Records with Subject: Planning & Scheduling
Showing records 1 to 25 of 171. [First] Page: 1 2 3 4 5 Last
A Molecular Force Field-Based Optimal Deployment Algorithm for UAV Swarm Coverage Maximization in Mobile Wireless Sensor Network
Xi Wang, Guan-zheng Tan, Fan-Lei Lu, Jian Zhao, Yu-si Dai
May 22, 2020 (v1)
Keywords: coverage maximization, deployment algorithm, molecular force, MWSN, UAV swarm
In the mobile wireless sensor network (MWSN) field, there exists an important problem—how can we quickly form an MWSN to cover a designated working area on the ground using an unmanned aerial vehicle (UAV) swarm? This problem is of significance in many military and civilian applications. In this paper, inspired by intermolecular forces, a novel molecular force field-based optimal deployment algorithm for a UAV swarm is proposed to solve this problem. A multi-rotor UAV swarm is used to carry sensors and quickly build an MWSN in a designated working area. The necessary minimum number of UAVs is determined according to the principle that the coverage area of any three UAVs has the smallest overlap. Based on the geometric properties of a convex polygon, two initialization methods are proposed to make the initial deployment more uniform, following which, the positions of all UAVs are subsequently optimized by the proposed molecular force field-based deployment algorithm. Simulation experime... [more]
Techno-Economic Analysis of CO2 Capture Technologies in Offshore Natural Gas Field: Implications to Carbon Capture and Storage in Malaysia
Norhasyima Rahmad Sukor, Abd Halim Shamsuddin, Teuku Meurah Indra Mahlia, Md Faudzi Mat Isa
May 22, 2020 (v1)
Keywords: carbon capture and storage (CCS), Carbon Dioxide Capture, offshore gas field, Technoeconomic Analysis
Growing concern on global warming directly related to CO2 emissions is steering the implementation of carbon capture and storage (CCS). With Malaysia having an estimated 37 Tscfd (Trillion standard cubic feet) of natural gas remains undeveloped in CO2 containing natural gas fields, there is a need to assess the viability of CCS implementation. This study performs a techno-economic analysis for CCS at an offshore natural gas field in Malaysia. The framework includes a gas field model, revenue model, and cost model. A techno-economic spreadsheet consisting of Net Present Value (NPV), Payback Period (PBP), and Internal Rate of Return (IRR) is developed over the gas field’s production life of 15 years for four distinctive CO2 capture technologies, which are membrane, chemical absorption, physical absorption, and cryogenics. Results predict that physical absorption solvent (Selexol) as CO2 capture technology is most feasible with IRR of 15% and PBP of 7.94 years. The output from the techno-... [more]
Optimization Strategies for Dockless Bike Sharing Systems via two Algorithms of Closed Queuing Networks
Rui-Na Fan, Fan-Qi Ma, Quan-Lin Li
May 22, 2020 (v1)
Keywords: closed queuing network, dockless bike sharing system, flow equivalent server algorithm, mean value analysis, optimization strategy, sustainable transportation
The dockless bike sharing system (DBSS) has been globally adopted as a sustainable transportation system. Due to the robustness and tractability of the closed queuing network (CQN), it is a well-behaved method to model DBSSs. In this paper, we view DBSSs as CQNs and use the mean value analysis (MVA) algorithm to calculate a small size DBSS and the flow equivalent server (FES) algorithm to calculate the larger size DBSS. This is the first time that the FES algorithm is used to study the DBSS, by which the CQN can be divided into different subnetworks. A parking region and its downlink roads are viewed as a subnetwork, so the computation of CQN is reduced greatly. Based on the computation results of the two algorithms, we propose two optimization functions for determining the optimal fleet size and repositioning flow, respectively. At last, we provide numerical experiments to verify the two algorithms and illustrate the optimal fleet size and repositioning flow. This computation framewor... [more]
Water Sources Diagram and Its Applications
Ewerton Emmanuel da Silva Calixto, Fernando Luiz Pellegrini Pessoa, Reinaldo Coelho Mirre, Flávio da Silva Francisco, Eduardo Mach Queiroz
May 18, 2020 (v1)
Keywords: Sources Diagrams, water reuse, Water Sources Diagram, WSD applications
Water Sources Diagram (WSD) has proved to be one of the most efficient methods to reduce industrial freshwater consumption and to provide a minimum amount of wastewater to be treated. Different types of industry have been benefited from the use of this technique, which resulted in great savings in the design of the effluent treatment systems. Among the successful case studies, we mention herein applications in systems with wastewater treatment, thermal and water plants’ integration, oil refineries, petrochemicals, batch processes, pulp and paper plants, and textile plants. The degree of WSD maturity motivated researchers to not only improve WSD algorithms, but also extend the concept of the Sources Diagram to Source/Sink types of process. This paper presents a background of WSD progress as well as insights into future perspectives using the Sources Diagrams’ concept.
