The Research of Microgrid Optimized Dispatching Method Based on MEA

2014 ◽  
Vol 494-495 ◽  
pp. 1841-1844
Author(s):  
Bao Yi Wang ◽  
Chen Wei ◽  
Shao Min Zhang
Keyword(s):  
Large Scale ◽  
Scheduling Algorithm ◽  
Power Grid ◽  
Renewable Energy Sources ◽  
Energy Resource ◽  
Mixed Integer ◽  
Programming Algorithm ◽  
Storage Element ◽  
Electric Cars ◽  
Operation Control

Integration of large scale renewable energy sources and electric cars into power grid will bring new opportunities and challenges to the operation, control of the power grid and the power market .The microgrid , which integration the distributed generation systems, energy storage element and loads ,has been seen as one effective way to solve the problems. This paper proposed a MEA-based scheduling algorithm, and studied a microgrid that contains 32 nodes and 50 electric cars. Both the MEA algorithm and mixed integer nonlinear programming algorithm (MINLP) can solve the energy resource scheduling problem,but the results of our simulation shows that the total cost of MEA is higher than that of the MINLP,but there is a significant improvement in the efficiency of execution.The results shows that we can use MEA to achieve optimal scheduling,it also verify the effectiveness of the algorithm.

scholarly journals Stochastic Mixed-Integer Programming (SMIP)-Based Distributed Energy Resource Allocation Method for Virtual Power Plants

Energies ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 67
Author(s):  
Rakkyung Ko ◽  
Sung-Kwan Joo
Keyword(s):  
Renewable Energy ◽  
Power Plants ◽  
Renewable Energy Sources ◽  
Energy Resource ◽  
Mixed Integer ◽  
Virtual Power ◽  
Distributed Energy ◽  
Distributed Energy Resource ◽  
Stochastic Mixed Integer Programming ◽  
Virtual Power Plants

Virtual power plants (VPPs) have been widely researched to handle the unpredictability and variable nature of renewable energy sources. The distributed energy resources are aggregated to form into a virtual power plant and operate as a single generator from the perspective of a system operator. Power system operators often utilize the incentives to operate virtual power plants in desired ways. To maximize the revenue of virtual power plant operators, including its incentives, an optimal portfolio needs to be identified, because each renewable energy source has a different generation pattern. This study proposes a stochastic mixed-integer programming based distributed energy resource allocation method. The proposed method attempts to maximize the revenue of VPP operators considering market incentives. Furthermore, the uncertainty in the generation pattern of renewable energy sources is considered by the stochastic approach. Numerical results show the effectiveness of the proposed method.

scholarly journals Grid Modernization - Integration of Storage

2016 ◽  
Vol 9 (2) ◽  
Author(s):  
Z. Islifo
Keyword(s):  
Energy Storage ◽  
Large Scale ◽  
Power Grid ◽  
Renewable Energy Sources ◽  
Customer Participation ◽  
Energy Sources ◽  
Electric Power Grid ◽  
Time Flow ◽  
Storage Technologies ◽  
Vanadium Redox

The existing electric power grid is reliable enough to meet everyday needs of U.S. electricity users. However, the grid needs major infrastructure upgrades to meet the rising demands for a reliable, resilient, and secure electricity delivery. Drivers to modernize the grid include increased demand for clean sources of energy, growing number of renewable energy sources on the grid and customer participation in power generation. Smart grid technologies are critical for monitoring, managing and controlling the power grid. Energy storage introduces an important new dimension on the grid, the ability to store electricity at one time and release the stored electricity for use at another time. Flow batteries are one type of energy storage technologies that are well suited for large-scale utility application on the grid. Currently, vanadium redox ow batteries are the most common used utility-scaled ow batteries.

scholarly journals Minimum Frequency and Voltage Stability Constrained Unit Commitment for AC/DC Transmission Systems

2019 ◽  
Vol 9 (16) ◽  
pp. 3412 ◽  
Author(s):  
Ningyu Zhang ◽  
Qian Zhou ◽  
Haoming Hu
Keyword(s):  
Direct Current ◽  
Voltage Stability ◽  
Benders Decomposition ◽  
Unit Commitment ◽  
Power Grid ◽  
Eastern China ◽  
Normal Operation ◽  
Mixed Integer ◽  
Programming Algorithm ◽  
Frequency Regulation

