Records with Subject: Planning & Scheduling
Showing records 1 to 25 of 34. [First] Page: 1 2 Last
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]
Adjustable Robust Optimization Algorithm for Residential Microgrid Multi-Dispatch Strategy with Consideration of Wind Power and Electric Vehicles
Ruifeng Shi, Shaopeng Li, Changhao Sun, Kwang Y. Lee
September 21, 2018 (v1)
Keywords: adjustable robust optimization, economic analysis, electric vehicles, grouping dispatch, microgrids, multi-dispatch, wind power
A prospect of increasing penetration of uncoordinated electric vehicles (EVs) together with intermittent renewable energy generation in microgrid systems has motivated us to explore an effective strategy for safe and economic operation of such distributed generation systems. This paper presents a robust economic dispatch strategy for grid-connected microgrids. Uncertainty from wind power and EV charging loads is modeled as an uncertain set of interval predictions. Considering the worst case scenario, the proposed strategy can help to regulate the EV charging behaviors, and distributed generation in order to reduce operation cost under practical constraints. To address the issue of over-conservatism of robust optimization, a dispatch interval coefficient is introduced to adjust the level of robustness with probabilistic bounds on constraints, which gradually improves the system's economic efficiency. In addition, in order to facilitate the decision-making strategies from an economic per... [more]
Comparison of the Location and Rating of Energy Storage for Renewables Integration in Residential Low Voltage Networks with Overvoltage Constraints
Andrew F. Crossland, Darren Jones, Neal S. Wade, Sara L. Walker
September 21, 2018 (v1)
Keywords: battery energy storage systems, distributed generation, low voltage distribution network, Planning
Expansion of photovoltaic (PV) generation is increasing the challenge for network operators to keep voltages within operational limits. Voltage rise occurs in low voltage (LV) networks when distributed generators export, particularly at times of low demand. However, there is little work quantifying the scale of voltage issues and subsequently potential solutions across large numbers of real networks. In this paper, a method is presented to analyse a large quantity of geographically and topographically varying distribution networks. The impact of PV on voltages in 9163 real LV distribution networks is then quantified. One potential mitigation measure is increased network demand to reduce voltages. In this work, location algorithms are used to identify where increased demand, through energy storage, has the greatest effect on overvoltage. The study explores the impact on overvoltage of two modes of storage installation reflecting differing routes to adoption: purchase of storage by homeo... [more]
Understanding Continuance Usage of Natural Gas: A Theoretical Model and Empirical Evaluation
Victor Fernández-Guzmán, Edgardo R. Bravo
September 21, 2018 (v1)
Keywords: continuance usage, expectation-confirmation, Natural Gas
The adoption of natural gas increased notably last years, and there is some recognition that it improves the quality of life of inhabitants. While initial acceptance is an essential first step, the continued use is relevant to the long-term success of any technology. However, the literature on energy has focused on adoption and has devoted less attention to models that explain continuance usage. Accordingly, this study developed a model to explain continuance usage, grounded in Expectation-Confirmation Model (ECM). Unlike adoption models, confirmation of previous expectations and satisfaction with the experience of use have a relevant role in this phenomenon. Data was gathered through a questionnaire to 435 users of the service in a Latin American metropolis, and structural equations model was used for analysis. The results show that constructs of the ECM (perceived usefulness, disconfirmation, and satisfaction) influences on continuance intention. While the price impacts as expected,... [more]
The Synergies of Shared Autonomous Electric Vehicles with Renewable Energy in a Virtual Power Plant and Microgrid
Riccardo Iacobucci, Benjamin McLellan, Tetsuo Tezuka
September 21, 2018 (v1)
Keywords: charge optimization, electric vehicles, Renewable Energy, shared transportation, vehicle-to-grid
The introduction of shared autonomous electric vehicles (SAEVs), expected within the next decade, can transform the car into a service, accelerate electrification of the transport sector, and allow for large scale control of electric vehicle charging. In this work, we investigate the potential for this system to provide aggregated storage when combined with intermittent renewable energy sources. We develop a simulation methodology for the optimization of vehicle charging in the context of a virtual power plant or microgrid, with and without grid connection or distributed dispatchable generators. The model considers aggregate storage availability from vehicles based on transport patterns taking into account the necessary vehicle redistribution. We investigate the case of a grid-connected VPP with rooftop solar and the case of a isolated microgrid with solar, wind, and dispatchable generation. We conduct a comprehensive sensitivity analysis to study the effect of several parameters on th... [more]
