IET Energy Systems Integration最新文献

The offshore integrated energy system plays important role in the offshore oil and gas processing industry. To ensure the safe development of offshore oil and gas resources, accurately assessing their risks is crucial. First, this article describes the risk factors that affect the operation of the equipment and builds a risk model that takes into account the relevance of the coupled system; then, a risk transfer model based on material–energy analysis is proposed, which describes the transfer of risk through material–energy flow. In addition, according to the structure and operating characteristics of the offshore integrated energy system, a risk indicator system has been designed from five levels: operational risk, energy supply risk, structural risk, economic risk and environmental risk. Finally, by taking the simulation experiment of an offshore oil and gas platform, the proposed model in this paper evaluates the risks of offshore oil and gas platforms accurately.

This paper deals with a tripartite control based on LCL-filter for a single-stage solar photovoltaic (PV) interconnected three-phase grid-tied system. This work proposes a novel tripartite control for LCL-filter based on sensing capacitor side voltage utilising two sensors. Conventionally, the control algorithm requires six sensors for sensing the inverter-side inductor current, capacitor side voltage, and grid-side inductor current. However, in this work, to execute the tripartite control algorithm, the only voltage across the filter capacitor need to be sensed. The voltage across the filter capacitor estimates inverter-side inductor current and grid-side inductor current. The proposed algorithm offers the advantage/benefit in reducing size, weight, and implemented cost. As an outcome, the reduction in the complexity of the hardware takes place. The implemented system is analysed for parametric variation to ensure the stability and robustness of the system. The system response is observed under digital control delay variation. The proposed method offers a cost-effective solution for meeting grid regulation. The implemented system is extensively tested and validated by simulation in the MATLAB/Simulink platform. The justification of the system is carried out by experimental results obtained from the prototype designed in the laboratory.

In this paper, an efficient and robust power and energy management for large clusters of plug-in electric vehicles (PEVs) and distribution networks is proposed. The method aims to minimise the charging cost of large clusters of PEVs in real time while ensuring distribution network normal operation and satisfying a large number of constraints from PEV level up to distribution network. The design of the method ensures very low dependence on forecast errors of critical quantities such as electricity price while it can be easily integrated with conventional optimal power flow algorithms. To this end, innovative virtual differential operation costs are assigned to clusters of PEVs. Moreover, an innovative definition of the flexibility of a cluster of PEVs to change its power is introduced while a simple idea based on the principle of the selection of the fittest is used to achieve efficient power dispatch to the PEVs with minimal computational requirements. The efficiency and the robustness of the proposed method are proved by detailed simulations of several operation scenarios of a realistic distribution network with large penetration of PEVs and renewable energy sources.

With the development of digitalisation and intelligence, the power system has been upgraded from the traditional single energy transmission and conversion system to a complex cyber-physical power system (CPPS) with tightly coupled energy and information flows. The cyber-physical power system achieves the controllability and observability of the power system through ubiquitous sensing technology, advanced measurement technology, and powerful information processing technology. However, the large number of intelligent electronic device accesses and frequent information interactions in CPPS make it more vulnerable and susceptible to be attacked than any previous single structured system. Viruses and intrusions can attack the CPPS through the cyber subsystem, which in turn can deal a fatal blow to the energy supply physical system. Because of the above problems, malicious attacks against CPPS have been occurring in recent years and have generated a great deal of scholarly attention. This paper precisely focusses on this problem, by profiling the structure of CPPS and the potential threats, conducting an in-depth analysis of CPPS attack modes from the cyber and physical subsystems, and summarising the three-level security defence methods for CPPS in detail. Finally, the future technological development prospects of CPPS security research are explicitly addressed, which will provide technical support for building reliable, safe, and robust energy systems.

Natural disasters and cyber intrusions threaten the normal operation of the critical Multi-Energy Systems (MESs) infrastructures. There is still no universally-accepted definition of MESs resilience under the integration of cyber and physical, and lack of a widely accepted methodology to quantify and assess the resilience in MESs. Hence, this paper introduces an extensive review of the state-of-the-art research of power systems’ resilience. Then, this work proposes the definition of the Multi-Energy Cyber-Physical Systems (MECPSs) resilience and its related characteristics. To improve the resilience of MECPSs, this paper investigates extreme natural disaster models and analyses the vulnerability of the system to find the key constraint factors. Furthermore, this work presents the qualitative assessment curve, quantitative indexes, and assessment framework of the MECPSs resilience. Finally, the key improvement measures for the planning and operation of MECPSs resilience and the focus of future research are presented.

