Records with Subject: Planning & Scheduling
Showing records 1 to 25 of 78. [First] Page: 1 2 3 4 Last
Robust Peak-Shaving for a Neighborhood with Electric Vehicles
Marco E. T. Gerards, Johann L. Hurink
January 7, 2019 (v1)
Keywords: adaptive scheduling, demand side management, electric vehicles, optimal scheduling, smart grids
Demand Side Management (DSM) is a popular approach for grid-aware peak-shaving. The most commonly used DSM methods either have no look ahead feature and risk deploying flexibility too early, or they plan ahead using predictions, which are in general not very reliable. To counter this, a DSM approach is presented that does not rely on detailed power predictions, but only uses a few easy to predict characteristics. By using these characteristics alone, near optimal results can be achieved for electric vehicle (EV) charging, and a bound on the maximal relative deviation is given. This result is extended to an algorithm that controls a group of EVs such that a transformer peak is avoided, while simultaneously keeping the individual house profiles as flat as possible to avoid cable overloading and for improved power quality. This approach is evaluated using different data sets to compare the results with the state-of-the-art research. The evaluation shows that the presented approach is capa... [more]
Energy Optimization in Smart Homes Using Customer Preference and Dynamic Pricing
Muhammad Babar Rasheed, Nadeem Javaid, Ashfaq Ahmad, Mohsin Jamil, Zahoor Ali Khan, Umar Qasim, Nabil Alrajeh
January 7, 2019 (v1)
Keywords: binary knapsack, demand response, energy optimization, peak load avoidance, smart grid, time of use pricing
In this paper, we present an energy optimization technique to schedule three types of household appliances (user dependent, interactive schedulable and unschedulable) in response to the dynamic behaviours of customers, electricity prices and weather conditions. Our optimization technique schedules household appliances in real time to optimally control their energy consumption, such that the electricity bills of end users are reduced while not compromising on user comfort. More specifically, we use the binary multiple knapsack problem formulation technique to design an objective function, which is solved via the constraint optimization technique. Simulation results show that average aggregated energy savings with and without considering the human presence control system are 11.77% and 5.91%, respectively.
Optimal Cooling Load Sharing Strategies for Different Types of Absorption Chillers in Trigeneration Plants
Benedetto Conte, Joan Carles Bruno, Alberto Coronas
January 7, 2019 (v1)
Keywords: absorption chillers, optimal operation, partial load, trigeneration
Trigeneration plants can use different types of chillers in the same plant, typically single effect and double effect absorption chillers, vapour compression chillers and also cooling storage systems. The highly variable cooling demand of the buildings connected to a district heating and cooling (DHC) network has to be distributed among these chillers to achieve lower operating costs and higher energy efficiencies. This problem is difficult to solve due to the different partial load behaviour of each chiller and the different chiller combinations that can cover a certain cooling demand using an appropriate sizing of the cooling storage. The objective of this paper is to optimize the daily plant operation of an existing trigeneration plant based on cogeneration engines and to study the optimal cooling load sharing between different types of absorption chillers using a mixed integer linear programming (MILP) model. Real data from a trigeneration plant connected to a DHC close to Barcelon... [more]
Multislot Simultaneous Spectrum Sensing and Energy Harvesting in Cognitive Radio
Xin Liu, Zhenyu Na, Min Jia, Xuemai Gu, Xiaotong Li
January 7, 2019 (v1)
Keywords: cognitive radio (CR), detection probability, energy harvesting, spectrum sensing, throughput