Estimation of Load Pattern for Optimal Planning of Stand-Alone Microgrid Networks
Chang Koo Lee, Byeong Gwan Bhang, David Kwangsoon Kim, Sang Hun Lee, Hae Lim Cha, Hyung Keun Ahn
September 21, 2018 (v1)
Keywords: energy storage system (ESS), load pattern estimation, microgrid, optimal planning, zero energy network, renewable energy resources
This paper proposes a method for estimating the load pattern for optimal planning of stand-alone renewable microgrids and verifies when the basic data for microgrid design are limited. To estimate a proper load pattern for optimal microgrid design when the data obtained in advance are insufficient, the least squares method is used to compare the similarity of annual power consumption between the subject area and eight islands in Korea whose actual load patterns were previously obtained. Similarity is compared in terms of annual (every month), seasonal, bi-monthly, and monthly averages. To verify the validity of the proposed estimation method, the applied proposed estimation method is used for two islands that have already installed a microgrid consisting of photovoltaic, wind power, energy storage systems, and diesel generators. In comparing the actual data from the two islands, the costs of electricity in terms of microgrid operations show improvements of 37.2% and 29.8%, respectively... [more]
A Fully Distributed Approach for Economic Dispatch Problem of Smart Grid
Bo Li, Yudong Wang, Jian Li, Shengxian Cao
September 21, 2018 (v1)
Keywords: consensus algorithm, distributed control, economic dispatch problem, optimal resource management, Sensor data collection
The cooperative, reliable and responsive characteristics make smart grid more popular than traditional power grid. However, with the extensive employment of smart grid concepts, the traditional centralized control methods expose a lot of shortcomings, such as communication congestion, computing complexity in central management systems, and so on. The distributed control method with flexible characteristics can meet the timeliness and effectiveness of information management in smart grid and ensure the information collection timely and the power dispatch economically. This article presents a decentralized approach based on multi agent system (MAS) for solving data collection and economic dispatch problem of smart grid. First, considering the generators and loads are distributed on many nodes in the space, a flooding-based consensus algorithm is proposed to achieve generator and load information for each agent. Then, a suitable distributed algorithm called λ-consensus is used for solving... [more]
Operation and Economic Assessment of Hybrid Refueling Station Considering Traffic Flow Information
Suyang Zhou, Yuxuan Zhuang, Wei Gu, Zhi Wu
September 21, 2018 (v1)
Keywords: battery storage, electricity tariffs, hybrid refueling station, integrated refueling station, mixed integer linear programming, optimal planning, Renewable Energy
It is anticipated that the penetration of “Green-Energy„ vehicles, including Electric Vehicle (EV), Fuel Cell Vehicle (FCV), and Natural Gas Vehicle (NGV) will keep increasing in next decades. The demand of refueling stations will correspondingly increase for refueling these “Green-Energy„ vehicles. While such kinds of “Green-Energy„ vehicles can provide both social and economic benefits, effective management of refueling various kinds of these vehicles is necessary to maintain vehicle users’ comfortabilities and refueling station’s return on investment. To tackle these problems, this paper proposes a novel energy management approach for hybrid refueling stations with EV chargers, Hydrogen pumps and gas pumps. Firstly, the detailed models of EV chargers, Hydrogen pumps with electrolyte and hydrogen tank, the gas pumps with gas tank, renewable resources, and battery energy storage systems are established. The forecasting methodologies for renewable energy, electricity price and the traf... [more]
Distributed Energy Resources Scheduling and Aggregation in the Context of Demand Response Programs
Pedro Faria, João Spínola, Zita Vale
September 21, 2018 (v1)
Keywords: clustering, demand Response, distributed generation, smart grids
Distributed energy resources can contribute to an improved operation of power systems, improving economic and technical efficiency. However, aggregation of resources is needed to make these resources profitable. The present paper proposes a methodology for distributed resources management by a Virtual Power Player (VPP), addressing the resources scheduling, aggregation and remuneration based on the aggregation made. The aggregation is made using K-means algorithm. The innovative aspect motivating the present paper relies on the remuneration definition considering multiple scenarios of operation, by performing a multi-observation clustering. Resources aggregation and remuneration profiles are obtained for 2592 operation scenarios, considering 548 distributed generators, 20,310 consumers, and 10 suppliers.
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