IET Energy Systems Integration最新文献

Smart local energy systems (SLES) have been reported in the past decade, which are associated with diverse energy carriers, components and objectives. This paper provides a comprehensive review of information and communications technology (ICT) infrastructure of SLES. A systematic survey of existing research work and industrial projects was provided to highlight, categorise and analyse the ICT infrastructure, which lays the foundation for the successful functioning of SLES. First of all, various SLES measurements are described and categorised based on the energy carriers and technologies. Then, communications infrastructure for SLES is described with communications technologies summarised. Moreover, the ICT infrastructures for SLES are categorised and summarised based on their objectives and technologies. Finally, the challenges and recommendations are presented. The findings from this paper are intended to serve as a convenient reference for developing future SLES.

This paper presents the potential of building a local electricity market (LEM) to boost the deployment of the local energy communities, centred around active customers with distributed energy resources (DERs). To conduct a comprehensive and detailed study on different cases with reduced computational burdens, this paper adopts a simplified modelling approach where the market and network model simulations are performed in a cascaded, decoupled fashion. This allows achieving the optimal LEM output for the energy community with different DER assets that are not bounded by the network constraints. The investigation involves quantifying the benefits brought by LEM to energy communities by tapping the flexibility associated with trading inside the energy community. Moreover, it presents the influence of different types of DERs (mainly photovoltaics (PV) and energy storage (ES)) in customers' premises on the outcome of the LEM. The LEM demonstrates successfully the reduction of cost associated with the energy purchased from the energy retailer and maximises the consumption of locally generated clean electricity. Among the studied DER portfolios, the combination of PV and ES solution shows the highest economic potential but deteriorates the voltage profiles and shows high active power loss in the winter month among all the cases examined.

The development of accurate dynamic models of thermal energy storage (TES) units is important for their effective operation within cooling systems. This paper presents a one-dimensional discretised dynamic model of an ice-based TES tank. Simplicity and portability are key attributes of the presented model as they enable its implementation in any programing language which would, in turn, facilitate the simulation and analysis of complex cooling systems. The model considers three main components: energy balance, definition of the specific heat curve, and calculation of the overall heat transfer coefficient. An advantage of the model is that it can be adapted to other types of TES units employing phase change materials. The modelling approach assumes equal flow and temperature distribution in the tank and considers two internal tubes only to represent the whole tank—significantly reducing the number of equations required and thus the computation time. Thermophysical properties of water during the phase change and of the heat transfer fluid are captured. The ice-based TES tank model has been implemented in MATLAB/Simulink. A good agreement between simulation results and experimental data available in the literature has been achieved—providing confidence in the validity of the mathematical model.

Power supply reliability (PSR) is a critical factor in the optimal configuration of stand-alone microgrids. Considering the impact of the failure outage of power generation and energy storage equipment, as well as the uncertainty of renewable energy on PSR, a multi-objective bi-level mixed-integer optimisation model is proposed. Based on Benders decomposition, the model is decoupled into a master problem (MP) of the equipment optimal configuration considering economy and environmental conservation and a sub-problem (SP) of the PSR check. Considering the load importance hierarchy, two types of slack variables are introduced into the SP to ensure both the reliable power supply of important loads and the PSR of the system. Through interactive iteration of the MP and SP, the complexity of the optimisation model is considerably reduced, improving the solution efficiency while ensuring the rationality of the optimal configuration scheme. Finally, the effectiveness of the proposed model is verified by a typical stand-alone wind–photovoltaic–diesel–battery microgrid system and analysed in terms of the impact of reliability requirement and energy storage on the configuration scheme and algorithm convergence.

The solar photovoltaic (PV)-based microgrid is one of the most ideal renewable energy resources. This paper presents a utility grid intertie multi-PV-inverter-based microgrid (MG) control for the solar rooftop application. The main and ancillary voltage source converters (VSCs) DC links are assimilated with PV arrays of independent maximum power point tracking (MPPT) algorithms for the economical and efficacious single-stage configuration. At the point of common coupling (PCC), parallel VSCs arrangement increases the MG's power rating with distinctive local loads. In normal circumstances, the current control methodology is employed by the main VSC under the grid-interactive mode. Conversely, in some grid contingency conditions under the isolated mode, its control transfers to the voltage control, which regulates the frequency and the voltage at PCC and acts like a grid-forming inverter. The ancillary VSC operation is implemented with the current control algorithm. The main VSC supplies the active power towards the grid and accomplishes the load requirement, whereas the ancillary VSC retains its load demand in a grid-interactive mode and also regulates the load requirement in an islanded mode of operation. The utilization of feed-forward components for PV arrays powers in the VSCs current control techniques improves the MG dynamic performance. The seamless mode transfer performance of the main VSC is implemented via a power electronics switch. The MATLAB software is used to model a microgrid and its performance is analysed via RT-LAB in real time through the OPAL-RT (OP4510) controller for various scenarios, that is, varying solar insolation, load alterations and unbalanced non-linear loads. The utilization of the modified Kwong's algorithm-based current control enhances the power quality such as harmonics current elimination and improvement in the power factor. The voltage profile of PCC voltages is enhanced via using a modified Kwong's algorithm-based filter in the voltage controller. The modified Kwong's algorithm has fast convergence, reduces misadjustments and gives very good performance compared to the least-mean-square (LMS) and Kwong's approaches. The total harmonic distortion (THD) of grid currents and PCC voltages THD in an isolated mode is found according to the limits of the IEEE-519 standard.