In cognitive radio (CR), the spectrum sensing of the primary user (PU) may consume some electrical power from the battery capacity of the secondary user (SU), resulting in a decrease in the transmission power of the SU. In this paper, a multislot simultaneous spectrum sensing and energy harvesting model is proposed, which uses the harvested radio frequency (RF) energy of the PU signal to supply the spectrum sensing. In the proposed model, the sensing duration is divided into multiple sensing slots consisting of one local-sensing subslot and one energy-harvesting subslot. If the PU is detected to be present in the local-sensing subslot, the SU will harvest RF energy of the PU signal in the energy-harvesting slot, otherwise, the SU will continue spectrum sensing. The global decision on the presence of the PU is obtained through combining local sensing results from all the sensing slots by adopting “Or-logic Rule”. A joint optimization problem of sensing time and time splitter factor is p... [more]
Indirect Load Control for Energy Storage Systems Using Incentive Pricing under Time-of-Use Tariff
Mu-Gu Jeong, Seung-Il Moon, Pyeong-Ik Hwang
January 7, 2019 (v1)
Keywords: bilevel programming, demand-side management, energy storage system (ESS), indirect load control (ILC)
Indirect load control (ILC) is a method by which the customer determines load reduction of electricity by using a price signal. One of the ILCs is a time-of-use (TOU) tariff, which is the most commonly used time-varying retail pricing. Under the TOU tariff, the customer can reduce the energy cost through an energy storage system (ESS). However, because this tariff is fixed for several months, the ESS operation does not truly reflect the wholesale market price, which could widely fluctuate. To overcome this limitation, this paper proposes an incentive pricing method in which the load-serving entity (LSE) gives the incentive pricing signal to the customers with ESSs. Because the ESS charging schedule is determined by the customer through ILC, a bilevel optimization problem that includes the customer optimization problem is utilized to determine the incentive pricing signal. Further, the bilevel optimization problem is reformulated into a one-level problem to be solved by an interior poin... [more]
Harnessing the Flexibility of Thermostatic Loads in Microgrids with Solar Power Generation
Rosa Morales González, Shahab Shariat Torbaghan, Madeleine Gibescu, Sjef Cobben
January 7, 2019 (v1)
Keywords: commercial and industrial areas, demand response, Genetic Algorithm, local RES integration, microgrids, mixed-integer optimization, physical system modeling, smart grid, thermostatic load modeling
This paper presents a demand response (DR) framework that intertwines thermodynamic building models with a genetic algorithm (GA)-based optimization method. The framework optimizes heating/cooling schedules of end-users inside a business park microgrid with local distributed generation from renewable energy sources (DG-RES) based on two separate objectives: net load minimization and electricity cost minimization. DG-RES is treated as a curtailable resource in anticipation of future scenarios where the infeed of DG-RES to the regional distribution network could be limited. We test the DR framework with a case study of a refrigerated warehouse and an office building located in a business park with local PV generation. Results show the technical potential of the DR framework in harnessing the flexibility of the thermal masses from end-user sites in order to: (1) reduce the energy exchange at the point of connection; (2) reduce the cost of electricity for the microgrid end-users; and (3) i... [more]
Coordination Control of a Novel Wind Farm Configuration Including a Hydrogen Storage System and a Gas Turbine
Shihua Xuan, Weihao Hu, Jun Yao, Zhe Chen
January 7, 2019 (v1)
Keywords: electrolyzer, gas turbine, Hydrogen, wind farm
This paper proposes a novel configuration that combines wind turbines, an electrolyzer, and a gas turbine with the corresponding generator. A control strategy for this configuration is also proposed. The purpose of this configuration and its control strategy is to make the wind farm work like a conventional power plant from a grid’s point of view. The final proposed configuration works properly with the proposed control strategy, the three times per revolution (3p) oscillation frequency is removed and the output power fluctuations caused by wind fluctuation are compensated. The final power output of the proposed configuration is constant like that of a conventional power plant, and it can change according to the different requirements of the transmission system operator.
