Records with Subject: Planning & Scheduling
Showing records 1 to 25 of 42. [First] Page: 1 2 Last
Rolling Horizon Model for Gasoline Blend Planning under Uncertainty in Demands
mahir jalanko, Vladimir Mahalec
October 30, 2018 (v1)
Keywords: production planning under uncertainty, supply-demand pinch
Use rolling horizon model to solve the gasoline blend planning under uncertainty in products demands. We show that an aggregated model based on supply-demand pinch points can improve executions times greatly
Correction: Jiménez, F., et al. System for Road Vehicle Energy Optimization Using Real Time Road and Traffic Information. Energies 2014, 7, 3576-3598
Felipe Jiménez, Wilmar Cabrera-Montiel, Santiago Tapia-Fernández
October 23, 2018 (v1)
In the original version of the article [1], insufficient acknowledgement was given for the original Dynamic Programming optimization tool. We apologize for this error. To correct this fact, Santiago Tapia-Fernández has been added as an author, and the acknowledgements and authors contributions have been corrected.
Optimal Bidding Strategy for Renewable Microgrid with Active Network Management
Seung Wan Kim, Jip Kim, Young Gyu Jin, Yong Tae Yoon
October 23, 2018 (v1)
Keywords: active network management, market participation of microgrid, microgrid operation, renewable microgrid
Active Network Management (ANM) enables a microgrid to optimally dispatch the active/reactive power of its Renewable Distributed Generation (RDG) and Battery Energy Storage System (BESS) units in real time. Thus, a microgrid with high penetration of RDGs can handle their uncertainties and variabilities to achieve the stable operation using ANM. However, the actual power flow in the line connecting the main grid and microgrid may deviate significantly from the day-ahead bids if the bids are determined without consideration of the real-time adjustment through ANM, which will lead to a substantial imbalance cost. Therefore, this study proposes a formulation for obtaining an optimal bidding which reflects the change of power flow in the connecting line by real-time adjustment using ANM. The proposed formulation maximizes the expected profit of the microgrid considering various network and physical constraints. The effectiveness of the proposed bidding strategy is verified through the simul... [more]
Matching of Energy Provisions in Multihop Wireless Infra-Structures
Rui Teng, Huan-Bang Li, Ryu Miura, Tatsuya Yamazaki, Peter Davis
October 23, 2018 (v1)
Keywords: energy provision, green energy, matching, network sustainability, wireless multihop infrastructures
Recently there have been large advances in energy technologies for battery-operated systems, including green energy resources and high capacity batteries. The effective use of battery energy resources in wireless infrastructure networks to improve the versatility and reliability of wireless communications is an important issue. Emerging applications of smart cities, Internet of Things (IoT), and emergency responses highly rely on the basic communication network infrastructures that enable ubiquitous network connections. However, energy consumption by nodes in a wireless infrastructure network depends on the transmissions of other nodes in the network. Considering this inter-dependence is necessary to achieve efficient provision of energy in wireless networks. This paper studies the issue of energy provision for wireless relay nodes in Wireless Multihop Infrastructures (WMI) assuming constraints on the total energy provision. We introduce a scheme of Energy Provision Matching (Matching-... [more]
Assessing the Potential of Plug-in Electric Vehicles in Active Distribution Networks
Reza Ahmadi Kordkheili, Seyyed Ali Pourmousavi, Mehdi Savaghebi, Josep M. Guerrero, Mohammad Hashem Nehrir
October 23, 2018 (v1)
Keywords: Optimization, photovoltaic (PV) panels, plug-in electric vehicle (PEV), state of charge (SoC), vehicle to grid (V2G)
A multi-objective optimization algorithm is proposed in this paper to increase the penetration level of renewable energy sources (RESs) in distribution networks by intelligent management of plug-in electric vehicle (PEV) storage. The proposed algorithm is defined to manage the reverse power flow (PF) from the distribution network to the upstream electrical system. Furthermore, a charging algorithm is proposed within the proposed optimization in order to assure PEV owner’s quality of service (QoS). The method uses genetic algorithm (GA) to increase photovoltaic (PV) penetration without jeopardizing PEV owners’ (QoS) and grid operating limits, such as voltage level of the grid buses. The method is applied to a part of the Danish low voltage (LV) grid to evaluate its effectiveness and capabilities. Different scenarios have been defined and tested using the proposed method. Simulation results demonstrate the capability of the algorithm in increasing solar power penetration in the grid up t... [more]
A Simple Operating Strategy of Small-Scale Battery Energy Storages for Energy Arbitrage under Dynamic Pricing Tariffs
Enrico Telaretti, Mariano Ippolito, Luigi Dusonchet
October 22, 2018 (v1)
Keywords: battery energy storage system, energy management, hourly electricity prices, optimal operation, price arbitrage
