Results 1 - 10 of 67
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[en] In this study, a mathematical model of an ice thermal energy storage (ITES) system for gas turbine cycle inlet air cooling is developed and thermal, economic, and environmental (emissions cost) analyses have been applied to the model. While taking into account conflicting thermodynamic and economic objective functions, a multi-objective genetic algorithm is employed to obtain the optimal design parameters of the plant. Exergetic efficiency is chosen as the thermodynamic objective while the total cost rate of the system including the capital and operational costs of the plant and the social cost of emissions, is considered as the economic objective. Performing the optimization procedure, a set of optimal solutions, called a Pareto front, is obtained. The final optimal design point is determined using TOPSIS decision-making method. This optimum solution results in the exergetic efficiency of 34.06% and the total cost of 28.7 million US$ y−1. Furthermore, the results demonstrate that inlet air cooling using an ITES system leads to 11.63% and 3.59% improvement in the output power and exergetic efficiency of the plant, respectively. The extra cost associated with using the ITES system is paid back in 4.72 years with the income received from selling the augmented power. - Highlights: • Mathematical model of an ITES system for a GT cycle inlet air cooling is developed. • Exergetic, economic and environmental analyses were performed on the developed model. • Exergy efficiency and total cost rate were considered as the objective functions. • The total cost rate involves the capital, maintenance, operational and emissions costs. • Multi-objective optimization was applied to obtain the Pareto front
[en] this paper presents a two-level stochastic microgrid planning tool. The proposed tool determines the optimal location and size of different technologies through a long-term plan as well as the optimal operation strategy for technologies through a short-term plan. The proposed planning tool considers distributed generation resources, energy storage systems, and lines as candidates for the expansion. One of the key characteristics of the introduced planning is its ability to tackle load and renewable energies uncertainties through stochastic planning. Both the long-term and short-term plans are mathematically expressed as mixed integer nonlinear programming problems and solved by using a strong Meta-heuristic optimization algorithm. Simulation results demonstrate that the proposed two-level planning method reduces the planning cost compared to the conventional method (i.e., only long-term planning). As well, it is indicated that considering line as an option for the expansion reduces the planning cost and increases the flexibility of the planning. - Highlights: • A stochastic expansion planning is addressed on microgrids. • The planning tool includes two long-term and short-term plans. • Wind unit, solar panel, energy storage system, and line are installed by plan. • The planning tool is expressed as a mixed integer nonlinear programming. • Meta-heuristic optimization algorithm is applied so solve the problem.
[en] The integration of renewable energy sources (RESs) in distribution networks has brought great challenges to the volt/var management due to their intermittency and volatility. This paper proposes a two-stage energy management framework of distribution networks to facilitate the accommodation of high wind energy penetration. In the proposed framework, the volt/var management problem is formulated and decomposed as a two-stage energy scheduling optimization model with different time frames considering the uncertainties of wind energy and load forecasts. In the first stage, a scenario-based stochastic day-ahead scheduling model is formulated to optimize the 24-h charging/discharging scheme of energy storage system (ESS) and power generation of diesel generator (DG) in order to minimize the expected operation cost. Based on the stochastic optimal scheduling results in the first stage, the second stage implements the multiobjective volt/var optimization (VVO) to determine the optimal real-time operation of volt/var control devices, considering the costs of adjusting the control devices (CACDs). The proposed method has been fully evaluated and benchmarked on a 69-bus distribution network under various operational scenarios to demonstrate its superiority on various performance metrics and further confirm its effectiveness and efficiency for distribution networks to accommodate a high penetration of wind energy. - Highlights: • A multiobjective VVO is proposed for distribution networks with RESs. • A two-stage energy management framework is used to accommodate the wind energy. • ESS is utilized to reduce the network loss and maximize economic benefits. • ESS degradation cost and CACDs are considered in the volt/var management.
