overcharging the battery
[en] This paper aims to present a new type of series-parallel hybrid electric bus and its energy management strategy. This hybrid bus is a post-transmission coupled system employing a novel transmission as the series-parallel configuration switcher. In this paper, the vehicle architecture, transmission scheme and numerical models are presented. The energy management system governs the mode switching between the series mode and the parallel mode as well as the instantaneous power distribution. In this work, two separated controllers using fuzzy logic called Mode Decision and Parallel-driving Energy Management are employed to fulfill these two tasks. The energy management strategy and the applications of fuzzy logic are described. The strategy is validated by a forward-facing simulation program based on the software Matlab/Simulink. The results show that the energy management strategy is effective to control the engine operating in a high-efficiency region as well as to sustain the battery charge state while satisfy the drive ability. The energy consumption is theoretically reduced by 30.3% to that of the conventional bus under transit bus driving cycle. In addition, works need future study are also presented.