An increased use of the high-voltage direct current (HVDC) technologies can have important effects on frequency performance and voltage stability of the receiving-end grid during normal operation as well as during blocking failure. The main reasons are the inherent characteristics of the HVDC such as its much larger capacity than thermal plants and lack of voltage supporting ability to the alternating current (AC) grid. These has led to new challenges for AC/direct current (DC) power grid operators in terms of ensuring power system security. To address these challenges, a unit commitment (UC) of the receiving-end in the AC/DC hybrid grid is presented in this paper. In the proposed model, primary frequency modulation constraints are added to provide sufficient capacity for HVDC blocking. Besides, grid security constraint after secondary frequency regulation is also considered because HVDC blocking failure would cause large range power transfer and transmission lines overload. Meanwhile, voltage stability constraints are employed to guarantee enough voltage supporting capacity from thermal plants at the HVDC feed-in area. Based on the characteristics of the model, Benders decomposition and mixed integer programming algorithm are used to get the optimal transmission power of the HVDC and schedule of thermal units. The study is done by considering the IEEE-39 and Jiangsu power grid in eastern China, containing two HVDC transmission projections respectively. The results are also validated by simulation of different HVDC blocking failure scenarios.

scholarly journals Charging Network Planning for Electric Bus Cities: A Case Study of Shenzhen, China

2019 ◽  
Vol 11 (17) ◽  
pp. 4713 ◽  
Author(s):  
Yuping Lin ◽  
Kai Zhang ◽  
Zuo-Jun Max Shen ◽  
Lixin Miao
Keyword(s):  
Large Scale ◽  
Programming Model ◽  
Cost Minimization ◽  
Transportation Network ◽  
Power Grid ◽  
Mixed Integer ◽  
Charging Infrastructure ◽  
Second Order Cone ◽  
Charging Stations

In 2017, Shenzhen replaced all its buses with battery e-buses (electric buses) and has become the first all-e-bus city in the world. Systematic planning of the supporting charging infrastructure for the electrified bus transportation system is required. Considering the number of city e-buses and the land scarcity, large-scale bus charging stations were preferred and adopted by the city. Compared with other EVs (electric vehicles), e-buses have operational tasks and different charging behavior. Since large-scale electricity-consuming stations will result in an intense burden on the power grid, it is necessary to consider both the transportation network and the power grid when planning the charging infrastructure. A cost-minimization model to jointly determine the deployment of bus charging stations and a grid connection scheme was put forward, which is essentially a three-fold assignment model. The problem was formulated as a mixed-integer second-order cone programming model, and a “No R” algorithm was proposed to improve the computational speed further. Computational studies, including a case study of Shenzhen, were implemented and the impacts of EV technology advancements on the cost and the infrastructure layout were also investigated.

A cogeneration scheme with biogas and improvement of frequency stability using inertia based control in AC microgrid

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Subhendu Bikash Santra ◽  
Babatunde Tolu Ogungbe
Keyword(s):  
Large Scale ◽  
Frequency Control ◽  
Power Grid ◽  
Renewable Energy Sources ◽  
Rate Of Change ◽  
Biogas Plant ◽  
Frequency Change ◽  
Power Requirement ◽  
Frequency Changes ◽  
Ac Microgrid

Abstract Currently, penetration of the renewable energy sources (RES) like solar photovoltaic (PV) panels, wind turbine-based plants is increasing in the conventional power grid to combat pollution, global warming, and to enhance energy sustainability. Fast power electronic converters are necessary to extract power from these sources which do not have any inertia. When more renewable sources are connected to the power grid, it reduces the effective system inertia which results in unacceptable grid frequency changes for any transient. This leads to frequent tripping, cascading fault, and instability of the overall system which can create large-scale blackouts. This work is related to the generation of physical inertia through the biogas plant and emulates inertia from the dc-link capacitor to control the rate of change of frequency (RoCoF) under abrupt load change. The stored energy in a biogas plant and dc-link capacitor in an AC microgrid (MG) can support momentary power requirement which improves the transient performance of grid frequency under unavailability of PV power. A storage system can help to compensate for abrupt frequency change during transient but due to its higher cost and relatively lesser lifetime, these systems can’t be relied upon in the long run. The proposed scheme of cogeneration and frequency control can provide better performance which is simulated in MATLAB 2013 (b). The control system is implemented in hardware using NI-cRiO 9082 in 500 W AC MG which shows 53.57% improvement in RoCoF which complies with the requirement of IEEE/IEC 60255-118-1.

scholarly journals Modeling a Large-Scale Battery Energy Storage System for Power Grid Application Analysis

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3312 ◽  
Author(s):  
Giuliano Rancilio ◽  
Alexandre Lucas ◽  
Evangelos Kotsakis ◽  
Gianluca Fulli ◽  
Marco Merlo ◽  
...  
Keyword(s):  
Energy Storage ◽  
Large Scale ◽  
Numerical Models ◽  
Power Grid ◽  
Renewable Energy Sources ◽  
Test Protocol ◽  
Standard Equipment ◽  
Battery Energy Storage ◽  
Experimental Campaign ◽  
Battery Energy