Price arbitrage involves taking advantage of an electricity price difference, storing electricity during low-prices times, and selling it back to the grid during high-prices periods. This strategy can be exploited by customers in presence of dynamic pricing schemes, such as hourly electricity prices, where the customer electricity cost may vary at any hour of day, and power consumption can be managed in a more flexible and economical manner, taking advantage of the price differential. Instead of modifying their energy consumption, customers can install storage systems to reduce their electricity bill, shifting the energy consumption from on-peak to off-peak hours. This paper develops a detailed storage model linking together technical, economic and electricity market parameters. The proposed operating strategy aims to maximize the profit of the storage owner (electricity customer) under simplifying assumptions, by determining the optimal charge/discharge schedule. The model can be appl... [more]
Heuristic Optimization of Consumer Electricity Costs Using a Generic Cost Model
Chris Ogwumike, Michael Short, Fathi Abugchem
October 22, 2018 (v1)
Keywords: decision support system, demand side management, heuristic algorithm, load scheduling, smart grid
Many new demand response strategies are emerging for energy management in smart grids. Real-Time Energy Pricing (RTP) is one important aspect of consumer Demand Side Management (DSM), which encourages consumers to participate in load scheduling. This can help reduce peak demand and improve power system efficiency. The use of Intelligent Decision Support Systems (IDSSs) for load scheduling has become necessary in order to enable consumers to respond to the changing economic value of energy across different hours of the day. The type of scheduling problem encountered by a consumer IDSS is typically NP-hard, which warrants the search for good heuristics with efficient computational performance and ease of implementation. This paper presents an extensive evaluation of a heuristic scheduling algorithm for use in a consumer IDSS. A generic cost model for hourly pricing is utilized, which can be configured for traditional on/off peak pricing, RTP, Time of Use Pricing (TOUP), Two-Tier Pricing... [more]
Energy Management Strategy for Microgrids by Using Enhanced Bee Colony Optimization
Whei-Min Lin, Chia-Sheng Tu, Ming-Tang Tsai
October 22, 2018 (v1)
Keywords: bee colony optimization, microgrid, Renewable and Sustainable Energy, time-of-use
This paper presents a microgrid (MG) energy management strategy by considering renewable energy and battery storage systems. Renewable energy, including wind power generation and solar power generation, is integrated into the distribution network, for which is formulated the optimal dispatch model of mixed-power generation by considering the charging/discharging scheduling of battery storage systems. The MG system has an electrical link for power exchange between the MG and the utility during different hours of the day. Based on the time-of-use (TOU) and all technical constraints, an enhanced bee colony optimization (EBCO) is proposed to solve the daily economic dispatch of MG systems. In the EBCO procedure, the self-adaption repulsion factor is embedded in the bee swarm of the BCO in order to improve the behavior patterns of each bee swarm and increase its search efficiency and accuracy in high dimensions. Different modifications in moving patterns of EBCO are proposed to search the f... [more]
Research on a Plug-In Hybrid Electric Bus Energy Management Strategy Considering Drivability
Ye Yang, Youtong Zhang, Jingyi Tian, Si Zhang
September 21, 2018 (v1)
Keywords: drivability, dynamic programming, fuel economy, linear weight particle swarm optimization, plug-in hybrid electric bus
Plug-in hybrid electric buses (PHEBs) is some of the most promising products to address air pollution and the energy crisis. Considering the switching between different working modes often bring about sudden changes of the torque and the speed of different power sources, which may lead to the instability of the power output and affect the driving performance and ride comfort, it is of great significance to develop a real-time optimal energy management strategy for PHEBs to achieve the optimization of fuel economy and drivability. In this study, the proposed strategy includes an offline part and an online part. In the offline part, firstly, the energy conversion coefficient s(t) is optimized by linear weight particle swarm optimization algorithm (LinWPSO), then, the optimization results of s(t) are converted into a 2-dimensional look-up table. Secondly, combined with three typical driving cycle conditions, the gear-shifting correction and mode switching boundary parameters that affect t... [more]
The Effects of Dynamic Pricing of Electric Power on Consumer Behavior: A Propensity Score Analysis for Empirical Study on Nushima Island, Japan
Thanh Tam Ho, Sarana Shinkuma, Koji Shimada
September 21, 2018 (v1)
Keywords: demand response, dynamic pricing, local linear matching, propensity score analysis
This study aimed to investigate the change of consumer behavior in electric power consumption after the application of dynamic pricing via real-time feedback. Afield experiment of dynamic pricing was carried out on Nushima Island, which is located in Hyogo Prefecture in central Japan. The panel data of hourly electric power consumption among 50 households (including 22 control households and 28 treated households) were collected from a baseline survey (14 days before the dynamic pricing experiment was conducted) and during the 14-day experimental period. Propensity score analysis with local linear matching was employed to analyze the average treatment effects of dynamic pricing on consumer behavior. The results report that dynamic pricing plays a crucial role in reducing consumers’ electric power consumption—by 9.6% compared to the pre-experimental period.