[en] This paper presents an optimal planning and scheduling on energy storage systems (ESSs) for congestion management in electric power systems including renewable energy resources. The proposed problem finds optimal capacity and charging-discharging regime of ESSs. The storage units are optimally charged and discharged to tackle the uncertainty related to wind-solar units as well as relief congestion in the lines. Output power of solar and wind units is modeled by Gaussian probability distribution function (PDF) and Monte-Carlo simulation (MCS) is applied to tackle the uncertainty. Simulation results demonstrate that the proposed planning can manage congestion of the network efficiently while dealing with wind and solar resources uncertainties. - Highlights: • Congestion management is addressed through energy storage planning. • Uncertainty of wind and solar units is considered. • Monte-Carlo simulation is carried out to deal with the uncertainty. • Scenario based stochastic planning is applied to solve the problem. • The planning can tackle the uncertainties and manage congestion of the network.
[en] Thanks to the lower overall emission of Electric Vehicles, the promising transportation has attracted numerous attentions from industry and academy. However, as a consequence of lower energy density in widely adopted electrochemical energy source-battery, the driving range per charge presents a major barrier for electric vehicle's large-scale commercialization. Additionally, the limited battery life and extra costs associated with its replacement are other negative factors that hinder the development of electric vehicle. Currently, the one-speed gearbox is dominant in electric vehicles' market though it is only a trade-off between manufacturing cost and vehicle performance. Therefore, multi-speed electrified powertrains have been proposed and investigated in this paper to pursue the improvement of energy efficiency and dynamic performance without increasing battery size. In addition, supercapacitor, as the supplementary to battery, is combined with multi-speed transmissions to improve driving range and battery life. The combination of two advanced technologies are investigated in both B and E-class electric vehicle. Results demonstrate that considerable benefits attained for both small and large passenger vehicles through the application of multi-speed transmissions. The effectiveness of hybrid energy storage system in protecting battery from damage is verified. The relationship of hybrid energy storage system and multi-speed transmission is reported. - Highlights: • Comparison of multi-speed powertrain configurations and drivability performance. • Discussion of gear ratio selection for multi-speed BEV. • Efficiency improvement and battery capacity reduction are reported. • Performances of hybrid energy storage system are presented. • Battery service life extension and current fluctuation reduction are compared.
[en] The Optimal day-ahead Scheduling of Combined Heat and Power (OSCHP) units is a crucial problem in the energy management of Active Distribution Networks (ADNs), especially in the presence of Electrical and Thermal Energy Storages considering Load Commitment (LC) programs. The ADN operator may use Combined Heat and Power (CHP) units to supply its Industrial Customers (ICs) and can transact electricity with the upstream wholesale electricity market. The OSCHP problem is a Mixed Integer Non Linear Programming (MINLP) problem with many variables and constraints. However, the optimal operation of CHP units, Electrical and Thermal Energy Storages considering LC programs and contingency scenarios, may highly complicate this problem. In this paper, linearization techniques are adopted to linearize equations and a two-stage Stochastic Mixed-Integer Linear Programming (SMILP) model is utilized to solve the problem. The first stage models the behavior of operation parameters and minimizes the operation costs, verifies the feasibility of the ICs' requested power exchanges and the second stage considers LC programs and the system's stochastic contingency scenarios. The effectiveness of the proposed algorithm has been demonstrated considering 18-bus, 33-bus and 123-bus IEEE test systems. - Highlights: • Optimal day-ahead Scheduling of Combined Heat and Power units with Energy Storage systems. • Load Commitment Programs and inter-zonal power exchange on the operation scheduling scenarios. • A stochastic model to assess the uncertainty of system contingencies and upward wholesale market.