A Numerical Study on the Effects of Trust in Supplier Development
Haniyeh Dastyar, Daniel Rippel, Jürgen Pannek, Klaus-Dieter Thoben, Michael Freitag
May 18, 2020 (v1)
Keywords: decision making support, Model Predictive Control, Optimization, supplier development, trust
Supplier development constitutes one of the current tools to enhance supply chain performance. While most literature in this context focuses on the relationship between manufacturers and suppliers, supplier development also provides an opportunity for distinct manufacturers to collaborate in enhancing a joint supplier. This article proposes a model for the optimization of such joint supplier development programs, which incorporates the effects of trust in the manufacturer-to-manufacturer relationship. This article uses a model-predictive formulation to obtain optimal supplier development investment decisions to consider the strong dynamics of the markets. Thereby, the model is designed to be highly customizable to the needs and requirements of different companies. We analyzed the price development related to Mercedes’ A-Class cars and the cost development in the automotive sector over the last ten years in Germany. According to the obtained result, the proposed model shows a sensible b... [more]
Dominance Conditions for Optimal Order-Lot Matching in the Make-To-Order Production System
Jae-Gon Kim, June-Young Bang, Hong-Bae Jun, Jong-Ho Shin
April 14, 2020 (v1)
Keywords: dominance condition, dynamic programming, machine scheduling, order-lot matching problem, total tardiness
Order-lot matching is the process of assigning items in lots being processed in the make-to-order production system to meet the due dates of the orders. In this study, an order-lot matching problem (OLMP) is considered to minimize the total tardiness of orders with different due dates. In the OLMP considered in this study, we need to not only determine the allocation of items to lots in the production facility but also generate a lot release plan for the given time horizon. We show that the OLMP can be considered as a special type of machine scheduling problem with many similarities to the single machine total tardiness scheduling problem ( 1 | | ∑ T i ). We suggest dominance conditions for the OLMP by modifying those for 1 | | ∑ T i and a dynamic programming (DP) model based on the dominance conditions. With two example problems, we show that the DP model can solve small-sized OLMPs optimally.
