Home energy management system (HEMS) is an important problem that has been attracting significant attentions in the recent years. However, the conventional HEMS includes several shortcomings. The ...conventional HEMSs mainly utilize battery energy storage system (BESS) to deal with energy uncertainties. But they only ascertain optimal charging-discharging pattern for BESS and the power and capacity of BESS are not optimally determined. Furthermore, most of the HEMSs are modeled as a mixed integer linear programming (MILP) including linearization and relaxations. Additionally, considering all possible operating conditions for home has not been adequately addressed in the existing HEMSs. The possible operating conditions are (i) receiving energy from the main grid (i.e., purchasing energy), (ii) sending energy to the utility grid (i.e., selling energy), (iii) working on standalone mode as disconnected from the network (i.e., net-zero energy building). As a result, current paper deals with these existing challenges at the same time. This paper presents HEMS including small-scale wind turbine, BESS, load curtailment option, and fuel cell vehicle. The introduced HEMS not only determines optimal charging-discharging pattern for BESS, but also specifies optimal capacity and optimal rated power of the BESS at the same time. The proposed HEMS is expressed as a mixed integer nonlinear programming (MINLP) and solved by cultural algorithm as an effective Meta-heuristic optimization algorithm. All three operating conditions are considered for home. Output power of wind unit is modeled by Gaussian probability distribution function (PDF) and Monte-Carlo simulation (MCS) is applied to deal with uncertainties. Results emphasize on the feasibility and usefulness of the introduced HEMS.
•An efficient home energy management system (HEMS) is addressed.•Battery energy storage system (BESS) and small-scale wind turbine are utilized.•Charging-discharging regime and capacity of BESS are optimally determined.•Home can sell energy to network, buy energy from network, or work on islanding mode.•The proposed HEMS significantly reduces annual electricity bill in the home.
This paper addresses an optimal model reference adaptive system (MRAS) to design power system stabilizer (PSS) in multi-machine electric power systems. Weighting factors of the proposed MRAS are ...adjusted by particle swarm optimization (PSO) as well as its input signal is limited by a normalization technique to assure network stability. The proposed modified-optimal MRAS-PSS is evaluated against conventional PSS to demonstrate its advantages. In order to investigate the performance of the proposed MRAS-PSS under parametric uncertainties, three operating conditions are defined and simulated. Several nonlinear and time-domain simulations are carried out to validate the viability and effectiveness of the proposed MRAS-PSS under network uncertainties.
Renewable energy resources are often known as cost-effective and lucrative resources and have been widely developed due to environmental-economic issues. Renewable energy utilization even in small ...scale (e.g., microgrid networks) has attracted significant attention. Energy management in microgrid can be carried out based on the generating side management or demand side management. In this paper, portable renewable energy resource are modeled and included in microgrid energy management as a demand response option. Utilizing such resources could supply the load when microgrid cannot serve the demand. This paper addresses energy management and scheduling in microgrid including thermal and electrical loads, renewable energy sources (solar and wind), CHP, conventional energy sources (boiler and micro turbine), energy storage systems (thermal and electrical ones), and portable renewable energy resource (PRER). Operational cost of microgrid and air pollution are considered as objective functions. Uncertainties related to the parameters are incorporated to make a stochastic programming. The proposed problem is expressed as a constrained, multi-objective, linear, and mixed-integer programing. Augmented Epsilon-constraint method is used to solve the problem. Final results and calculations are achieved using GAMS24.1.3/CPLEX12.5.1. Simulation results demonstrate the viability and effectiveness of the proposed method in microgrid energy management.
•Introducing portable renewable energy resource (PRER) and considering effect of them.•Considering reserve margin and sensitivity analysis for validate robustness.•Multi objective and stochastic management with considering various loads and sources.•Using augmented Epsilon-constraint method to solve multi objective program.•Highly decreasing total cost and pollution with PRER in stochastic state.
