scholarly journals A Competitive Swarm Optimizer-Based Technoeconomic Optimization with Appliance Scheduling in Domestic PV-Battery Hybrid Systems

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Bo Wang ◽  
Yanjing Li ◽  
Fei Yang ◽  
Xiaohua Xia
Keyword(s):  
User Satisfaction ◽  
Large Scale ◽  
Energy System ◽  
Mixed Integer ◽  
Specific Power ◽  
Objective Functions ◽  
Hybrid Energy ◽  
Decision Variables ◽  
Time Scheduling ◽  
Numerical Solver

A technoeconomic optimization problem for a domestic grid-connected PV-battery hybrid energy system is investigated. It incorporates the appliance time scheduling with appliance-specific power dispatch. The optimization is aimed at minimizing energy cost, maximizing renewable energy penetration, and increasing user satisfaction over a finite horizon. Nonlinear objective functions and constraints, as well as discrete and continuous decision variables, are involved. To solve the proposed mixed-integer nonlinear programming problem at a large scale, a competitive swarm optimizer-based numerical solver is designed and employed. The effectiveness of the proposed approach is verified by simulation results.

scholarly journals Hybrid Energy Network Management: Simulation and Optimisation of Large Scale PV Coupled with Hydrogen Generation

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1734
Author(s):  
Marco Cerchio ◽  
Francesco Gullí ◽  
Maurizio Repetto ◽  
Antonino Sanfilippo
Keyword(s):  
Large Scale ◽  
Hydrogen Generation ◽  
Renewable Energy Sources ◽  
Supply And Demand ◽  
Primary Source ◽  
Electrical Energy ◽  
Energy System ◽  
Mixed Integer ◽  
Electrical Networks ◽  
Hybrid Energy

The power production of electrical Renewable Energy Sources (RES), mainly PV and wind energy, is affected by their primary source of energy: solar radiation value or wind strength. Electrical networks with a large share of these sources must manage temporal imbalances of supply and demand. Hybrid Energy Networks (HEN) can mitigate the effects of this unbalancing by providing a connection between the electricity grid and and other energy vectors such as heat, gas or hydrogen. These couplings can activate synergies among networks that, all together, increase the share of renewable sources helping a decarbonisation of the energy sector. As the energy system becomes more and more complex, the need for simulation and optimisation tools increases. Mathematical optimisation can be used to look for a management strategy maximising a specific target, for instance economical, i.e. the minimum management cost, or environmental as the best exploitation or RES. The present work presents a Mixed Integer Linear Programming (MILP) optimisation procedure that looks for the minimum running cost of a system made up by a large-scale PV plant where hydrogen production, storage and conversion to electricity is present. In addition, a connection to a natural gas grid where hydrogen can be sold is considered. Different running strategies are studied and analysed as functions of electricity prices and other forms of electrical energy exploitation.

scholarly journals A Multi-objective Scheduling Optimization Model for Hybrid Energy System Connected with Wind-Photovoltaic-Conventional Gas Turbines, CHP Considering Heating Storage Mechanism

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 425 ◽  
Author(s):  
Yao Wang ◽  
Yan Lu ◽  
Liwei Ju ◽  
Ting Wang ◽  
Qingkun Tan ◽  
...  
Keyword(s):  
Demand Response ◽  
Gas Turbines ◽  
Energy System ◽  
Objective Functions ◽  
Distributed Energy ◽  
Operating Income ◽  
Hybrid Energy ◽  
Multi Objective ◽  
Load Demand ◽  
Load Fluctuation

In order to meet the user’s electricity demand and make full use of distributed energy, a hybrid energy system (HES) was proposed and designed, including wind turbines (WTs), photovoltaic (PV) power generation, conventional gas turbines (CGTs), incentive-based demand response (IBDR), combined heat and power (CHP) and regenerative electric (RE) boilers. Then, the collaborative operation problem of HES is discussed. First, the paper describes the HES’ basic structure and presents the output model of power sources and heating sources. Next, the maximum operating income and minimum load fluctuation are taken as the objective function, and a multi-objective model of HES scheduling is proposed. Then an algorithm for solving the model is proposed that comprises two steps: processing the objective functions and constraints into linear equations and determining the optimal weight of the objective functions. The selected simulation system is a microgrid located on an eastern island of China to comparatively analyze the influence of RE-heating storage (RE-HS) and price-based demand response (PBDR) on HES operation in relation to four cases. By analyzing the results, the following three conclusions are drawn: (1) HES can comprehensively utilize a variety of distributed energy sources to meet load demand. In particular, RE technology can convert the abandoned energy of WT and PV into heat during the valley load time, to meet the load demand combined with CHP; (2) The proposed multi-objective scheduling model of HES operation not only considers the maximum operating income but also considers the minimum load fluctuation, thus achieving the optimal balancing operation; (3) RE-HS and PBDR have a synergistic optimization effect, and when RE-HS and PBDR are both applied, an HES can achieve optimal operation results. Overall, the proposed decision method is highly effective and applicable, and decision makers could utilize this method to design an optimal HES operation strategy according to their own actual conditions.