Combined Two-Stage Stochastic Programming and Receding Horizon Control Strategy for Microgrid Energy Management Considering Uncertainty
Zhongwen Li, Chuanzhi Zang, Peng Zeng, Haibin Yu
January 7, 2019 (v1)
Keywords: energy management, microgrid, recording horizon control, stochastic programming, uncertainty
Microgrids (MGs) are presented as a cornerstone of smart grids. With the potential to integrate intermittent renewable energy sources (RES) in a flexible and environmental way, the MG concept has gained even more attention. Due to the randomness of RES, load, and electricity price in MG, the forecast errors of MGs will affect the performance of the power scheduling and the operating cost of an MG. In this paper, a combined stochastic programming and receding horizon control (SPRHC) strategy is proposed for microgrid energy management under uncertainty, which combines the advantages of two-stage stochastic programming (SP) and receding horizon control (RHC) strategy. With an SP strategy, a scheduling plan can be derived that minimizes the risk of uncertainty by involving the uncertainty of MG in the optimization model. With an RHC strategy, the uncertainty within the MG can be further compensated through a feedback mechanism with the lately updated forecast information. In our approach,... [more]
Optimal Planning of Sustainable Buildings: Integration of Life Cycle Assessment and Optimization in a Decision Support System (DSS)
Fabio Magrassi, Adriana Del Borghi, Michela Gallo, Carlo Strazza, Michela Robba
December 3, 2018 (v1)
Keywords: decision support system (DSS), life cycle assessment (LCA), nearly-zero energy buildings, Optimization, sustainable buildings
Energy efficiency measures in buildings can provide for a significant reduction of greenhouse gas (GHG) emissions. A sustainable design and planning of technologies for energy production should be based on economic and environmental criteria. Life Cycle Assessment (LCA) is used to quantify the environmental impacts over the whole cycle of life of production plants. Optimization models can support decisions that minimize costs and negative impacts. In this work, a multi-objective decision problem is formalized that takes into account LCA calculations and that minimizes costs and GHG emissions for general buildings. A decision support system (DSS) is applied to a real case study in the Northern Italy, highlighting the advantage provided by the installation of renewable energy. Moreover, a comparison among different optimal and non optimal solution was carried out to demonstrate the effectiveness of the proposed DSS.
Integrated Combined Heat and Power System Dispatch Considering Electrical and Thermal Energy Storage
Rongxiang Yuan, Jun Ye, Jiazhi Lei, Timing Li
November 28, 2018 (v1)
Keywords: combined heat and power, dispatch, electrical energy storage, thermal energy storage
Wind power has achieved great development in Northern China, but abundant wind power is dissipated, rather than utilized, due to inflexible electricity production of combined heat and power (CHP) units. In this paper, an integrated CHP system consisting of CHP units, wind power plants, and condensing power plants is investigated to decouple the power and heat production on both the power supply side and heat supply side, by incorporating electrical energy storage (EES) and thermal energy storage (TES). Then the integrated CHP system dispatch (ICHPSD) model is formulated to reach the target of reducing wind power curtailment and primary energy consumption. Finally, the feasibility and effectiveness of the proposed ICHPSD model are verified by the six-bus system, and the simulation results show that EES has a better effect on wind power integration than TES. The annual net benefits by incorporating EES and TES increase with increasing wind penetration, but they gradually approach saturat... [more]
Scheduling of Electricity Storage for Peak Shaving with Minimal Device Wear
Thijs van der Klauw, Johann L. Hurink, Gerard J. M. Smit
November 28, 2018 (v1)
Keywords: device aging, electrical energy storage, mixed integer linear program (MILP), peak shaving, polynomial time optimal algorithm
In this work, we investigate scheduling problems for electrical energy storage systems and formulate an algorithm that finds an optimal solution with minimal charging cycles in the case of a single device. For the considered problems, the storage system is used to reduce the peaks of the production and consumption within (part of) the electricity distribution grid, while minimizing device wear. The presented mathematical model of the storage systems captures the general characteristic of electrical energy storage devices while omitting the details of the specific technology used to store the energy. In this way, the model can be applied to a wide range of settings. Within the model, the wear of the storage devices is modeled by either: (1) the total energy throughput; or (2) the number of switches between charging and discharging, the so-called charging cycles. For the first case, where the energy throughput determines the device wear, a linear programming formulation is given. For the... [more]