This paper presents a control mechanism on high voltage direct current (HVDC) transmission line for frequency/voltage regulation, fault ride through (FRT) capability, and cyber‐attack/fault ...detection. The network under study consists of two areas with different frequencies that are connected through one 300 km HVDC line. The proposed control system regulates the frequency in both areas by managing power through HVDC line. The converters on both sides of HVDC line are controlled to handle faults on the DC and AC sections as well as improving fault ride through capability. The control strategies are implemented and operated depending on fault/cyber‐attack type and behaviour. In this respect, the control mechanism may change the firing angle of converters, switch their operating mode from rectifier to converter and vice‐versa or even block the converters. The proposed paradigm successfully distinguishes between the cyber‐attacks and faults. The simulations in MATLAB software validate that the proposed mechanism realizes all the objectives and the cyber‐attacks are completely identified and separated from the faults.
A resilient control system in the island microgrid including AC and DC buses is designed here. The DC bus is supported by fuel cell, solar cell and battery and the AC bus is equipped with diesel ...generator and wind turbine. The AC bus is sectionalized into three sub‐buses that enables to continue operation when one section is not functioning. The connection between DC and AC buses is made by two parallel three‐phase lines each line made by three single‐phase inverters. The objectives are to eliminate the harmonics, the unbalanced load management, dealing with outage of resources and short circuits, providing backup strategies and supplying critical loads under all events. The simulations are performed by MATLAB/Simulink. It is demonstrated that the resilient control technique can achieve all the defined purposes at the same time. The harmonics are eliminated, the unbalanced load issues are dealt with and the microgrid has sufficient resilience against outages and faults.
Battery energy storage systems (ESS) are the proper technologies to reduce operational cost of electrical networks as well as smoothing wind uncertainty. However, some characteristics of the battery ...energy storage systems have not been accurately analyzed such as coordination of initial energy and depth of discharge (DOD) and determining their optimal levels. Moreover, the impacts of these parameters on the planning and operational costs have not been appropriately addressed. In order to address such shortcomings, current paper presents a unified stochastic planning on battery energy storage systems in electric power systems including wind power plants. The proposed planning considers following items as objective function and optimizes them: cost of energy in the network (i.e., generators fuel cost) and investment-operational costs and lifetime of battery energy storage systems. The design variable are also classified in three categories as (i) optimal generation scheduling (i.e., determining optimal generation pattern for all generators at each hour over the day), (ii) optimal energy storage planning (i.e., denoting capacity of batteries, nominal power of interfacing converters, and location of battery energy storage units), and (iii) optimal energy storage scheduling (i.e., determining optimal charging-discharging pattern, initial energy, depth-of-discharge, lifetime, and life-cycle for energy storage units). All of these items are carried out through stochastic modeling under wind power uncertainties. The paper presents a proper coordination between design variables such as initial energy and depth-of-discharge in order to minimize the network operational cost, maximizing lifetime of battery energy storage system, and smoothing wind uncertainty. The efficiency of the introduced methodology is demonstrated through various analyses and comparative studies.
•Problem minimizes generators cost and storage costs at the same time.•Optimal capacity, power, and location of storage systems are determined.•Optimal charging-discharging, depth of discharge, and initial energy is designed.•Optimal generation pattern is scheduled for generators.•Stochastic planning is carried out to tackle the uncertainties of wind power.
Battery energy storage system (BESS) has already been studied to deal with uncertain parameters of the electrical systems such as loads and renewable energies. However, the BESS have not been ...properly studied under unbalanced operation of power grids. This paper aims to study the modelling and operation of BESS under unbalanced-uncertain conditions in the power grids. The proposed model manages the BESS to optimize energy cost, deal with load uncertainties, and settle the unbalanced loading at the same time. The three-phase unbalanced-uncertain loads are modelled and the BESSs are utilized to produce separate charging/discharging pattern on each phase to remove the unbalanced condition. The IEEE 69-bus grid is considered as case study. The load uncertainty is developed by Gaussian probability function and the stochastic programming is adopted to tackle the uncertainties. The model is formulated as mixed-integer linear programming and solved by GAMS/CPLEX. The results demonstrate that the model is able to deal with the unbalanced-uncertain conditions at the same time. The model also minimizes the operation cost and satisfies all security constraints of power grid.