Feasibility Assessment of Two Biogas-Linked Rural Campus Systems: A Techno-Economic Case Study
Liqin Zhu, Congguang Zhang
April 1, 2020 (v1)
Keywords: biomass conversion, eco-campus, sustainable development, Technoeconomic Analysis
The principle of sustainable development is becoming more and more prominent in various schools, and the eco-campus in rural areas often has more room for display. The identification and assessment of cost-effective biomass resources appropriate for recycling represent an opportunity that may significantly improve the comprehensive efficiency of an eco-campus system, resulting in remarkable investment savings, pollution reduction, as well as reducing energy consumption and resources waste. The economic feasibility of two biogas-linked rural campus systems (Fanjiazhai Middle School, FJZ and Xidazhai Middle School, XDZ, Yangling, China), as well as their key technologies, is investigated, the two systems respectively represent two biobased agricultural production modes. It is found that the initial investment, operating investment, and total revenue of FJZ system is 1.37 times, 2.39 times, and 1.71 times of XDZ system respectively, thus indicating that FJZ campus is proved to be a “large... [more]
Multi-Criteria Decision Making (MCDM) Model for Supplier Evaluation and Selection for Oil Production Projects in Vietnam
Chia-Nan Wang, Hsiung-Tien Tsai, Thanh-Phong Ho, Van-Thanh Nguyen, Ying-Fang Huang
March 12, 2020 (v1)
Keywords: AHP, DEA, MCDM, oil industry, SCOR, supplier selection
The following research utilizes Multi-Criteria Decision Making (MCDM) in order to build a business strategy to reduce product costs, improve competitiveness, focus on production planning based on actual operating capacity and flexible adjustment according to the market, maximize the labor productivity of technology workshops, reduce costs and inventory, and focus on producing many petrochemical products and products of high economic value. Selecting the right materials supplier is of paramount importance to the success of the organization as a whole. Supplier evaluation and the selection of a suitable supplier is a complex problem in which the decision maker must consider both qualitative and quantitative factors. Multi-Criteria Decision Making Models are an effective tool used to solve complex selection issues including multiple criteria and options, especially for qualitative variables. Thus, the author proposes an MCDM model including the Supply Chain Operation Reference (SCOR) mode... [more]
Community-Based Link-Addition Strategies for Mitigating Cascading Failures in Modern Power Systems
Po Hu, Lily Lee
March 12, 2020 (v1)
Keywords: cascading failures, complex network theory, Fast–Newman algorithm, link-addition strategy, power systems
The propagation of cascading failures of modern power systems is mainly constrained by the network topology and system parameter. In order to alleviate the cascading failure impacts, it is necessary to adjust the original network topology considering the geographical factors, construction costs and requirements of engineering practice. Based on the complex network theory, the power system is modeled as a directed graph. The graph is divided into communities based on the Fast−Newman algorithm, where each community contains at least one generator node. Combined with the islanding characteristics and the node vulnerability, three low-degree-node-based link-addition strategies are proposed to optimize the original topology. A new evaluation index combining with the attack difficulty and the island ratio is proposed to measure the impacts on the network under sequential attacks. From the analysis of the experimental results of three attack scenarios, this study adopts the proposed strategie... [more]
A Two-Stage Optimal Scheduling Model of Microgrid Based on Chance-Constrained Programming in Spot Markets
Jiayu Li, Caixia Tan, Zhongrui Ren, Jiacheng Yang, Xue Yu, Zhongfu Tan
February 3, 2020 (v1)
Keywords: chance-constrained programming, demand side management, microgrid, spot markets
Aimed at the coordination control problem of each unit caused by microgrid participation in the spot market and considering the randomness of wind and solar output and the uncertainty of spot market prices, a day-ahead real-time two-stage optimal scheduling model for microgrid was established by using the chance-constrained programming theory. On this basis, an improved particle swarm optimization (PSO) algorithm based on stochastic simulation technology was used to solve the problem and the effect of demand side management and confidence level on scheduling results is discussed. The example results verified the correctness and effectiveness of the proposed model, which can provide a theoretical basis in terms of reasonably coordinating the output of each unit in the microgrid in the spot market.
