Determination of optimal reserve contribution of thermal units to afford the wind power uncertainty

Due to unforeseen variations in wind speed profiles, wind farm integrations are recognized as intermittent and uncertain energy contributors. More specifically, integration of such renewable energy resources aligned with the conventional thermal units although reduces the emissions and brings about a clean environment, it introduces serious problems in assigning optimal and reliable level of these units in load supplying and spinning reserve provision. This situation is more intensified considering the uncertainties arisen by the power system loading demand. To facilitate such operational hurdles, the ongoing study puts forward an efficient model for assigning the optimal spinning reserve which accommodates the uncertainties in both the wind speed and load profiles. Stochastic behavior of these parameters is simulated by generating a proper number of scenarios through the Monte Carlo simulation (MCS) approach. Then, each of these scenarios is evaluated based on the established linear mixed integer approach in a deterministic fashion. Accordingly, a computationally efficient approach is obtained paving the way for real-world implementations and assuring the global optimum results. The proposed approach is applied to a 12-unit test system including 10 thermal units and 2 wind farms. Results are reflected in terms of the commitment status, energy dispatches, and reserve contributions of each committed unit. A comprehensive discussion is conducted to disclose the possible improvements

Transient stability enhancement in multiple‐microgrid networks by cloud energy storage system alongside considering protection system limitations

Abstract The gas turbine synchronous generators (GTSGs) are widely deployed as distributed generations (DGs) in countries with massive natural gas production owing to their low prices. However, due to the low inertia time constants of these synchronous‐based DGs, they are more susceptible to power grid faults which stands as a transient stability issue in networks with multiple microgrids (MGs). On the other hand, the cloud energy storage system (CESS) is a new concept that centralizes the individual distributed energy storage of one or more MGs. Here, the employment of CESS with synchronverter grid connections creates a suitable opportunity for improving the transient stability of the network by providing higher inertia. This is while the fault current contribution of the synchronverter‐based CESS imperils protection constraints in these networks. Therefore, a proper protection coordination index (PCI) is considered in the conducted study to identify the optimal size of the synchronverter‐based CESS through a two‐stage optimization algorithm that preserves the protection constraints among protective devices. Finally, the transient stability of the network with synchronverter‐based CESS is assayed by calculation of the critical clearing time (CCT) for faults. Numerical studies are carried out on the IEEE 33‐bus test system. Results are discussed in depth

A comprehensive stochastic energy management system in reconfigurable microgrids

This paper addresses the joint stochastic energy and reserve scheduling problem in microgrids (MGs). The established approach proposes a novel high-performance energy management system (EMS) making use of automatically controlled switches (ACSs). Accordingly, besides the optimal scheduling of active elements namely distributed generations (DGs) and responsive loads (RLs), the optimal topology of the network for each of the scheduling intervals is determined as well. Likewise, the effects of the reconfiguration process in probable variations of the scheduled energy patterns in DGs, RLs, and grid purchases are thoroughly assessed to highlight the alterations in unallocated capacities of these resources. Moreover, the uncertainties associated with both the load and wind speed forecasting errors are suitably accommodated through the reserve allocations. The proposed optimization procedure is formulated as a mixed-integer non-linear problem and resolved using a genetic algorithm (GA). The effectiveness of the projected framework is verified utilizing a typical MG, and the obtained numerical results are discussed in depth. Copyright © 2016 John Wiley & Sons, Ltd

A new hybrid control technique for operation of DC microgrid under islanded operating mode

This study proposes a novel combined primary and secondary control approach for direct current microgrids, specifically in islanded mode. In primary control, this approach establishes an appropriate load power sharing between the distributed energy resources based on their rated power. Simultaneously, it considers the load voltage deviation and provides satisfactory voltage regulation in the secondary control loop. The proposed primary control is based on an efficient droop mechanism that only deploys the local variable measurements, so as to overcome the side effects caused by communication delays. In the case of secondary control, two different methods are devised. In the first, low bandwidth communication links are used to establish the minimum required data transfer between the converters. The effect of communication delay is further explored. The second method excludes any communication link and only uses local variables. Accordingly, a self-sufficient control loop is devised without any communication requirement. The proposed control notions are investigated in MATLAB/Simulink platform to highlight system performance. The results demonstrate that both proposed approaches can effectively compensate for the voltage deviation due to the primary control task. Detailed comparisons of the two methods are also provided.Peer reviewe

A two-stage robust-intelligent controller design for efficient LFC based on Kharitonov theorem and fuzzy logic

This paper proposes an efficient load frequency control (LFC) approach based on robust and intelligent methods. Practically speaking, proportional-integral (PI) controller is widely deployed in LFC structure. Basically, the parameters of PI controller are adjusted based on trial-and-error or classic control methods. In such manners, robust performance of PI controller cannot be guaranteed in disturbances including load changes or parameter variations. In this research, at the first stage, the gain values of PI controller are tuned in an offline manner based on Kharitonov theorem which strengthens the validity of the controller against the variations in time constants of turbine and governor. As another aspect of uncertainty, power system loading demand is changed ceaselessly. To accommodate such conditions, at the second stage, the initial gain values based on Kharitonov theorem are adapted in an online manner based on fuzzy logic approach. The fuzzy controller, as an aspect of intelligence, adapts the proportional and integral gains through appropriate membership functions in an online fashion. Frequency deviation and its derivative are selected as efficient input signals for the fuzzy controller. Detailed numerical studies are conducted to assess performance of the proposed approach. Results demonstrate a reliable frequency performance against different uncertainties

A multi-stage linearized interactive operation model of smart distribution grid with residential microgrids

This paper addresses an interactive energy scheduling model developed between distribution system and residential microgrids (RMGs). To make such concepts, a three-stage mathematical programming framework is proposed. Residential energy management (REM) approach which is in interaction with residential microgrid operator (RMGO) is developed which contains two stages, sequentially. The main goal of these stages is to modify RMGs day-ahead load profile by considering the minimized total daily energy expenses of each home at each RMG. Moreover, in these stages, in addition to existing fixed-loads at each evaluated residential homes, in-home energy management (iHEM) systems are responsible for adjusting the shiftable appliances and small scale distributed energy resources (DERs) commitment. In third stage, besides the interactions between distribution system operator (DSO) and RMG operators (RMGOs), optimal operation cost of the distribution system is determined as well. In this way, optimal scheduling of distribution system active elements namely large scale DERs are considered and the changing trends in energy exchanges, power losses, and voltage profile are addressed. To lower the computational burden of the proposed model, linearization techniques are applied in the proposed model. Simulation studies are reported on modified IEEE 33-bus distribution test system to assess the performance of the proposed model. Results are discussed in depth

An optimal procedure for sizing and siting of DGs and smart meters in active distribution networks considering loss reduction

The presence of responsive loads in the promising active distribution networks (ADNs) would definitely affect the power system problems such as distributed generations (DGs) studies. Hence, an optimal procedure is proposed herein which takes into account the simultaneous placement of DGs and smart meters (SMs) in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Seeking to power loss minimization, the optimization procedure is tackled with genetic algorithm (GA) and tested thoroughly on 69-bus distribution test system. Different scenarios including variations in the number of DG units, adaptive power factor (APF) mode for DGs to support reactive power, and individual or simultaneous placing of DGs and SMs have been established and interrogated in depth. The obtained results certify the considerable effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the lowest value of power losses as well