IET Energy Systems Integration最新文献

The fluctuating outputs from renewable energy sources (RESs) and variable load power demand deteriorate the current quality, thus an improved generalised integrator with a frequency-locked loop (IGI-FLL) control strategy is used, which is not only easy but simple to attain a quick and precise fundamental extraction. IGI-FLL control method is utilised with all-pass filter and is capable to accomplish enhanced harmonics, noise and DC offset rejection ability while estimating fundamental component of the load current. In addition, the FLL structure is used to increase the frequency immunity against voltage variations. It provides improved steady-state and dynamic performances with flexibility in parameter tuning in comparison to SOGI-FLL algorithm. It also presents a cost-effective and robust genetic algorithm (GA)-based optimisation to provide optimum battery charging and discharging power while satisfying the state-of-charge (SOC) limits under RES uncertainty. In this islanded microgrid, a Synchronous Reluctance Generator for pico-hydro and photovoltaic array is used so that this hybrid system utilises maximum solar PV array power, matches the load, or else charges the battery energy storage while maintaining power balance in the microgrid. Comparative outcomes authenticate the efficacy of the algorithm to handle the issue of RES uncertainty and load unbalance in an islanded microgrid.

The active distribution network (ADN) can provide the reactive power ancillary service (RPAS) to improve the operations of the transmission network operations (such as voltage control and network loss reduction) as distribution generation grows. In this context, an RPAS market is required to motivate the ADN to provide the RPAS to the transmission network since the transmission system operator (TSO) and the distribution system operator (DSO) are different entities. Hence, to obtain the TSO–DSO coordination in the RPAS market, this study proposes a two-stage market framework on the basis of the successive clearing of the energy and RPAS markets. Additionally, a distributed market-clearing mechanism based on an alternating direction method of multipliers (ADMM) is adopted to guarantee TSO's and DSO's information privacy. Furthermore, a binary expansion (BE) method is used to linearise the non-convex bilinear terms in the market-clearing model. The effectiveness of the proposed RPAS market framework and distributed market-clearing mechanism is validated using two different test systems with different system scales.

This study deals with a new control for a double-stage grid-integrated solar photovoltaic array (SPVA)-based energy generation system, which is based on adjoint least mean square (ALMS) control. This ALMS control algorithm has some new features: (1) it provides a fast rate of convergence, (2) harmonics mitigation ability, and (3) ease of implementation. The solar PV energy generating system includes a DC–DC boost converter, a voltage source converter (VSC), a ripple filter, a three-phase grid, and local non-linear loads. The VSC is controlled for feeding the active power from the solar array to the grid and three-phase non-linear loads. Moreover, VSC control is used to improve the grid current quality. A DC–DC boost converter is coupled between the photovoltaic array and the DC-link capacitor, which tracks the maximum SPVA power from the SPV array by using perturb & observe algorithm. Here, the main goals of SPVA generating system are to eradicate power quality problems caused by unbalanced and non-linear loads and to provide sinusoidal grid currents at solar PV array irradiance variation. Moreover, a comparison of ALMS control is made with other control algorithms. Performance of this ALMS control is studied at varying non-linear loads and under different environmental conditions on a developed prototype in the laboratory. The simulated results of the system are validated with test results. Detailed behaviour of the grid-integrated SPV system and harmonics spectrum of grid currents are given here while meeting the IEEE 519 Standard.

In the design procedure of a PV-based microgrid, optimal sizing of its components plays a significant role, as it ensures optimum utilization of the available solar energy and associated storage devices. This in turn ensures efficient and economic operation of the microgrid. Various approaches have been reported in the literature in order to approach the sizing problem in PV-based microgrids. However, the existing approaches are subjective to the requirements of the microgrid and there is no unique framework for approaching the microgrid sizing problem. In this study, a comprehensive review of the existing approaches used for sizing of PV-based microgrids with a summary of the commonly adopted design considerations has been presented. Also, the optimization problem, including the usually considered designed objectives and constraints, for PV-based microgrid sizing have been thoroughly reviewed in this study. Furthermore, the adopted approaches for solving the optimization problem associated with the sizing of a PV-based microgrid system available in the literature have been reviewed comprehensively. With a view to present a generic framework for the optimal sizing of a PV-based microgrid, this study further presents a framework based on the comprehensive review of the existing literature. The developed framework will be useful for both the practising engineers and academics to understand and apply the usual practices for optimal sizing of PV-based microgrids.

Mobile battery energy storage systems (MBESSs) represent an emerging application within the broader framework of battery energy storage systems (BESSs). By transporting lightweight BESSs, energy backup support can be provided to different geographical locations. This work studies a new scenario, in which an MBESS service provider delivers a number of BESSs to serve multiple end energy customers in an emergent grid outage event. An integrated distribution planning framework is proposed to coordinately optimise the MBESS carrier's driving paths and the distribution plans for the BESSs. The framework aims at maximising the MBESS service provider's total profit. An efficient, decomposed solving approach is developed for the proposed framework; numerical simulations are conducted to validate the effectiveness of the proposed system.