scholarly journals Study of Modeling of Hybrid Energy System for Optimum Power Extraction from the System to the Grid

2021 ◽  
Vol 7 (2) ◽  
pp. 19-24
Author(s):  
Ashish Srivastava ◽  
Dr. M S Dash
Keyword(s):  
Power Generation ◽  
Hybrid System ◽  
Large Scale ◽  
Energy System ◽  
Stable Operation ◽  
Hybrid Energy ◽  
Power Extraction ◽  
Energy Demands ◽  
Attractive Option ◽  
Micro Grid

With the growing demand of electricity, deployment of micro grid is becoming an attractive option to meet the energy demands. At present, large-scale wind/solar hybrid system is of great potential for development. The large-scale wind/solar hybrid system is of higher reliability compared with wind power generation alone and solar power generation alone However, a grid-connected micro grid suffers from critical stability problems during a power grid failure. For stable operation of the micro grid during a grid failure. In this paper, the transition stability of the micro grid is examined during a power failure

scholarly journals A comparative study of many-objective optimizers on large-scale many-objective software clustering problems

2021 ◽  
Author(s):  
Amarjeet Prajapati
Keyword(s):  
Large Scale ◽  
Optimization Problems ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Software Clustering ◽  
Multi Objective ◽  
The Past ◽  
Decision Variables ◽  
Clustering Problems ◽  
Special Case

AbstractOver the past 2 decades, several multi-objective optimizers (MOOs) have been proposed to address the different aspects of multi-objective optimization problems (MOPs). Unfortunately, it has been observed that many of MOOs experiences performance degradation when applied over MOPs having a large number of decision variables and objective functions. Specially, the performance of MOOs rapidly decreases when the number of decision variables and objective functions increases by more than a hundred and three, respectively. To address the challenges caused by such special case of MOPs, some large-scale multi-objective optimization optimizers (L-MuOOs) and large-scale many-objective optimization optimizers (L-MaOOs) have been developed in the literature. Even after vast development in the direction of L-MuOOs and L-MaOOs, the supremacy of these optimizers has not been tested on real-world optimization problems containing a large number of decision variables and objectives such as large-scale many-objective software clustering problems (L-MaSCPs). In this study, the performance of nine L-MuOOs and L-MaOOs (i.e., S3-CMA-ES, LMOSCO, LSMOF, LMEA, IDMOPSO, ADC-MaOO, NSGA-III, H-RVEA, and DREA) is evaluated and compared over five L-MaSCPs in terms of IGD, Hypervolume, and MQ metrics. The experimentation results show that the S3-CMA-ES and LMOSCO perform better compared to the LSMOF, LMEA, IDMOPSO, ADC-MaOO, NSGA-III, H-RVEA, and DREA in most of the cases. The LSMOF, LMEA, IDMOPSO, ADC-MaOO, NSGA-III, and DREA, are the average performer, and H-RVEA is the worst performer.

Feasibility study of on/off grid large-scale PV/WT/WEC hybrid energy system in coastal cities: A case-based research

2020 ◽  
Vol 162 ◽  
pp. 2075-2095 ◽  
Author(s):  
Mohammad Hossein Jahangir ◽  
Samaneh Fakouriyan ◽  
Mohammad Amin Vaziri Rad ◽  
Hassan Dehghan
Keyword(s):  
Feasibility Study ◽  
Large Scale ◽  
Energy System ◽  
Hybrid Energy System ◽  
Hybrid Energy ◽  
Coastal Cities ◽  
Case Based

Optimal Test Assembly in Practice

2013 ◽  
Vol 221 (3) ◽  
pp. 190-200 ◽  
Author(s):  
Jörg-Tobias Kuhn ◽  
Thomas Kiefer
Keyword(s):  
Particle Physics ◽  
Large Scale ◽  
Block Design ◽  
Linear Optimization ◽  
Mixed Integer ◽  
Optimal Test ◽  
Automated Test Assembly ◽  
Test Assembly ◽  
Block Level ◽  
Mixed Integer Linear Optimization

Several techniques have been developed in recent years to generate optimal large-scale assessments (LSAs) of student achievement. These techniques often represent a blend of procedures from such diverse fields as experimental design, combinatorial optimization, particle physics, or neural networks. However, despite the theoretical advances in the field, there still exists a surprising scarcity of well-documented test designs in which all factors that have guided design decisions are explicitly and clearly communicated. This paper therefore has two goals. First, a brief summary of relevant key terms, as well as experimental designs and automated test assembly routines in LSA, is given. Second, conceptual and methodological steps in designing the assessment of the Austrian educational standards in mathematics are described in detail. The test design was generated using a two-step procedure, starting at the item block level and continuing at the item level. Initially, a partially balanced incomplete item block design was generated using simulated annealing, whereas in a second step, items were assigned to the item blocks using mixed-integer linear optimization in combination with a shadow-test approach.

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