An Optimization Approach Considering User Utility for the PV-Storage Charging Station Planning Process
Yingxin Liu, Houqi Dong, Shengyan Wang, Mengxin Lan, Ming Zeng, Shuo Zhang, Meng Yang, Shuo Yin
February 3, 2020 (v1)
Keywords: bi-level optimization, green energy, planning process, PV-storage charging stations, user utility
Based on the comprehensive utilization of energy storage, photovoltaic power generation, and intelligent charging piles, photovoltaic (PV)-storage charging stations can provide green energy for electric vehicles (EVs), which can significantly improve the green level of the transportation industry. However, there are many challenges in the PV-storage charging station planning process, making it theoretically and practically significant to study approaches to planning. This paper promotes a bi-level optimization planning approach for PV-storage charging stations. First, taking PV-storage charging stations and EV users as the upper- and lower-level problems, respectively, during the planning process, a bi-level optimization model for PV-storage charging stations considering user utility is established for capacity allocation and user behavior-based electricity pricing. Second, the model is converted into a single-level mixed-integer linear programming model using the piecewise linear util... [more]
Model and Algorithm for Planning Hot-Rolled Batch Processing under Time-of-Use Electricity Pricing
Zhengbiao Hu, Dongfeng He, Wei Song, Kai Feng
February 3, 2020 (v1)
Keywords: Genetic Algorithm, hot rolling, hot rolling planning, TOU electricity pricing
Batch-type hot rolling planning highly affects electricity costs in a steel plant, but previous research models seldom considered time-of-use (TOU) electricity pricing. Based on an analysis of the hot-rolling process and TOU electricity pricing, a batch-processing plan optimization model for hot rolling was established, using an objective function with the goal of minimizing the total penalty incurred by the differences in width, thickness, and hardness among adjacent slabs, as well as the electricity cost of the rolling process. A method was provided to solve the model through improved genetic algorithm. An analysis of the batch processing of the hot rolling of 240 slabs of different sizes at a steel plant proved the effectiveness of the proposed model. Compared to the man−machine interaction model and the model in which TOU electricity pricing was not considered, the batch-processing model that included TOU electricity pricing produced significantly better results with respect to bot... [more]
Integrated Forecasting Method for Wind Energy Management: A Case Study in China
Yao Dong, Lifang Zhang, Zhenkun Liu, Jianzhou Wang
February 3, 2020 (v1)
Keywords: combined model, data preprocessing technology, forecasting accuracy, multi-objective optimization algorithm, wind energy forecasting
Wind speed forecasting helps to increase the efficacy of wind farms and prompts the comparative superiority of wind energy in the global electricity system. Many wind speed forecasting theories have been widely applied to forecast wind speed, which is nonlinear, and unstable. Current forecasting strategies can be applied to various wind speed time series. However, some models neglect the prerequisite of data preprocessing and the objective of simultaneously optimizing accuracy and stability, which results in poor forecast. In this research, we developed a combined wind speed forecasting strategy that includes several components: data pretreatment, optimization, forecasting, and assessment. The developed system remedies some deficiencies in traditional single models and markedly enhances wind speed forecasting performance. To evaluate the performance of this combined strategy, 10-min wind speed sequences gathered from large wind farms in Shandong province in China were adopted as a case... [more]
Modeling of Parallel Movement for Deep-Lane Unit Load Autonomous Shuttle and Stacker Crane Warehousing Systems
Yanyan Wang, Rongjun Man, Xiaofeng Zhao, Hui Liu
February 3, 2020 (v1)
Keywords: autonomous shuttle and stacker crane warehousing system, compact storage systems, elitist non-dominated sorting genetic algorithm, warehouse operation process
The autonomous shuttle and stacker crane (AC/SC) warehousing system, as a new automated deep-lane unit load storage/retrieval system, has been becoming more popular, especially for batch order fulfilment because of its high flexibility, low operational cost and improved storage capacity. This system consists of a shuttle sub-system that controls motion along the x-axis and a stacker crane sub-system that controls motion along the y-axis and z-axis. The combination of shuttles and a stacker crane performs storage and retrieval tasks. Modelling the parallel motion is an important design tool that can be used to calculate the optimal number of shuttles for a given configuration of the warehousing system. In this study, shuttle movements from one lane to another are inserted into the stock-keeping unit (SKU) task queue, and convert such that they are consistent with the retrieval tasks. The tasks are then grouped according to their starting lane, and converted to an assembly-line parallel... [more]
