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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] Highlights: • Improving the utilization of wind power by the demand response of residential hybrid energy system. • An optimal scheduling of home energy management system integrating micro-CHP. • The scattered response capability of consumers is aggregated by demand bidding curve. • A stochastic day-ahead economic dispatch model considering demand response and wind power. - Abstract: As the installed capacity of wind power is growing, the stochastic variability of wind power leads to the mismatch of demand and generated power. Employing the regulating capability of demand to improve the utilization of wind power has become a new research direction. Meanwhile, the micro combined heat and power (micro-CHP) allows residential consumers to choose whether generating electricity by themselves or purchasing from the utility company, which forms a residential hybrid energy system. However, the impact of the demand response with hybrid energy system contained micro-CHP on the large-scale wind power utilization has not been analyzed quantitatively. This paper proposes an operation optimization model of the residential hybrid energy system based on price response, integrating micro-CHP and smart appliances intelligently. Moreover, a novel load aggregation method is adopted to centralize scattered response capability of residential load. At the power grid level, a day-ahead stochastic economic dispatch model considering demand response and wind power is constructed. Furthermore, simulation is conducted respectively on the modified 6-bus system and IEEE 118-bus system. The results show that with the method proposed, the wind power curtailment of the system decreases by 78% in 6-bus system. In the meantime, the energy costs of residential consumers and the operating costs of the power system reduced by 10.7% and 11.7% in 118-bus system, respectively.
[en] The biological conversion of the Urban Solid Residuals (USR) for energy purposes comes winning importance every day, once the urban residuals became considered a source of alternative energy. To foresee the generation of resulting biogas of the process of biological decomposition of the solid residuals of organic origin in the sanitary fillers is fundamental to estimate the energy and economic balance of facilities of recovery of gas. For the appropriate determination of the potential of generation of gases you employment the calculation methodology presented by the Agency of Environmental Protection of United States. In this context, the objective of this article is to quantify the potential of electric power generation coming from the gas methane originating of the Urban Solid Residuals of the municipalities Belas, Cacuaco and Viana of the County of Luanda in Angola. The available energy power was determined annually of the three municipalities. The instinct demonstrates that the biogas flow arrives at the maximum level and it possesses the maximum available Power in the year 2037, obtaining stops the municipalities Belas, Cacuaco and Viana 3330 · 103, 1206.13 · 103 and 2809.23 · 103m"3/year of profitable methane respectively whose calculated energy potential was respectively of 2316.52, 1358.88 and 3165,02 kW. The carried out calculations not allow alone to evaluate the energy potential of the filler, but also to evaluate, in certain way, the environmental impact for the mitigation of emissions of gases of effect hothouse. (author)
[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] The smart grid is seen as a power system with realtime communication and control capabilities between the consumer and the utility. This modern platform facilitates the optimization in energy usage based on several factors including environmental, price preferences, and system technical issues. In this paper a real-time energy management system (EMS) for microgrids or nanogrids was developed. The developed system involves an online optimization scheme to adapt its parameters based on previous, current, and forecasted future system states. The communication requirements for all EMS modules were analyzed and are all integrated over a data distribution service (DDS) Ethernet network with appropriate quality of service (QoS) profiles. In conclusion, the developed EMS was emulated with actual residential energy consumption and irradiance data from Miami, Florida and proved its effectiveness in reducing consumers’ bills and achieving flat peak load profiles.
[en] Although the meaning of energy efficiency is clear, different definitions exist and important issues relating to its implementation still need to be addressed. It is now recognised that complicating factors – such as complex industrial sites and energy flows, multiple products and fuels, and the influence of production rate on energy efficiency – render it necessary to adopt a structured framework to define and measure energy efficiency more precisely. In this paper, a methodology is proposed to build such a framework. The whole energy system of a site is represented using a single matrix equation, which expresses the relationship between imported energies and energy drivers. The elements of the matrix are the specific energy consumptions of each single process. Mathematical process modelling, through statistical analysis of energy consumption data, is used to quantify the specific energy consumption as a function of the output. The results of this structured approach are relevant for energy benchmarking, budgeting and targeting purposes. Furthermore, this approach is suitable for implementation in an energy management system standard (e.g. EN 16001, ISO 50001) or LCA standard (e.g. ISO 14044). Glass and cast iron melting processes are presented in order to illustrate the application of the method. -- Highlights: ► A structured framework for energy efficiency in industrial processes is proposed. ► Two energy efficiency indicators are revised to take into account a variable output. ► The whole energy system of a factory can be represented by a single matrix equation. ► Mathematical modelling is used to characterise the energy consumption of a process. ► The results are relevant for energy benchmarking, budgeting and energy targeting.
[en] Numerical models of transmission-constrained electricity markets are used to inform regulatory decisions. How robust are their results? Three research groups used the same data set for the northwest Europe power market as input for their models. Under competitive conditions, the results coincide, but in the Cournot case, the predicted prices differed significantly. The Cournot equilibria are highly sensitive to assumptions about market design (whether timing of generation and transmission decisions is sequential or integrated) and expectations of generators regarding how their decisions affect transmission prices and fringe generation. These sensitivities are qualitatively similar to those predicted by a simple two-node model. (Author)
[en] In order to reach the EU: s 20–20–20 primary energy savings target, energy efficiency needs to increase. Previous research on energy use and energy efficiency has focused mainly on the diffusion of energy efficient technologies. The discrepancy between optimal and actual implementation of energy efficient technologies has been illustrated in numerous articles and is often referred to as the energy efficiency gap. However, efficient technologies are not the only ways to increase energy efficiency. Empirical studies have found that a cost-effective way to improve energy efficiency is to combine investments in energy-efficient technologies with continuous energy management practices. By including energy management into an estimated energy efficiency potential this paper introduces an extended energy efficiency gap, mainly in manufacturing industries and the commercial sector. The inclusion of energy management components in future energy policy will play an important role if the energy savings targets for 2020, and later 2050, are to be met in the EU. - Highlights: ► Theoretical contributions examining the role of energy management have been rare. ► Studies have illustrated that adaptation levels of energy management are low. ► By including energy management this paper introduces an extended energy efficiency gap.