[en] A dual-mode thermochemical sorption energy storage system using working pair of expanded graphite/SrCl2-NH3 was proposed for seasonal solar thermal energy storage. The proposed system has two working modes to produce useful heat with an expected temperature during the discharging phase according to the different ambient temperatures, including the direct heating supply and temperature-lift heating supply. Solar thermal energy is transformed into chemical bonds and stored in summer, and the stored energy is released in the form of chemical reaction heat in winter. The direct heating supply mode is adopted at a relatively high ambient temperature in winter. The effective energy storage density is higher than 700 kJ/kg and the corresponding system COP is 0.41 when the heat output temperature and ambient temperature are 35 °C and 15 °C, respectively. The specific heating power increases with the decrease of heat output temperature for a given ambient temperature. The temperature-lift heating supply mode is adopted to upgrade the heat output temperature at a low ambient temperature below 0 °C in winter. It can produce heat with a temperature above 70 °C although the ambient temperature is as low as −15 °C. It is desirable to further improve the system performance using low mass ratio and high global conversion. Experimental results showed the advanced dual-mode thermochemical sorption energy storage technology is feasible and effective for seasonal solar thermal energy storage. - Graphical abstract: Working temperature range of dual-mode thermochemical sorption energy storage system during the discharging phase in winter. - Highlights: • A dual-mode seasonal solar thermochemical sorption energy storage system is developed. • The sorption working pair is strontium chloride/expanded graphite-ammonia. • Two working modes can be performed according to the different heat requirements in winter. • Energy density and COP of direct heating supply mode are 706 kJ/kg and 0.41 respectively. • Temperature-lift heating supply mode can meet heat demand at low ambient temperature.
[en] Renewable energy generation is expected to continue to increase globally due to renewable energy targets and obligations to reduce greenhouse gas emissions. Some renewable energy sources are variable power sources, for example wind, wave and solar. Energy storage technologies can manage the issues associated with variable renewable generation and align non-dispatchable renewable energy generation with load demands. Energy storage technologies can play different roles in each of the step of the electric power supply chain. Moreover, large scale energy storage systems can act as renewable energy integrators by smoothing the variability. Compressed air energy storage is one such technology. This paper examines the impacts of a compressed air energy storage facility in a pool based wholesale electricity market in a power system with a large renewable energy portfolio
[en] This paper analyzes the concept of a decentralized power system based on wind energy and a pumped hydro storage system in a tall building. The system reacts to the current paradigm of power outage in Latin American countries caused by infrastructure limitations and climate change, while it fosters the penetration of renewable energy sources (RES) for a more diversified and secure electricity supply. An explicit methodology describes the assessment of technical, operational and economic potentials in a specific urban setting in Caracas/Venezuela. The suitability, applicability and the impacts generated by such power system are furthermore discussed at economic, social and technical level. - Highlights: ► We have modeled an innovative pico pumped hydro-storage system and wind power system for tall buildings. ► We conducted technical, economic and social analysis on these energy supply and storage alternatives. ► The energy storage system can achieve efficiencies within 30% and 35%. ► The energy storage is realistic and economic sensible in comparison to other solutions. ► The impacts of such a system in the current living conditions and safety issues of the building are minimum
[en] Introducing Combined Heat and Power (CHP) units into Active Distribution Network (ADN) can significantly affect the problem of optimal generation scheduling. A new method for solving the problem of Optimal Scheduling of Combined Heat and Power (OSCHP) units of an ADN with Electric Storage Systems (ESSs) and Thermal Storage Systems (TSSs) considering Industrial Customers (ICs) Inter-Zonal Power Exchanges (IZPEs) is presented. The ADN operator may use CHP units to supply its ICs and based on smart grid conceptual model, it can transact electricity with upstream network. However, the electricity transactions between the ADN and its ICs in normal and contingency scenarios may highly complicate this problem. In this paper, linearization techniques are adopted to linearize equations and a two-stage stochastic mixed integer linear programming (SMILP) model is utilized to solve the problem to determine the optimal generation scheduling units. The first stage models the behaviour of operation parameters, minimizes the operation costs, and checks the feasibility of the ICs' requested firm and non-firm IZPEs, while the second stage considers system's stochastic contingency scenarios. The competitiveness of ADN in the deregulated market can be improved by adjusting the proposed decision variables in the two-stage optimization procedure. The proposed method is applied to 18- and 123-bus IEEE test systems to thoroughly demonstrate the benefits of implementing inter-zonal power exchanges. - Highlights: • A method for solving the optimal scheduling of combined heat and power units is presented. • A two-stage stochastic mixed integer linear programming model is utilized. • The proposed method is applied to 18- and 123-bus IEEE test systems. • The benefits of implementing inter-zonal power exchanges are demonstrated.