A smart charging algorithm for integration of EVs in providing primary reserve as manageable demand-side resources

Summary Residential loads represent one of the most important types of existing loads, which represent 54.9% of the total electricity consumption in the Egyptian network. Traditional Egyptian distribution systems are not capable of handling the extra loading over the existing lines. These systems already suffer from many obstacles, which result in increasing service outage rate that would badly decrease distribution system efficiency, reliability, quality, and security. The load demand management can be considered one of the promising solution methods for peak load shaving as well as enhancing system performance and reliability. In this paper, a complete discussion and analysis of different types of Egyptian residential loads including its daily operation performance and time shifting operation capability have been introduced. Then, a generalized formula of the load management problem has been formulated including all objectives that need to be achieved as well as their respective constraints. A new smart load management technique has been proposed to solve this problem. The proposed technique represents the programming part necessary for the load management control centers. The proposed technique accepts the consumers' preferred operation times as input data, which ensure maximum consumers' satisfaction. Applying the proposed solution technique on a real overloaded Egyptian distribution network, the obtained results confirm the efficiency and effectiveness of the introduced methodology to relieve the overloading problem, enhance network performance, and meet the consumers' requirements.

Section: Proposed Load Management Solution Techniquementioning

confidence: 99%

Section: Egyptian Residential Load Profile and The Test System Topomentioning

confidence: 99%

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Smart residential load management technique for distribution systems' performance enhancement and consumers' satisfaction achievement

Elsayed

Hegab

Farrag

2019

“…1,2 According to statistics from the intergovernmental Organization for Economic Co-operation and Development (OECD), 40% of global carbon dioxide emissions come from power systems, and 24% come from internal combustion engine vehicles. 5 Because wind and photovoltaic (PV) energy sources exhibit strong randomness, the output power of an individual wind or PV power generation system is very unstable and cannot be controlled in accordance with typical requirements. 3,4 Therefore, it is important to popularize the application of EVs in place of traditional fuel vehicles.…”

Section: Introductionmentioning

confidence: 99%

Multitime scale coordinated scheduling for electric vehicles considering photovoltaic/wind/battery generation in microgrid

Liu

Song

Mao

et al. 2019

Summary The problem of multitime scale coordinated scheduling for electric vehicles (EVs) with vehicle‐to‐grid (V2G) technology is formulated for a microgrid with photovoltaic/wind/battery generation. The life of the energy storage system in the microgrid, and the benefits for EV users are considered as the optimization goals. Reasonable measures of the charging and discharging behaviors of EVs are considered to construct the objective functions. A stratified sequencing method is designed to transform the multiobjective optimization problem into a single‐objective nonlinear optimization problem that can be solved through adaptive particle swarm optimization (APSO). Then an optimal multitime scale coordinated scheduling scheme can be obtained. The effectiveness and feasibility of the methods are verified by simulation results.

“…In order to meet the objective of climate‐neutrality in world of electrical energy, integration of low‐emission electric vehicles (EVs) and renewable energy sources (RESs) in the distribution system has increased in the last few decades. The increased penetration of EVs may affect the distribution system parameters such as voltage deviation, quality of supply, power losses and transformers aging . EVs may also supports distribution system as ancillary services such as phase balancing, peak power shaving, spinning reserve, voltage and frequency regulations .…”

Section: Introductionmentioning

confidence: 99%

A modified current injection load flow method under different load model of EV for distribution system

Jha

Kumar

Dheer

et al. 2019

Summary In this article, a modified single‐phase current injection based load flow method for the distribution network with different load models of electric vehicle (EV) is proposed. The equations related to injected currents are non‐linear and are represented in rectangular co‐ordinates. The PQ and PV bus representations in load flow formulation are modified for the three different load models of EV including polynomial or ZIP load model (EV LM‐I), voltage dependent load model (EV LM‐II) and constant current load model (EV LM‐III). In addition, a stochastic modelling of EV load and selection of candidate locations for DGs integration are also presented. The effect of the proposed EV load models in terms of real power loss index (ILP), reactive power loss index (ILQ), voltage profile index (IV D) and the MVA capacity index (IC) has been studied on IEEE 38‐bus distribution system. Based on the values of ILP, ILQ, IV D and IC, best load model for EVs from among the load models EV LM‐I, EV LM‐II and EV LM‐III is finally obtained.