This work presents a Lyapunov-based control of a grid side converter of distributed energy systems. The analysis focuses on the constraints imposed by unbalanced operation and thermal limits. On one side, the proposal, which considers symmetrical components, allows controlling the converter in such a way that it is able to deliver constant real power to the grid in the presence of highly unbalanced voltages. On the other side, to solve the operation under thermal constraints, the references in control loops are adapted. Both issues, unbalanced operation but also thermal constraints, are considered in a sole Lyapunov function, formed by the union of a set of Lyapunov ones. This ensures the stability of the whole system by using simple PI controllers. Finally, different scenarios, strong disturbances and reaching current limits are explored in simulation results.

Mobility as a Service (MaaS) represents a paradigm shift from personally owned transportation modes towards mobility provided as a service. Using electric vehicles (EVs) as a mobile energy storage media, this article presents a new application scenario of MaaS in urban energy systems, referring to as the mobile energy to home (ME2H) integration. An architectural design of the ME2H system is proposed in this study, which is cantered by a ridesharing-like booking system. Through the booking system, a customer can appoint nearby on-road EVs to come to plug in and temporarily supply energy to their site with an agreed price lower than purchasing energy from the external grid. The ME2H booking system then interfaces with the customer-side home energy management system and the EV driver-side trip planner. Based on the ME2H booking schedules, the two decision-making systems plan the household appliance operations and travel paths for the ME2H service receiver (the customer) and provider (the EV driver), respectively. This study also investigates two representative scenarios to demonstrate the effectiveness of ME2H in urban energy systems.

It is recognized by academia and industry that second-life batteries retired from electric vehicles still have use values and can be effectively used for supporting less demanding applications. At present, there lacks investigation on the applications of re-using retired batteries on serving residential sector's energy management. Motivated by this, this paper studies the scenario of assembling retired batteries to be second-life battery energy storage systems (SL-BESSs) and using them to serve the energy demand of residential communities in an affordable manner. Based on an established SL-BESS model, a two-level community energy management framework is proposed, which optimizes the schedules of a SL-BESS and other energy resources in a community subjected to a variety of short-term operational objectives. In the upper level, a many-objective optimization model is formulated, which comprehensively integrates four objectives covering the community's multi-scale operational considerations. A NSGA-III-based solving approach is developed to find the non-dominated solutions of the model. In the lower level, the optimal community scale load reshaping decisions and energy costs obtained from the upper level are allocated to individual houses. Extensive numerical case studies are conducted, and the results show that the proposed system can realize better trade-off among the different operational considerations with less computational cost.

Modern distribution networks have an urgent need to increase the accommodation level of renewable energies facilitated by configuring battery energy storage systems (BESSs). In view of the contradictions of BESS capacity, cost, life, and operation environment, an optimal capacity allocation algorithm of BESS in modern distribution networks considering the ambient temperature has been proposed from the perspective of the life cycle cost-benefit optimisation. First, a refined BESS model under the influence of the ambient temperature has been established to accurately track life degradation and charging-discharging efficiencies. Subsequently, an electric vehicle (EV) charging load forecasting model that considers the influence of travel characteristics, traffic congestion and environmental factors has been established. Finally, a bi-level BESS optimisation algorithm has been proposed to maximise the system benefits on the EV charging station side and the grid side, and the marginal ageing cost has been considered while optimising the charging and discharging strategies of BESS, to achieve the best cost-benefit of BESS throughout the life cycle. The simulation results verify the effectiveness and economy of the proposed configuration schemes and operation strategies under different seasons.

With the continuous development of Regional Integrated Energy System (RIES), demand response (DR) is composed of diversified loads including electric load, heat load and gas load. Their cross-dependencies reflecting the nonlinear coupling complementary relationship between each load type are one of the key factors to improve multi-energy flow optimisation modelling and utilisation efficiency on the demand side. Accordingly, this paper proposes a DR dependency assessment method considering electricity-heat-gas loads based on the BOXCOX-Pair Copula model. BOXCOX transformation is introduced to convert various probability distribution statistics of electricity-heat-gas loads into Gaussian distributed variables. C-vine Pair Copula is used to characterise an ensemble-of-trees of high-dimensional dependency structure among multi-energy demand modalities. Then the combined model of BOXCOX transformation and C-vine Pair Copula can be employed to determine the complex coupling dependency among electricity-heat-gas loads according to different DR statistics. Some metrics between the original empirical distribution and BOXCOX-Pair Copula distribution are introduced to assess the dependency evaluation precision of the proposed model. Finally, the novel dependency assessment model is numerically tested utilising the electricity load, heat load and gas load data sequences in a real RIES. The results illustrate that the cross-dependency of electricity-heat-gas integrated DR based on the BOXCOX-C-vine copula model is closer to that of actual sample data, which verify the effectiveness and superiority of the proposed approach.