Optimal Scheduling of Energy Storage System for Self-Sustainable Base Station Operation Considering Battery Wear-Out Cost
Yohwan Choi, Hongseok Kim
November 28, 2018 (v1)
Keywords: battery wear-out cost, demand response (DR), dynamic programming (DP), energy storage system (ESS), optimal scheduling, peak shift, photovoltaic (PV), sustainable base station (BS)
A self-sustainable base station (BS) where renewable resources and energy storage system (ESS) are interoperably utilized as power sources is a promising approach to save energy and operational cost in communication networks. However, high battery price and low utilization of ESS intended for uninterruptible power supply (UPS) necessitates active utilization of ESS. This paper proposes a multi-functional framework of ESS using dynamic programming (DP) for realizing a sustainable BS. We develop an optimal charging and discharging scheduling algorithm considering a detailed battery wear-out model to minimize operational cost as well as to prolong battery lifetime. Our approach significantly reduces total cost compared to the conventional method that does not consider battery wear-out. Extensive experiments for several scenarios exhibit that total cost is reduced by up to 70.6% while battery wear-out is also reduced by 53.6%. The virtue of the proposed framework is its wide applicability... [more]
Power Production Losses Study by Frequency Regulation in Weak-Grid-Connected Utility-Scale Photovoltaic Plants
Jesús Muñoz-Cruzado-Alba, Christian A. Rojas, Samir Kouro, Eduardo Galván Díez
November 27, 2018 (v1)
Keywords: battery energy storage system (BESS), distributed generators, frequency regulation (FR), utility-scale photovoltaic plants (USPVPs), weak grids
Nowadays, an increasing penetration of utility-scale photovoltaic plants (USPVPs) leads to a change in dynamic and operational characteristics of the power distribution system. USPVPs must help to maintain the system stability and reliability while implementing minimum technical requirements (MTRs) imposed by the utility grid. One of the most significant requirements is about frequency regulation (FR). Overall production of USPVPs is reduced significantly by applying FR curves, especially in weak grids with high rate of frequency faults. The introduction of a battery energy storage system (BESS) reduces losses and improves the grid system reliability. Experimental frequency and irradiance data of several weak grids have been used to analyse USPVPs losses related to FR requirements and benefits from the introduction of a BESS. Moreover, its economic viability is showen without the need for any economic incentives.
Optimal Day-Ahead Scheduling of a Smart Distribution Grid Considering Reactive Power Capability of Distributed Generation
Rongxiang Yuan, Timing Li, Xiangtian Deng, Jun Ye
November 27, 2018 (v1)
Keywords: distributed energy resources (DERs), emissions, network loss, reactive power support, smart distribution grid
In the traditional paradigm, large power plants provide active and reactive power required for the transmission system and the distribution network purchases grid power from it. However, with more and more distributed energy resources (DERs) connected at distribution levels, it is necessary to schedule DERs to meet their demand and participate in the electricity markets at the distribution level in the near future. This paper proposes a comprehensive operational scheduling model to be used in the distribution management system (DMS). The model aims to determine optimal decisions on active elements of the network, distributed generations (DGs), and responsive loads (RLs), seeking to minimize the day-ahead composite economic cost of the distribution network. For more detailed simulation, the composite cost includes the aspects of the operation cost, emission cost, and transmission loss cost of the network. Additionally, the DMS effectively utilizes the reactive power support capabilities... [more]
Decentralized Renewable Hybrid Mini-Grids for Sustainable Electrification of the Off-Grid Coastal Areas of Bangladesh
Majbaul Alam, Subhes Bhattacharyya
November 27, 2018 (v1)
Keywords: coastal Bangladesh, hybrid mini-grids, hybrid optimisation of multiple energy resources (HOMER), off-grid electrification
