Electric vehicle optimal scheduling method considering charging piles matching based on edge intelligence

To adress the problems of insufficient consideration of charging pile resource limitations,discrete-time scheduling methods that do not meet the actual demand and insufficient descriptions of peak-shaving response capability in current electric vehicle(EV)opti-mization scheduling,edge intelligence-oriented electric vehicle optimization scheduling and charging station peak-shaving response capability assessment methods are proposed on the basis of the consideration of electric vehicle and charging pile matching.First,an edge-intelligence-oriented electric vehicle regulation frame for charging stations is proposed.Second,continuous time variables are used to represent the available charging periods,establish the charging station controllable EV load model and the future available charging pile mathematical model,and establish the EV and charging pile matching matrix and constraints.Then,with the goal of maximizing the user charging demand and reducing the charging cost,the charging station EV optimal scheduling model is established,and the EV peak response capacity assessment model is further established by considering the EV load shifting constraints under different peak response capacities.Finally,a typical scenario of a real charging station is taken as an example for the analysis of optimal EV scheduling and peak shaving response capacity,and the proposed method is compared with the traditional method to verify the effectiveness and practicality of the proposed method.

An Internet of Energy Things Based on Wireless LPWAN

Under intense environmental pressure, the global energy sector is promoting the integration of renewable energy into interconnected energy systems. The demand-side management （DSM） of energy systems has drawn considerable industrial and academic attention in attempts to form new flexibilities to respond to variations in renewable energy inputs to the system. However, many DSM concepts are still in the experimental demonstration phase. One of the obstacles to DSM usage is that the current information infrastructure was mainly designed for centralized systems, and does not meet DSM requirements. To overcome this barrier, this paper proposes a novel information infrastructure named the lnternet of Energy Things （IoET） in order to make DSM practicable by basing it on the latest wireless communication technology： the low-power wide-area network （LPWAN）. The primary advantage of LPWAN over general packet radio service （GPRS） and area Internet of Things （loT） is its wide-area coverage, which comes with minimum power consumption and maintenance costs. Against this background, this paper briefly reviews the representative LPWAN tech- nologies of narrow-band Internet of Things （NB-IoT） and Long Range （LORa） technology, and compares them with GPRS and area IoT technology. Next, a wireless-to-cloud architecture is proposed for the IoET, based on the main technical features of LPWAN. Finally, this paper looks forward to the potential of IoET in various DSM application scenarios.

A Least-squares-based Iterative Method with Better Convergence for PF/OPF in Integrated Transmission and Distribution Networks

The limitations of the conventional master-slavesplitting(MSS)method,which is commonly applied to power flow and optimal power flow in integrated transmission and distribution(I-T&D)networks,are first analyzed.Considering that the MSS method suffers from a slow convergence rate or even divergence under some circumstances,a least-squares-based iterative(LSI)method is proposed.Compared with the MSS method,the LSI method modifies the iterative variables in each iteration by solving a least-squares problem with the information in previous iterations.A practical implementation and a parameter tuning strategy for the LSI method are discussed.Furthermore,a LSI-PF method is proposed to solve I-T&D power flow and a LSIheterogeneous decomposition(LSI-HGD)method is proposed to solve optimal power flow.Numerical experiments demonstrate that the proposed LSI-PF and LSI-HGD methods can achieve the same accuracy as the benchmark methods.Meanwhile,these LSI methods,with appropriate settings,significantly enhance the convergence and efficiency of conventional methods.Also,in some cases,where conventional methods diverge,these LSI methods can still converge.

An integrated multi-energy flow calculation method for electricity-gas-thermal integrated energy systems

The modeling and multi-energy flow calculation of an integrated energy system (IES) are the bases of its operation and planning. This paper establishes the models of various energy sub-systems and the coupling equipment for an electricity-gas-thermal IES, and an integrated multi-energy flow calculation model of the IES is constructed. A simplified calculation method for the compressor model in a natural gas network, one which is not included in a loop and works in constant compression ratio mode, is also proposed based on the concept of model reduction. In addition, a numerical conversion method for dealing with the conflict between nominal value and per unit value in the multi-energy flow calculation of IES is described. A case study is given to verify the correctness and speed of the proposed method, and the electricity-gas-thermal coupling interaction characteristics among sub-systems are studied.

Operational Risk Assessment for Integrated Transmission and Distribution Networks

To satisfy the requirements of accurate operationalrisk assessment of integrated transmission and distribution networks (I-T&D), an integrated operational risk assessment (IORA) algorithm is proposed. Specific cases demonstrate thatan I-ORA is necessary because it provides accurate handlingof the coupling between transmission and distribution networks,accurate analysis of power supply mode (PSM) changes ofimportant users and helps to improve security and stability ofpower grid operations. Two key technical requirements in theI-ORA algorithm are realized, i.e., integrated topology analysisand integrated power flow calculation. Under a certain contingency, integrated topology analysis is used to assess the risksof substation power cuts, network split and PSM changes ofimportant users, while the integrated power flow calculation,based on the self-adaptive Levenburg-Marquard method andNewton method, can be implemented to assess risks of heavyload/overload and voltage deviation. In addition, the graphicsprocessing unit is used to parallelly process some computationintensive steps. Numerical experiments show that the proposedI-ORA algorithm can realize accurate assessment for the entireI-T&D. In addition, the efficiency and convergence are satisfying,indicating the proposed I-ORA algorithm can significantly benefitreal practice in the coordination operation of I-T&D in the future.

Fully Distributed Risk-based Robust Reserve Scheduling for Bulk Hybrid AC-DC Systems

To enhance the cost-effectiveness of bulk hybrid AC-DC power systems and promote wind consumption,this paper proposes a two-stage risk-based robust reserve scheduling(RRRS)model.Different from traditional robust optimization,the proposed model applies an adjustable uncertainty set rather than a fixed one.Thereby,the operational risk is optimized together with the dispatch schedules,with a reasonable admissible region of wind power obtained correspondingly.In addition,both the operational base point and adjustment capacity of tielines are optimized in the RRRS model,which enables reserve sharing among the connected areas to handle the significant wind uncertainties.Based on the alternating direction method of multipliers(ADMM),a fully distributed framework is presented to solve the RRRS model in a distributed way.A dynamic penalty factor adjustment strategy(DPA)is also developed and applied to enhance its convergence properties.Since only limited information needs to be exchanged during the solution process,the communication burden is reduced and regional information is protected.Case studies on the 2-area 12-bus system and 3-area 354-bus system illustrate the effectiveness of the proposed model and approach.

Optimal Home Energy Management System with Mixed Types of Loads

This paper presents a novel home area energy management system(HEMS)for smart homes with different load profiles installed with photovoltaic generation,energy storage,and DC demand.The developed HEMS is shown to optimize the utilization of local renewables while minimizing energy waste between AC and DC conversions and between storage charging and discharging.Previous studies on HEMS have not considered the impact of load types.In this study,the performance of the proposed HEMS is demonstrated on different smart homes with and without electric heating.A comparative study is carried out to investigate battery behavior,characteristics of AC and DC conversion,and benefits that customers receive.A sensitivity analysis is also conducted to discuss the effects from varied energy storage capacities,AC/DC conversion efficiencies,and PV output.The results show that cost reduction in energy bills can be greatly impacted by load profiles,and customers with electric heating load coupled with sufficiently large energy storage would receive the most reduction in their energy bills.