The idea of Hybrid Energy Storage System (HESS) lies on the fact that heterogeneous Energy Storage System (ESS) technologies have complementary characteristics in terms of power and energy density, ...life cycle, response rate, and so on. In other words, high power ESS devices possess fast response rate while in the contrary, high energy ESS devices possess slow response rate. Therefore, it may be beneficial to hybridize ESS technologies in the way that synergize functional advantages of two heterogeneous existing ESS technologies As a consequence, this hybridization provides excellent characteristics not offered by a single ESS unit. This new technology has been proposed and investigated by several researchers in the literature particularly in the fields of renewable energy and electrified transport sector. In this context and according to an extensive literature survey, this paper is to review the concept of the HESS, hybridization principles and proposed topologies, power electronics interface architectures, control and energy management strategies, and application arenas.
This paper addresses a novel multi-stage dynamic distribution network expansion planning (DNEP) taking into account the electric vehicle (EV) charging station based on the battery swapping model. The ...battery swapping station (BSS) is transferred seasonally and integrated to different buses in various seasons in order to defer the investment on the new lines. The BSS is as well integrated with rooftop solar panels. The uncertainties of loads and renewable energies are taken into account and handled by stochastic programming. The charging scheduling is optimized for all the batteries inside the BSS. A comparative study is presented for 3 cases including expansion planning without BSS, planning with a fixed location of BSS, and the proposed method (i.e., planning with seasonally transferred BSS). The numerical simulations demonstrate that the proposed model transfers the BSS every six months, where, it is installed on bus 25 in seasons 1 and 2, and on bus 17 in seasons 3 and 4. The congested lines such as lines 2 to 19, 16 to 17, and 6 to 7 are expanded by installing new lines in years 2, 4, and 5, respectively. The BSS sends power to the external grid in on-peak loading times such as hours 12 to 15 and 18 to 21. The proposed model reduces the planning cost by 5% compared to the expansion planning with a fixed location for BSS.
•Multi-stage dynamic distribution network expansion planning is addressed.•Planning is combined with the battery swapping station.•Battery swapping station is seasonally transferred between buses of the grid.•Station is equipped with rooftop solar panels and solar uncertainty is modeled.•Charging scheduling is optimized for all batterie inside the swapping station.
► To overcome the disadvantages of DC model in Transmission Expansion Planning, AC model should be used. ► The Transmission Expansion Planning associated with Reactive Power Planning results in fewer ...new transmission lines. ► Electricity market concepts should be considered in Transmission Expansion Planning problem. ► Reliability aspects should be considered in Transmission Expansion Planning problem. ► Particle Swarm Optimization is a suitable optimization method to solve Transmission Expansion Planning problem.
Transmission Expansion Planning (TEP) is an important issue in power system studies. It involves decisions on location and number of new transmission lines. Before deregulation of the power system, the goal of TEP problem was investment cost minimization. But in the restructured power system, nodal prices, congestion management, congestion surplus and so on, have been considered too. In this paper, an AC model of TEP problem (AC-TEP) associated with Reactive Power Planning (RPP) is presented. The goals of the proposed planning problem are to minimize investment cost and maximize social benefit at the same time. In the proposed planning problem, in order to improve the reliability of the system the Expected Energy Not Supplied (EENS) index of the system is limited by a constraint. For this purpose, Monte Carlo simulation method is used to determine the EENS. Particle Swarm Optimization (PSO) method is used to solve the proposed planning problem which is a nonlinear mixed integer optimization problem. Simulation results on Garver and RTS systems verify the effectiveness of the proposed planning problem for reduction of the total investment cost, EENS index and also increasing social welfare of the system.
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