Lack of access to energy is considered as a serious bottleneck for the socio-economic development of Bangladesh. Despite earning recognition for promoting solar home systems, most of the rural areas and remote islands of the country still remain non-electrified due to very high unit cost and low quality of electricity from solar home systems (SHS) coupled with only few hours of restricted usages in the evening. Considering the resource potential and demand characteristics at the local level, the present study investigates the hybrid renewable mini-grid approach as a possible solution for universal electricity access in the country. Using Hybrid Optimisation of Multiple Energy Resources (HOMER) simulation model, the study, covering the whole coastal region of Bangladesh, shows that it is possible to offer a much better quality electricity for 12 h to 18 h a day for as low as USD 0.29⁻USD 0.31/kWh. Hybrid models suggested in this study can be replicated along the coastal belt and remote... [more]
A Novel Power-Saving Transmission Scheme for Multiple-Component-Carrier Cellular Systems
Yao-Liang Chung
November 27, 2018 (v1)
Keywords: green cellular systems, multiple component carriers, power-saving
As mobile data traffic levels have increased exponentially, resulting in rising energy costs in recent years, the demand for and development of green communication technologies has resulted in various energy-saving designs for cellular systems. At the same time, recent technological advances have allowed multiple component carriers (CCs) to be simultaneously utilized in a base station (BS), a development that has made the energy consumption of BSs a matter of increasing concern. To help address this concern, herein we propose a novel scheme aimed at efficiently minimizing the power consumption of BS transceivers during transmission, while still ensuring good service quality and fairness for users. Specifically, the scheme utilizes the dynamic activation/deactivation of CCs during data transmission to increase power usage efficiency. To test its effectiveness, the proposed scheme was applied to a model consisting of a BS with orthogonal frequency division multiple access-based CCs in a... [more]
Optimization of the Heating System Use in Aged Public Buildings via Model Predictive Control
Edorta Carrascal, Izaskun Garrido, Aitor J. Garrido, José María Sala
November 27, 2018 (v1)
Keywords: Energy Efficiency, energy-saving policies, Model Predictive Control, RC-thermal model, system characterization, thermal comfort
This work presents the implementation of a Model Predictive Control (MPC) scheme used to study the improvement of the thermal quality in aged residential buildings without any rehabilitation. The controller manages the heating system of an experimentally characterized model of a residential dwelling in a social block built during the decade of the 1960s located in the neighborhood of Otxarkoaga (Bilbao, Spain), so as to obtain an optimal energy efficiency performance. Due to the characteristics of the construction in those days, this kind of buildings suffer problems related to the use of awkward building materials and inefficient heating systems. A comparison with traditionally used ON-OFF hysteresis control is presented in order to demonstrate the energetic improvement provided by the MPC scheme. Besides, the variation of different parameters of the MPC is also studied to determine its influence over the energy consumption and comfort conditions.
Optimization Design of an Inductive Energy Harvesting Device for Wireless Power Supply System Overhead High-Voltage Power Lines
Wei Wang, Xueliang Huang, Linlin Tan, Jinpeng Guo, Han Liu
November 27, 2018 (v1)
Keywords: energy harvesting, high voltage power line, power fluctuation, wireless power supply
Overhead high voltage power line (HVPL) online monitoring equipment is playing an increasingly important role in smart grids, but the power supply is an obstacle to such systems’ stable and safe operation, so in this work a hybrid wireless power supply system, integrated with inductive energy harvesting and wireless power transmitting, is proposed. The energy harvesting device extracts energy from the HVPL and transfers that from the power line to monitoring equipment on transmission towers by transmitting and receiving coils, which are in a magnetically coupled resonant configuration. In this paper, the optimization design of online energy harvesting devices is analyzed emphatically by taking both HVPL insulation distance and wireless power supply efficiency into account. It is found that essential parameters contributing to more extracted energy include large core inner radius, core radial thickness, core height and small core gap within the threshold constraints. In addition, there... [more]