The interest in modeling the operation of large-scale battery energy storage systems (BESS) for analyzing power grid applications is rising. This is due to the increasing storage capacity installed in power systems for providing ancillary services and supporting nonprogrammable renewable energy sources (RES). BESS numerical models suitable for grid-connected applications must offer a trade-off, keeping a high accuracy even with limited computational effort. Moreover, they are asked to be viable in modeling for real-life equipment, and not just accurate in the simulation of the electrochemical section. The aim of this study is to develop a numerical model for the analysis of the grid-connected BESS operation; the main goal of the proposal is to have a test protocol based on standard equipment and just based on charge/discharge tests, i.e., a procedure viable for a BESS owner without theoretical skills in electrochemistry or lab procedures, and not requiring the ability to disassemble the BESS in order to test each individual component. The BESS model developed is characterized by an experimental campaign. The test procedure itself is framed in the context of this study and adopted for the experimental campaign on a commercial large-scale BESS. Once the model is characterized by the experimental parameters, it undergoes the verification and validation process by testing its accuracy in simulating the provision of frequency regulation. A case study is presented for the sake of presenting a potential application of the model. The procedure developed and validated is replicable in any other facility, due to the low complexity of the proposed experimental set. This could help stakeholders to accurately simulate several layouts of network services.

scholarly journals Optimizing Painting Sequence Scheduling Based on Adaptive Partheno-Genetic Algorithm

Processes ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1714
Author(s):  
Jun Yang ◽  
Tong Sun ◽  
Xiuxiang Huang ◽  
Ke Peng ◽  
Zhongxiang Chen ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Programming Problem ◽  
Large Scale ◽  
Scheduling Algorithm ◽  
Real Life ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Rule Based ◽  
Multi Objective ◽  
Color Changes

In this paper, we formulate and solve a novel real-life large-scale automotive parts paint shop scheduling problem, which contains color arrangement restrictions, part arrangement restrictions, bracket restrictions, and multi-objectives. Based on these restrictions, we construct exact constraints and two objective functions to form a large-scale multi-objective mixed-integer linear programming problem. To reduce this scheduling problem’s complexity, we converted the multi-objective model into a multi-level objective programming problem by combining the rule-based scheduling algorithm and the adaptive Partheno-Genetic algorithm. The rule-based scheduling algorithm is adopted to optimize color changes horizontally and bracket replacements vertically. The adaptive Partheno-Genetic algorithm is designed to optimize production based on the rule-based scheduling algorithm. Finally, we apply the model to the actual optimization problem that contained 829,684 variables and 137,319 constraints, and solved this problem by Python. The proposed method solves the optimal solution, consuming 575 s.

scholarly journals Grid-Aware Layout of Photovoltaic Panels in Sustainable Building Energy Systems

2021 ◽  
Vol 8 ◽  
Author(s):  
Luise Middelhauve ◽  
Francesco Baldi ◽  
Paul Stadler ◽  
François Maréchal
Keyword(s):  
Energy Demand ◽  
Power Grid ◽  
Renewable Energy Sources ◽  
Energy Systems ◽  
Energy Generation ◽  
Building Energy ◽  
Solar Irradiation ◽  
Mixed Integer ◽  
Photovoltaic Panels ◽  
Building Energy Systems

In the context of increasing concern for anthropogenic CO2 emissions, the residential building sector still represents a major contributor to energy demand. The integration of renewable energy sources, and particularly of photovoltaic (PV) panels, is becoming an increasingly widespread solution for reducing the carbon footprint of building energy systems (BES). However, the volatility of the energy generation and its mismatch with the typical demand patterns are cause for concern, particularly from the viewpoint of the management of the power grid. This paper aims to show the influence of the orientation of photovoltaic panels in designing new BES and to provide support to the decision making process of optimal PV placing. The subject is addressed with a mixed integer linear optimization problem, with costs as objectives and the installation, tilt, and azimuth of PV panels as the main decision variables. Compared with existing BES optimization approaches reported in literature, the contribution of PV panels is modeled in more detail, including a more accurate solar irradiation model and the shading effect among panels. Compared with existing studies in PV modeling, the interaction between the PV panels and the remaining units of the BES, including the effects of optimal, scheduling is considered. The study is based on data from a residential district with 40 buildings in western Switzerland. The results confirm the relevant influence of PV panels’ azimuth and tilt on the performance of BES. Whereas south-orientation remains the most preferred choice, west-orientationed panels better match the demand when compared with east-orientationed panels. Apart from the benefits for individual buildings, an appropriate choice of orientation was shown to benefit the grid: rotating the panels 20° westwards can, together with an appropriate scheduling of the BES, reduce the peak power of the exchange with the power grid by 50% while increasing total cost by only 8.3%. Including the more detailed modeling of the PV energy generation demonstrated that assuming horizontal surfaces can lead to inaccuracies of up to 20% when calculating operating expenses and electricity generated, particularly for high levels of PV penetration.

Sign in / Sign up

Export Citation Format

Share Document