Location Planning for Dynamic Wireless Charging Systems for Electric Airport Passenger Buses
Stefan Helber, Justine Broihan, Young Jae Jang, Peter Hecker, Thomas Feuerle
January 23, 2020 (v1)
Keywords: airport infrastructure planning, apron buses, electric buses, inductive dynamic charging
The majority of the ground vehicles operating on the airside parts of commercial airports are currently powered by diesel engines. These include vehicles such as apron buses, fuel trucks, and aircraft tractors. Hence, these vehicles contribute to the overall CO 2 emissions of the aviation transport system and thus negatively influence its environmental footprint. To reduce this damaging environmental impact, these vehicles could potentially be electrified with on-board batteries as their energy sources. However, the conductive charging of such vehicles via stationary cable connections is rather time-consuming. A dynamic wireless charging system to supply public transportation passenger buses with electric energy while in motion has recently been installed on the Korea Advanced Institute of Science and Technology (KAIST) campus and in the Korean city of Gumi. In this paper, we study configuration problems related to the use of this technology to make airport operations more envi... [more]
A Risk Aversion Dispatching Optimal Model for a Micro Energy Grid Integrating Intermittent Renewable Energy and Considering Carbon Emissions and Demand Response
Xiaoxu Fu, Wei Fan, Hongyu Lin, Nan Li, Peng Li, Liwei Ju, Feng’ao Zhou
January 7, 2020 (v1)
Keywords: demand response, distributed energy, micro energy grid, risk aversion, uncertainty
This paper focuses on an optimal schedule for a micro energy grid considering the maximum total carbon emission allowance (MTEA). Firstly, the paper builds an energy devices operation model and demand response (DR) model. Secondly, to maximize the economical operation revenue, the basic scheduling model for the micro energy grid is constructed. Thirdly, the conditional value at risk method and robust stochastic theory are introduced to describe the uncertainty of wind power, photovoltaic power, and load, and a risk aversion model is proposed. Finally, this paper selects the Xinxiang active distribution network demonstration project in Jining, China as an example. The results show that: (1) a micro energy grid can make the most use of the complementary characters of different energy sources to meet different energy demands for electricity, heat, cold, and gas; (2) the risk aversion scheduling model can represent the influence of uncertainty variables in objective functions and constrain... [more]
Sequential Scheduling Method for FJSP with Multi-Objective under Mixed Work Calendars
Qiang Zeng, Menghua Wang, Ling Shen, Hongna Song
January 2, 2020 (v1)
Keywords: flexible job-shop scheduling, mixed work calendars, multi-objective optimization, NSGA-II, sequential scheduling
A sequential scheduling method for multi-objective, flexible job-shop scheduling problem (FJSP) work calendars is proposed. Firstly, the sequential scheduling problem for the multi-objective FJSP under mixed work calendars was described. Secondly, two key technologies to solve such a problem were proposed: one was a time-reckoning technology based on the machine’s work calendar, the other was a sequential scheduling technology. Then, a non-dominated sorting genetic algorithm with an elite strategy (NSGA-II) was designed to solve the problem. In the algorithm, a two-segment encoding method was used to encode the chromosome. A two-segment crossover and mutation operator were used with an improved strategy of genetic operators therein to ensure feasibility of the chromosomes. Time-reckoning technology was used to calculate start and end time of each process. The sequential scheduling technology was used to implement sequential scheduling. The case study shows that the proposed method can... [more]
Hybrid Integrations of Value Stream Mapping, Theory of Constraints and Simulation: Application to Wooden Furniture Industry
Emad Alzubi, Anas M. Atieh, Khaleel Abu Shgair, John Damiani, Sima Sunna, Abdallah Madi
December 16, 2019 (v1)
Keywords: bottleneck detection, OEE, Simulation, value stream map (VSM), wooden furniture manufacturing case study