On the Front Lines of a Sustainable Transportation Fleet: Applications of Vehicle-to-Grid Technology for Transit and School Buses
Tolga Ercan, Mehdi Noori, Yang Zhao, Omer Tatari
November 27, 2018 (v1)
Keywords: air emission externalities, battery electric transit and school buses, life cycle assessment (LCA), regional electricity grid mix, vehicle to grid (V2G)
The electricity generation/supply and transportation sectors are the two largest contributors to greenhouse gas (GHG) emissions in the U.S., and vehicle-to-grid (V2G) technology is a rapidly emerging solution to reduce these emissions with the adoption of battery-electric (BE) vehicles. Deployments of BE transit and school buses are expected to have larger battery capacities than passenger vehicles, making them more feasible candidates for V2G service. Five electricity generation regions are considered for cash flow analysis of BE and diesel transit and school buses over their entire respective lifetimes with the allowance of V2G services’ net revenue. Besides, the environmental benefits of using the V2G system are studied in place of combustion power generation plants for the regulation services of each study region. Air emission externalities are another crucial issue for bus operations because buses are operated near highly populated areas, so these externalities are also studied in... [more]
Realistic Scheduling Mechanism for Smart Homes
Danish Mahmood, Nadeem Javaid, Nabil Alrajeh, Zahoor Ali Khan, Umar Qasim, Imran Ahmed, Manzoor Ilahi
November 27, 2018 (v1)
Keywords: appliance classification, appliance scheduling, Binary Particle Swarm Optimization (BPSO), Demand Response (DR) programs, Demand Side Management (DSM), Home Energy Management System (HEMS), time of use pricing, user comfort
In this work, we propose a Realistic Scheduling Mechanism (RSM) to reduce user frustration and enhance appliance utility by classifying appliances with respective constraints and their time of use effectively. Algorithms are proposed regarding functioning of home appliances. A 24 hour time slot is divided into four logical sub-time slots, each composed of 360 min or 6 h. In these sub-time slots, only desired appliances (with respect to appliance classification) are scheduled to raise appliance utility, restricting power consumption by a dynamically modelled power usage limiter that does not only take the electricity consumer into account but also the electricity supplier. Once appliance, time and power usage limiter modelling is done, we use a nature-inspired heuristic algorithm, Binary Particle Swarm Optimization (BPSO), optimally to form schedules with given constraints representing each sub-time slot. These schedules tend to achieve an equilibrium amongst appliance utility and cost... [more]
Improving the Eco-Efficiency of High Performance Computing Clusters Using EECluster
Alberto Cocaña-Fernández, Luciano Sánchez, José Ranilla
November 27, 2018 (v1)
Keywords: energy-efficient cluster computing, evolutionary algorithms, multi-criteria decision making
As data and supercomputing centres increase their performance to improve service quality and target more ambitious challenges every day, their carbon footprint also continues to grow, and has already reached the magnitude of the aviation industry. Also, high power consumptions are building up to a remarkable bottleneck for the expansion of these infrastructures in economic terms due to the unavailability of sufficient energy sources. A substantial part of the problem is caused by current energy consumptions of High Performance Computing (HPC) clusters. To alleviate this situation, we present in this work EECluster, a tool that integrates with multiple open-source Resource Management Systems to significantly reduce the carbon footprint of clusters by improving their energy efficiency. EECluster implements a dynamic power management mechanism based on Computational Intelligence techniques by learning a set of rules through multi-criteria evolutionary algorithms. This approach enables clu... [more]
Electric Vehicle Charging and Discharging Coordination on Distribution Network Using Multi-Objective Particle Swarm Optimization and Fuzzy Decision Making
Dongqi Liu, Yaonan Wang, Yongpeng Shen
November 27, 2018 (v1)
Keywords: coordinated charging, electric vehicle (EV), optimal scheduling, smart grid, vehicle-to-grid (V2G)