An Overview of Energy Scenarios, Storage Systems and the Infrastructure for Vehicle-to-Grid Technology
Tohid Harighi, Ramazan Bayindir, Sanjeevikumar Padmanaban, Lucian Mihet-Popa, Eklas Hossain
September 21, 2018 (v1)
Keywords: Batteries, electric vehicles, grid-to-vehicle, harmonic distortion, IEEE Bus standards, vehicle-to-grid
The increase in the emission of greenhouse gases (GHG) is one of the most important problems in the world. Decreasing GHG emissions will be a big challenge in the future. The transportation sector uses a significant part of petroleum production in the world, and this leads to an increase in the emission of GHG. The result of this issue is that the population of the world befouls the environment by the transportation system automatically. Electric Vehicles (EV) have the potential to solve a big part of GHG emission and energy efficiency issues such as the stability and reliability of energy. Therefore, the EV and grid relation is limited to the Vehicle-to-Grid (V2G) or Grid-to-Vehicle (G2V) function. Consequently, the grid has temporary energy storage in EVs’ batteries and electricity in exchange for fossil energy in vehicles. The energy actors and their research teams have determined some targets for 2050; hence, they hope to decrease the world temperature by 6 °C, or at least by 2 °C... [more]
Optimal Energy Management within a Microgrid: A Comparative Study
Luis Orlando Polanco Vasquez, Cristian Andrés Carreño Meneses, Alejandro Pizano Martínez, Juana López Redondo, Manuel Pérez García, José Domingo Álvarez Hervás
September 21, 2018 (v1)
Keywords: distributed power system, energy management, microgrid, optimal power flow
In this work, we focus on optimal energy management within the context of the tertiary control of a microgrid operating in grid-connected mode. Specifically, the optimal energy management problem is solved in a unified way by using the optimal power flow (OPF) and day-ahead concepts. The elements considered in the microgrid are a photovoltaic panel, a wind turbine, electric vehicles, a storage system, and a point of common coupling with the main grid. The aim of this paper consists of optimizing the economic energy dispatch within the microgrid considering known predictions of electricity demand, solar radiation, and wind speed for a given period of time. The OPF is solved using three different algorithms provided by the optimization toolbox of MATLAB® (R2015a, MathWorks®, Natick, MA, USA): the interior point method (IP), a hybrid genetic algorithm with interior point (GA-IP), and a hybrid direct search with interior point (patternsearch-IP). The efficiency and effectiveness of the alg... [more]
Internet of Energy Approach for Sustainable Use of Electric Vehicles as Energy Storage of Prosumer Buildings
Evgeny Nefedov, Seppo Sierla, Valeriy Vyatkin
September 21, 2018 (v1)
Keywords: distributed energy storage, electric vehicles, internet of energy, photovoltaic generation, prosumer, Simulation, smartgrid, vehicle-to-building, vehicle-to-grid
Vehicle-to-building (V2B) technology permits bypassing the power grid in order to supply power to a building from electric vehicle (EV) batteries in the parking lot. This paper investigates the hypothesis stating that the increasing number of EVs on our roads can be also beneficial for making buildings sustainably greener on account of using V2B technology in conjunction with local photovoltaic (PV) generation. It is assumed that there is no local battery storage other than EVs and that the EV batteries are fully available for driving, so that the EVs batteries must be at the intended state of charge at the departure time announced by the EV driver. Our goal is to exploit the potential of the EV batteries capacity as much as possible in order to permit a large area of solar panels, so that even on sunny days all PV power can be used to supply the building needs or the EV charging at the parking lot. A system architecture and collaboration protocols that account for uncertainties in EV... [more]