We-Energy (WE), as an important energy unit with full duplex and multi-energy carriers in the integrated energy system, uses the coupling matrix to connect the network-side and demand-side energy. However, the coupling matrix of WE is very hard to be formulated directly due to the complicated internal structure and the flexibility of operation mode. This paper proposes a multi-step method for the modelling of WE. According to the method, the conversion process in the WE can be separated into several steps and the WE model can be built by the coupling matrix in each step. Then, the WE model is extended by considering the renewable energy, location of storage and different types of demand response. Because of the non-linearity caused by the dispatch factors, the computational complexity increases greatly for solving the optimal scheduling issue of the WE. In order to reduce the computational burden, the variable substitution is added in the proposed modelling method. The results of simulation cases are presented to demonstrate the performance of the proposed modelling and calculation method.

A concern regarding the deterioration in power quality (PQ) has escalated with the high level of integration of renewable energy sources to the utility, primarily in the scenario of a weak distribution grid. This paper presents a modified complex variable filter (MCVF)-based control to enhance the power quality performance of wind–solar photovoltaic (PV) and battery-based microgrid under the weak grid and dynamic load conditions. An MCVF attenuates the harmonics and DC bias infected voltage and current and extracts the fundamental components from distorted current and voltage. The control scheme for the voltage source converter (VSC) is presented to meet the active power demand of load/grid and attenuates harmonics to control the power quality issues at the point of common coupling. To achieve the round, the clock operation of the microgrid, a battery is interfaced to support the local loads under off-grid mode. Therefore, the presented VSC controller supplies the continuous power to the local loads and maintains the total harmonic distortion value of grid current within the PQ Standard IEEE-519-2014. The simulated and test results are presented to validate the VSC controller in different operating conditions.

The photovoltaic (PV) power generation and cooling demand of the air conditioner are increased along with an increase in solar irradiation. Therefore, considering such fact, in this paper, PV power is integrated with the air conditioner to support the grid. With recent developments in power electronics, the air conditioning systems are operated in variable speed using variable frequency drive (VFD) technology. In this paper, taking the advantage of the VFD technology, PV power is directly injected into the DC bus of VFD using an isolated DC-DC converter. In this methodology, due to the high-frequency DC-DC conversion, high power DC-AC (50 Hz) stage is eliminated, and seamless power is transferred from PV generation to the load without interrupting the main operation of the air conditioner. Thus, the reliability of the system is enhanced with the reduction in overall cost, conversion losses and bulkiness. With the PV power support, the peak amplitude of the grid current is reduced and consequently the power consumption, reactive power intake from the grid, as well as the harmonics component of the grid current, are reduced. This scheme is used in rural or suburban areas where the solar profile is significant and air conditioner is extensively used.

Demand response can reshape the load profiles by adjusting the energy price to improve overall performance of power grids. For the load serving entities (LSEs), the optimal demand response shall satisfy operation constraints and gain maximised profits. However, the individual end-consumer will surely value electricity differently, and price adjustments without considering the differences of user behaviours may induce unbalanced dispatch and degrade the overall profits. Given affordable price ranges under which the non-critical loads can properly response to price signals, the demand response can be operated in a manner where non-critical loads at different areas coordinately adjusted to achieve the global dispatch objectives. For this purposes, this paper proposes a cooperative demand response approach for LSE pricing based on a multi-agent deep reinforcement learning approach. The learning approach constructs the distributed pricing agents that cooperatively determine the price signals to be responded by different load clusters. To update the parameters of pricing agents, the deep deterministic policy gradient is derived considering the constraints and different behaviours of load clusters. The effectiveness of the proposed cooperative demand response method is verified based on numerical simulations.

With frequent occurrences of extreme natural disasters such as typhoons in urban integrated energy systems (UIES), it is of great significance to cope with different kinds of disturbances. This paper proposes a load restoration method under typhoon weather for urban distribution and natural gas networks based on soft open points (SOP). Firstly, the typhoon wind speed model is introduced and the line fault rates of distribution networks under typhoons are calculated. Secondly, the gas turbine and electric-driven compressor are considered as the coupling units of the integrated electric–gas energy system, and related models are constructed. The fault analysis method of the natural gas network is proposed considering the faults in the distribution network lead by typhoons. Thirdly, SOP installed in the distribution network with the V/f control mode is applied to restore electrical loads and provide voltage support for the loads on the fault side. After that, the loads of the gas network could also be restored because of the restoration of the coupling units. Optimal energy flow is applied to determine the output of the power and gas sources, coupling units and also the loads to be restored. Finally, the fault rate of each line under typhoon disaster is analysed and the correctness and effectiveness of the resilience improving method based on SOP are verified with test systems UIES E33-G14 and UIES E123-G48.