This paper studies manufacturing processes in a wooden furniture manufacturing company. The company suffers from long manufacturing lead times and an unbalanced production line. To identify sources of waste and delay value stream mapping (VSM) and a discrete event simulation model is implemented. VSM is used to visualize and analyze the major processes of the company and provide quantifiable KPIs; the manufacturing lead-time and then Overall Equipment Effectiveness (OEE) settings. A discrete event simulation model is then built to analyze the company on a wider scale and provide the data required to identify bottlenecks. Building on the data gathered from the production lines and the simulation model, two-bottleneck detection methods are used, the utilization method, and the waiting time method. Then based on the comparison of the two methods a third bottleneck detection is utilized; the scenario-based method, to identify the primary and secondary bottlenecks. After the bottlenecks are... [more]
Reliability Evaluation Method Considering Demand Response (DR) of Household Electrical Equipment in Distribution Networks
Hongzhong Chen, Jun Tang, Lei Sun, Jiawei Zhou, Xiaolei Wang, Yeying Mao
December 13, 2019 (v1)
Keywords: capacity constraint, demand response, household electrical equipment, incentive mechanism, real-time electricity price, reliability evaluation
The load characteristic of typical household electrical equipment is elaborately analyzed. Considering the electric vehicles’ (EVs’) charging behavior and air conditioning’s thermodynamic property, an electricity price-based demand response (DR) model and an incentive-based DR model for two kinds of typical high-power electrical equipment are proposed to obtain the load curve considering two different kinds of DR mechanisms. Afterwards, a load shedding strategy is introduced to improve the traditional reliability evaluation method for distribution networks, with the capacity constraints of tie lines taken into account. Subsequently, a reliability calculation method of distribution networks considering the shortage of power supply capacity and outages is presented. Finally, the Monte Carlo method is employed to calculate the reliability index of distribution networks with different load levels, and the impacts of different DR strategies on the reliability of distribution networks are an... [more]
Multi-Objective Predictive Control Optimization with Varying Term Objectives: A Wind Farm Case Study
Clara M. Ionescu, Constantin F. Caruntu, Ricardo Cajo, Mihaela Ghita, Guillaume Crevecoeur, Cosmin Copot
December 11, 2019 (v1)
Keywords: distributed model predictive control, multi-objective optimization, sequential optimisation, wind speed estimator, windmill park
This paper introduces the incentive of an optimization strategy taking into account short-term and long-term cost objectives. The rationale underlying the methodology presented in this work is that the choice of the cost objectives and their time based interval affect the overall efficiency/cost balance of wide area control systems in general. The problem of cost effective optimization of system output is taken into account in a multi-objective predictive control formulation and applied on a windmill park case study. A strategy is proposed to enable selection of optimality criteria as a function of context conditions of system operating conditions. Long-term economic objectives are included and realistic simulations of a windmill park are performed. The results indicate the global optimal criterium is no longer feasible when long-term economic objectives are introduced. Instead, local sub-optimal solutions are likely to enable long-term energy efficiency in terms of balanced production... [more]
Frequency Regulation Strategies in Grid Integrated Offshore Wind Turbines via VSC-HVDC Technology: A Review
Jafar Jallad, Saad Mekhilef, Hazlie Mokhlis
December 10, 2019 (v1)
Keywords: frequency regulation, high voltage direct current transmission control, inertia emulation, voltage source converter, wind turbine-permanent magnet synchronous generators (WT-PMSG)
The inclusion of wind energy in a power system network is currently seeing a significant increase. However, this inclusion has resulted in degradation of the inertia response, which in turn seriously affects the stability of the power system’s frequency. This problem can be solved by using an active power reserve to stabilize the frequency within an allowable limit in the event of a sudden load increment or the loss of generators. Active power reserves can be utilized via three approaches: (1) de-loading method (pitching or over-speeding) by a variable speed wind turbine (VSWT); (2) stored energy in the capacitors of voltage source converter-high voltage direct current (VSC-HVDC) transmission; and (3) coordination of frequency regulation between the offshore wind farms and the VSC-HVDC transmission. This paper reviews the solutions that can be used to overcome problems related to the frequency stability of grid- integrated offshore wind turbines. It also details the permanent magnet sy... [more]
Annual Assessment of Large-Scale Introduction of Renewable Energy: Modeling of Unit Commitment Schedule for Thermal Power Generators and Pumped Storages
Takashi Mitani, Muhammad Aziz, Takuya Oda, Atsuki Uetsuji, Yoko Watanabe, Takao Kashiwagi
December 10, 2019 (v1)
Keywords: annual analysis, interior point method, pumped storage, Tabu search, thermal power generator, unit commitment