Impact of Demand-Side Management on the Reliability of Generation Systems
Hussein Jumma Jabir, Jiashen Teh, Dahaman Ishak, Hamza Abunima
September 21, 2018 (v1)
Keywords: adequacy of generation systems, adequacy of power supply demand-side management, load management, load shaping, power system reliability, preventive and corrective load shifting, real-time load shifting
The load shifting strategy is a form of demand side management program suitable for increasing the reliability of power supply in an electrical network. It functions by clipping the load demand that is above an operator-defined level, at which time is known as peak period, and replaces it at off-peak periods. The load shifting strategy is conventionally performed using the preventive load shifting (PLS) program. In this paper, the corrective load shifting (CLS) program is proven as the better alternative. PLS is implemented when power systems experience contingencies that jeopardise the reliability of the power supply, whereas CLS is implemented only when the inadequacy of the power supply is encountered. The disadvantages of the PLS approach are twofold. First, the clipped energy cannot be totally recovered when it is more than the unused capacity of the off-peak period. The unused capacity is the maximum amount of extra load that can be filled before exceeding the operator-defined le... [more]
Investment Strategy and Multi⁻Objective Optimization Scheme for Premium Power under the Background of the Opening of Electric Retail Side
Yuanqian Ma, Xianyong Xiao, Ying Wang
September 21, 2018 (v1)
Keywords: empirical analysis, investment strategy, multi-participant, optimal investment scheme, premium power, stable two-sided matching
With the opening of electric retail side, premium power value-added service has become a main concern for both sensitive customers (SCs) and new electric retail companies (NERCs). However, due to the lack of appropriate investment strategy and optimal premium power investment scheme (PPIS) determination method, the premium power market is difficult to form, thus SCs’ demand for premium power is difficult to meet. Under such condition, how to determine the investment strategy and choose the optimal PPIS are problems that need to be solved. Motivated by this, this paper proposes a multi⁻participant premium power investment strategy and an optimal PPIS determination method. Suppose that the NERC and the corresponding SCs have already been determined, according to two⁻sided matching theory, taking SCs’ and NERC’s disappointment⁻rejoicing psychological perceptions into consideration, premium power perceived utility (PU) (i.e., the perceived effectiveness or satisfaction degree) can be obtai... [more]
Reactive Power Dispatch Optimization with Voltage Profile Improvement Using an Efficient Hybrid Algorithm †
Zahir Sahli, Abdellatif Hamouda, Abdelghani Bekrar, Damien Trentesaux
September 21, 2018 (v1)
Keywords: hybrid method, loss minimization, optimal reactive power dispatch, Particle Swarm Optimization, tabu search, voltage deviation
This paper presents an efficient approach for solving the optimal reactive power dispatch problem. It is a non-linear constrained optimization problem where two distinct objective functions are considered. The proposed approach is based on the hybridization of the particle swarm optimization method and the tabu-search technique. This hybrid approach is used to find control variable settings (i.e., generation bus voltages, transformer taps and shunt capacitor sizes) which minimize transmission active power losses and load bus voltage deviations. To validate the proposed hybrid method, the IEEE 30-bus system is considered for 12 and 19 control variables. The obtained results are compared with those obtained by particle swarm optimization and a tabu-search without hybridization and with other evolutionary algorithms reported in the literature.