This paper proposed a optimal strategy for coordinated operation of electric vehicles (EVs) charging and discharging with wind-thermal system. By aggregating a large number of EVs, the huge total battery capacity is sufficient to stabilize the disturbance of the transmission grid. Hence, a dynamic environmental dispatch model which coordinates a cluster of charging and discharging controllable EV units with wind farms and thermal plants is proposed. A multi-objective particle swarm optimization (MOPSO) algorithm and a fuzzy decision maker are put forward for the simultaneous optimization of grid operating cost, CO₂ emissions, wind curtailment, and EV users’ cost. Simulations are done in a 30 node system containing three traditional thermal plants, two carbon capture and storage (CCS) thermal plants, two wind farms, and six EV aggregations. Contrast of strategies under different EV charging/discharging price is also discussed. The results are presented to prove the effectiveness of the... [more]
Distributed Renewable Generation and Storage System Sizing Based on Smart Dispatch of Microgrids
Raji Atia, Noboru Yamada
November 27, 2018 (v1)
Keywords: demand response (DR), distributed power generation, energy management, Energy Storage, microgrid (MG), Optimization
This paper considers the contribution of independent owners (IOs) operating within microgrids (MGs) toward green power generation in deregulated energy markets. An optimization scheme is introduced for sizing distributed renewable generation (DRG) and a distributed energy storage system (DESS) based on a novel energy management system (EMS) that accounts for demand response (DR), DESS dispatch and performance degradation, dynamic pricing environments, power distribution loss and irregular renewable generation. The proposed EMS utilizes an iterative Newton-Raphson linear programming algorithm that schedules resources in order to minimize the objective function, to deal with the complicated nonlinear nature of the problem and to enable efficient long-term assessments. The EMS is used to evaluate candidate solutions that are generated by a genetic algorithm (GA) to determine the optimal combination of DRG and DESS. A case study for IEEE 34-bus distribution MG in Okinawa, Japan, is used fo... [more]
Optimal Power Management Strategy for Energy Storage with Stochastic Loads
Stefano Pietrosanti, William Holderbaum, Victor M. Becerra
November 27, 2018 (v1)
Keywords: Energy Storage, flywheel, Optimization, power management, RTG crane, stochastic loads
In this paper, a power management strategy (PMS) has been developed for the control of energy storage in a system subjected to loads of random duration. The PMS minimises the costs associated with the energy consumption of specific systems powered by a primary energy source and equipped with energy storage, under the assumption that the statistical distribution of load durations is known. By including the variability of the load in the cost function, it was possible to define the optimality criteria for the power flow of the storage. Numerical calculations have been performed obtaining the control strategies associated with the global minimum in energy costs, for a wide range of initial conditions of the system. The results of the calculations have been tested on a MATLAB/Simulink model of a rubber tyre gantry (RTG) crane equipped with a flywheel energy storage system (FESS) and subjected to a test cycle, which corresponds to the real operation of a crane in the Port of Felixstowe. The... [more]
Application of the Extension Taguchi Method to Optimal Capability Planning of a Stand-alone Power System
Meng-Hui Wang, Mei-Ling Huang, Zi-Yi Zhan, Chong-Jie Huang
November 27, 2018 (v1)
Keywords: analytic hierarchy process (AHP), extension Taguchi method (ETM), extension theory, loss of load probability (LOLP), stand-alone power system (SAPS)
An Extension Taguchi Method (ETM) is proposed on the optimized allocation of equipment capacity for solar cell power generation, wind power generation, full cells, electrolyzer and hydrogen tanks. The ETM is based on the domain knowledge containing the product specifications and allocation levels provided by suppliers and design factors since most of the renewable energy equipment available in the market comes with a specific capacity. A proper orthogonal array is used to collect 18 sets of simulation responses. The extension theory is introduced to determine the correlation function, and factor effects are used to identify the optimized capacity allocation. The hours of power shortage are simulated using Matlab for all capacity allocations at the lowest establishment cost and the optimized capacity allocation of loss of load probability (LOLP). Finally, the extension theory, extension AHP theory, ETM and Analytic Hierarchy Process (AHP) are used to determine the optimized capacity all... [more]
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