The fast-increasing introduction of renewable energy sources (RESes) leads to some problems in electrical power network due to fluctuating generated power. A power system must be operated with provision of various reserve powers like governor free capacity, load frequency control and spinning reserve. Therefore, the generator’s schedule (unit commitment schedule) should include the consideration of the various power reserves. In addition, it is necessary to calculate the annual operational costs of electric power systems by solving the unit commitment per week of thermal power generators and pumped storages in order to compare and examine the variance of the operational costs and the operating ratio of the generators throughout the year. This study proposes a novel annual analysis for the thermal power generator and pumped storages under a massive introduction of RESes. A weekly unit commitment schedule (start/stop planning) for thermal power generator and pumped storages has been mode... [more]
Pareto-Efficient Capacity Planning for Residential Photovoltaic Generation and Energy Storage with Demand-Side Load Management
Somi Jung, Dongwoo Kim
December 10, 2019 (v1)
Keywords: capacity planning, home load management, multi-objective optimization, noncooperative game, photovoltaic (PV) generation and energy storage (ES) systems, smart grids
Optimal sizing of residential photovoltaic (PV) generation and energy storage (ES) systems is a timely issue since government polices aggressively promote installing renewable energy sources in many countries, and small-sized PV and ES systems have been recently developed for easy use in residential areas. We in this paper investigate the problem of finding the optimal capacities of PV and ES systems in the context of home load management in smart grids. Unlike existing studies on optimal sizing of PV and ES that have been treated as a part of designing hybrid energy systems or polygeneration systems that are stand-alone or connected to the grid with a fixed energy price, our model explicitly considers the varying electricity price that is a result of individual load management of the customers in the market. The problem we have is formulated by a D-day capacity planning problem, the goal of which is to minimize the overall expense paid by each customer for the planning period. The ove... [more]
Optimal Scheduling of Microgrid with Multiple Distributed Resources Using Interval Optimization
Chongxin Huang, Dong Yue, Song Deng, Jun Xie
December 10, 2019 (v1)
Keywords: distributed resources, interval optimization, microgrid, optimal scheduling scheme
In this paper, an optimal day-ahead scheduling problem is studied for a microgrid with multiple distributed resources. For the sake of coping with the prediction uncertainties of renewable energies and loads and taking advantage of the time-of-use price for buying/selling electricity, an interval-based optimization model for maximum profits is developed. To reduce the computational complexity in solving the model, the possibility degree comparison between an interval and a real number is used to convert the interval constraints into the general ones; meanwhile, some slack variables and complementary conditions are introduced to eliminate the absolute-value operation. Unlike the stochastic optimization, the interval optimization only needs the upper-lower bounds of the uncertain variables instead of their probability distribution functions, which is beneficial to the practical application. Furthermore, the possible profit interval and the expected optimal profit can be determined by solving... [more]
A Chance-Constrained Economic Dispatch Model in Wind-Thermal-Energy Storage System
Yanzhe Hu, Yang Li, Mengjie Xu, Li Zhou, Mingjian Cui
December 10, 2019 (v1)
Keywords: economic dispatch, energy storage system, Gaussian mixture model, power system operations, wind power
As a type of renewable energy, wind energy is integrated into the power system with more and more penetration levels. It is challenging for the power system operators (PSOs) to cope with the uncertainty and variation of the wind power and its forecasts. A chance-constrained economic dispatch (ED) model for the wind-thermal-energy storage system (WTESS) is developed in this paper. An optimization model with the wind power and the energy storage system (ESS) is first established with the consideration of both the economic benefits of the system and less wind curtailments. The original wind power generation is processed by the ESS to obtain the final wind power output generation (FWPG). A Gaussian mixture model (GMM) distribution is adopted to characterize the probabilistic and cumulative distribution functions with an analytical expression. Then, a chance-constrained ED model integrated by the wind-energy storage system (W-ESS) is developed by considering both the overestimation costs an... [more]
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