Auto-Adaptive Filtering-Based Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles
Jamila Snoussi, Seifeddine Ben Elghali, Mohamed Benbouzid, Mohamed Faouzi Mimouni
September 21, 2018 (v1)
Keywords: frequency energy management, fuel cell hybrid electric vehicle, Lithium ion battery, sliding mode control, ultracapacitors
The global need to solve pollution problems has conducted automotive engineers to promote the development and the use of electric vehicle technologies. This paper focuses on the fuel cell hybrid electric vehicle which uses a proton exchange membrane fuel cell as a main source associated to hybrid storage device: lithium ion battery and ultracapacitors. A common interest in such technology is to spread out the energy flow between its different sources in order to satisfy the power demand for any requested mission. However, the challenging task stills the optimization of this split to reduce hydrogen consumption and respect, at the same time, the system limitations such as admissible limits of storage system capacities and battery current variation. An adaptive filtering-based energy management strategy is proposed in this paper to ensure an optimum distribution of the energy between the sources taking into account dynamic and energetic constraints of each device. For more performance, a... [more]
An Extreme Scenario Method for Robust Transmission Expansion Planning with Wind Power Uncertainty
Zipeng Liang, Haoyong Chen, Xiaojuan Wang, Idris Ibn Idris, Bifei Tan, Cong Zhang
September 21, 2018 (v1)
Keywords: benders’ decomposition, load shedding, transmission network expansion planning, uncertainty, wind power
The rapid incorporation of wind power resources in electrical power networks has significantly increased the volatility of transmission systems due to the inherent uncertainty associated with wind power. This paper addresses this issue by proposing a transmission network expansion planning (TEP) model that integrates wind power resources, and that seeks to minimize the sum of investment costs and operation costs while accounting for the costs associated with the pollution emissions of generator infrastructure. Auxiliary relaxation variables are introduced to transform the established model into a mixed integer linear programming problem. Furthermore, the novel concept of extreme wind power scenarios is defined, theoretically justified, and then employed to establish a two-stage robust TEP method. The decision-making variables of prospective transmission lines are determined in the first stage, so as to ensure that the operating variables in the second stage can adapt to wind power fluc... [more]
A Stochastic Inexact Robust Model for Regional Energy System Management and Emission Reduction Potential Analysis—A Case Study of Zibo City, China
Yulei Xie, Linrui Wang, Guohe Huang, Dehong Xia, Ling Ji
September 21, 2018 (v1)
Keywords: electric-power structure adjustment, energy conservation and emissions reduction, energy system management model, scenario-based multistage stochastic programming, stochastic robust optimization
In this study, in order to improve regional energy system adjustment, a multistage stochastic inexact robust programming (MSIRP) is proposed for electric-power generation planning and structure adjustment management under uncertainty. Scenario-based inexact multistage stochastic programming and stochastic robust optimization were integrated into general programming to reflect uncertainties that were expressed as interval values and probability distributions in the objective function and constraints. An MSIRP-based energy system optimization model is proposed for electric-power structure management of Zibo City in Shandong Province, China. Three power demand scenarios associated with electric-power structure adjustment, imported electricity, and emission reduction were designed to obtain multiple decision schemes for supporting regional sustainable energy system development. The power generation schemes, imported electricity, and emissions of CO₂ and air pollutants were analyzed. The re... [more]
Sequence Planning for Selective Disassembly Aiming at Reducing Energy Consumption Using a Constraints Relation Graph and Improved Ant Colony Optimization Algorithm
Bingtao Hu, Yixiong Feng, Hao Zheng, Jianrong Tan
September 21, 2018 (v1)
Keywords: constraints relation graph, disassembly sequence planning, energy consumption, improved ant colony optimization algorithm, selective disassembly
With environmental pollution and the shortage of resources becoming increasingly serious, the disassembly of certain component in mechanical products for reuse and recycling has received more attention. However, how to model a complex mechanical product accurately and simply, and minimize the number of components involved in the disassembly process remain unsolved problems. The identification of subassembly can reduce energy consumption, but the process is recursive and may change the number of components to be disassembled. In this paper, a method aiming at reducing the energy consumption based on the constraints relation graph (CRG) and the improved ant colony optimization algorithm (IACO) is proposed to find the optimal disassembly sequence. Using the CRG, the subassembly is identified and the number of components that need to be disassembled is minimized. Subsequently, the optimal disassembly sequence can be planned using IACO where a new pheromone factor is proposed to improve the... [more]
Online Energy Management and Heterogeneous Task Scheduling for Smart Communities with Residential Cogeneration and Renewable Energy
Yongsheng Cao, Guanglin Zhang, Demin Li, Lin Wang, Zongpeng Li
September 21, 2018 (v1)
Keywords: dynamic energy management, energy sharing, resCHP system, Sarsa algorithm, smart grid