Prevalence of distributed generation drives the emergence of the ‘Virtual Power Plant (VPP)’ paradigm. A VPP aggregates distributed energy resource and can operate as a conventional power plant. In recent years, a large portion of renewable energy sources are installed in the commercial/industrial/residential building side, and their potentials and flexibilities can be aggregated in the VPP context. Nevertheless, building-side energy resources are usually managed by building energy management systems (BEMSs) with autonomous objectives and policies, making them hardly to be directly controlled by the VPP energy management system as the state-of-the-art VPP. This study systematically presents a building VPP (BVPP) architecture that aggregates building-side energy resources through the communication between the VPP energy management system and autonomous BEMSs. The implementation technologies, key components, and operation modes of BVPPs are discussed. Case studies are reported to demonstrate the effectiveness of BVPP in different operational conditions.

Aggregation of heterogeneous distributed energy resources (DERs) and prosumers for profit maximisation by virtue of the market interface has evolved into virtual power plants (VPPs). The VPP operator optimises its aggregated resources to maximise profit by participating in the wholesale electricity market. VPP resources may be geographically dispersed and connected to a transmission grid at various nodes having different locational marginal prices (LMPs). These LMPs vary throughout the day and exhibit mutual correlation. Considering this, the current study presents a profit maximisation framework for VPP operators working under multiple LMPs, with their correlated uncertainties. This work also provides VPP resource scheduling for profit maximisation, considering optimal trading at various LMP nodes for a constrained internal network. This decision is devised using Markowitz's mean-variance (M-V) criterion under expedient correlation between volatile LMPs. A numerical case study on the proposed model with the PJM market demonstrates that LMP correlation alters the role of the VPP operator. This affects its trading and scheduling decisions as a buyer/seller at various time intervals to improve its profit–risk trade-off and consequently the market interfacing of the VPP operator. The proposed model is relevant in practical market conditions for day-ahead/medium-term VPP planning while managing market uncertainty.

This work deals with a single-phase grid-fed fan type variable speed load profile system operated by a mechanical sensorless induction motor (IM) drive. A power factor corrected (PFC) boost converter is utilised for the development of the system. A full speed range of a fan with enhanced power quality during normal and abnormal grid voltage conditions is achieved by using this system. The system is simulated and analysed under variable speed and load conditions, during both the normal and weak grid, for a fan type load profile. To comply the IEEE-519 standard at the utility grid, the power quality limits are achieved by developed control. Simulated results are validated with test results obtained on a developed prototype. The simulated and test results validate the suitability of the developed system at diverse operating conditions. The operational cost of the system is reduced by the use of a high-efficiency IM and its efficiency is optimised. A combined approach of design of experiment (DOE) for reduction of variables and a particle swarm optimisation (PSO) technique with an objective function as the maximisation of efficiency is used to design and develop an IM with improved performance. Initially, parametric analysis of different variables of the IM is performed analytically to design the IM, design of experiment is used to reduce the number of variables, and different components of the motor are designed and optimised using PSO. Design simulations are performed using RMxprt analysis and finite element analysis is performed using Maxwell-2D design software. The developed high-efficiency motor is tested on a test setup in the laboratory and its tests are conducted as per the IEEE-standard 112-2017, with comparative analysis of a conventional motor of a 1.5 kW four-pole, three-phase squirrel cage IM, and simulated and experimental performances justify its suitability for grid-fed fan applications.

The high energy consumption of data centres (DCs) has recently become a significant problem with the rapid development of DCs worldwide. This work studies the daily energy management of a data centre microgrid (DCM). The energy management problem is formulated as a two-stage stochastic mixed-integer linear programing (MILP) model that accounts for workload schedules, cooling resources, uncertainties of onsite renewable generation, and electricity price. An energy management scheme that co-optimises workloads and waste heat is proposed to minimise the operating cost. Furthermore, the potential for waste heat recovery and reuse is also considered. The simulation results illustrate that the proposed model can reduce the operating cost of DCM by the co-optimisation of workloads and waste heat while meeting the temperature requirements for server clusters.

In modern power systems, the high penetration of renewable energy challenges system frequency regulation and stability. In such conditions, the demand-side loads can be aggregated and applied for power system frequency regulation. In this study, a dual-level distributed control framework is proposed for thermostatically controlled load (TCL) aggregators in multi-area load frequency control. In the higher control level, the leader of TCL aggregators in each control area is controlled by local and neighbouring area control errors. In the lower control level, multiple TCL aggregators are coupled via a leader-follower consensus control protocol to track the power reference from the area leader. As a result, the dual-level distributed controlled TCL aggregators can operate together with synchronous generators for frequency regulation in multi-area power systems. The proposed method is validated in a three-area power system under various cyber-physical conditions, including contingency and normal operation conditions, as well as communication failure and delay conditions.