With the development of renewable energy technology and communication technology in recent years, many residents now utilize renewable energy devices in their residences with energy storage systems. We have full confidence in the promising prospects of sharing idle energy with others in a community. However, it is a great challenge to share residents’ energy with others in a community to minimize the total cost of all residents. In this paper, we study the problem of energy management and task scheduling for a community with renewable energy and residential cogeneration, such as residential combined heat and power system (resCHP) to pay the least electricity bill. We take elastic and inelastic load demands into account which are delay intolerant and delay tolerant tasks in the community. The minimum cost problem of a non-cooperative community is extracted into a random non-convex optimization problem with some physical constraints. Our objective is to minimize the time-average cost for... [more]
A Study on the Fuel Economy Potential of Parallel and Power Split Type Hybrid Electric Vehicles
Hyunhwa Kim, Junbeom Wi, Jiho Yoo, Hanho Son, Chiman Park, Hyunsoo Kim
September 21, 2018 (v1)
Keywords: dynamic programming, fuel economy potential, hybrid electric vehicle (HEV), number of gear steps, power split type, transmission mounted electric device (TMED) type
What is the best number of gear steps for parallel type hybrid electric vehicles (HEVs) and what are the pros and cons of the power split type HEV compared to the parallel type have been interesting issues in the development of HEVs. In this study, a comparative analysis was performed to evaluate the fuel economy potential of a parallel HEV and a power split type HEV. First, the fuel economy potential of the parallel HEV was investigated for the number of gear steps. Four-speed, six-speed, and eight-speed automatic transmissions (ATs) and a continuously variable transmission (CVT) were selected, and their drivetrain losses were considered in the dynamic programming (DP). It was found from DP results that the power electronics system (PE) loss decreased because the magnitude of the motor load leveling power decreased as the number of gear steps increased. On the other hand, the drivetrain losses including the electric oil pump (EOP) loss increased with increasing gear step. The improvem... [more]
Italian Experience on Electrical Storage Ageing for Primary Frequency Regulation
Roberto Benato, Sebastian Dambone Sessa, Maura Musio, Francesco Palone, Rosario Maria Polito
September 21, 2018 (v1)
Keywords: large-scale electrochemical storage, lithium-ion secondary batteries, secondary battery ageing, sodium-nickel chloride secondary batteries, storage lab
The paper describes the results of different types of ageing tests performed by Terna (the Italian Transmission System Operator) applied to several electrochemical technologies, namely lithium-based and sodium-nickel chloride-based technologies. In particular, the tested lithium-based technologies exploit a graphite-based anode and the following cathode electrochemistries: lithium iron phosphate, lithium nickel cobalt aluminium, lithium nickel cobalt manganese, and lithium titanate. These tests have been performed in the storage labs located in Sardinia (Codrongianos) and Sicily (Ciminna). The aim of the storage labs is intended to give the electrical grid ancillary services, for example, primary frequency regulation, secondary frequency regulation, voltage regulation, synthetic rotational inertia provision, and many more. For the primary frequency regulation service, the ageing of the batteries is difficult to foresee as the ageing tests are not standardized. The authors proposed some... [more]
A Decentralized Local Flexibility Market Considering the Uncertainty of Demand
Ayman Esmat, Julio Usaola, Mª Ángeles Moreno
September 21, 2018 (v1)
Keywords: aggregators, demand flexibility, flexibility market, payback effect, uncertainty
The role of the distribution system operator (DSO) is evolving with the increasing possibilities of demand management and flexibility. Rather than implementing conventional approaches to mitigate network congestions, such as upgrading existing assets, demand flexibility services have been gaining much attention lately as a solution to defer the need for network reinforcements. In this paper, a framework for a decentralized local market that enables flexibility services trading at the distribution level is introduced. This market operates on two timeframes, day-ahead and real-time and it allows the DSO to procure flexibility services which can help in its congestion management process. The contribution of this work lies in considering the uncertainty of demand during the day-ahead period. As a result, we introduce a probabilistic process that supports the DSO in assessing the true need of obtaining flexibility services based on the probability of congestion occurrence in the following d... [more]
An Electric Bus Power Consumption Model and Optimization of Charging Scheduling Concerning Multi-External Factors
Yajing Gao, Shixiao Guo, Jiafeng Ren, Zheng Zhao, Ali Ehsan, Yanan Zheng
September 21, 2018 (v1)
Keywords: modeling of power consumption, multi external factors, optimal charging scheduling, similar day selection, the grey relational analysis, wavelet neural network
With the large scale operation of electric buses (EBs), the arrangement of their charging optimization will have a significant impact on the operation and dispatch of EBs as well as the charging costs of EB companies. Thus, an accurate grasp of how external factors, such as the weather and policy, affect the electric consumption is of great importance. Especially in recent years, haze is becoming increasingly serious in some areas, which has a prominent impact on driving conditions and resident travel modes. Firstly, the grey relational analysis (GRA) method is used to analyze the various external factors that affect the power consumption of EBs, then a characteristic library of EBs concerning similar days is established. Then, the wavelet neural network (WNN) is used to train the power consumption factors together with power consumption data in the feature library, to establish the power consumption prediction model with multiple factors. In addition, the optimal charging model of EBs... [more]
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