scholarly journals Optimal Operation of Multiple Energy System Based on Multi-Objective Theory and Grey Theory

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 68
Author(s):  
Bo Hu ◽  
Nan Wang ◽  
Zaiming Yu ◽  
Yunqing Cao ◽  
Dongsheng Yang ◽  
...  
Keyword(s):  
Environmental Pollution ◽  
Energy Management ◽  
Manufacturing Industry ◽  
Energy System ◽  
Optimal Operation ◽  
Operating Conditions ◽  
Maintenance Cost ◽  
Grey Theory ◽  
Multi Objective ◽  
Electricity Cost

The manufacturing industry consumes electricity and natural gas to provide the power and heat required for manufacturing. Additionally, large amounts of electric energy and heat energy are used, and the electricity cost, amount of environmental pollution, and equipment maintenance cost are high. Thus, optimizing the management of equipment with new energy is important to satisfy the load demand from the system. This paper formulates the scheduling problem of these multiple energy systems as a multi-objective linear regression model (MLRM), and an energy management system is designed focusing on the economy and on greenhouse gas emissions. Furthermore, a variety of optimization objectives and constraints are proposed to make the energy management scheme more practical. Then, grey theory is combined with the common MLRM to accurately represent the uncertainty in the system and to make the model better reflect the actual situation. This paper takes load fluctuation, total grid operation cost, and environmental pollution value as reference standards to measure the effect of the gray optimization algorithm. Lastly, the model is applied to optimize the energy supply plan and its performance is demonstrated using numerical examples. The verification results meet the optimized operating conditions of the multi-energy microgrid system.

scholarly journals A Novel Energy Management Strategy for a Ship’s Hybrid Solar Energy Generation System Using a Particle Swarm Optimization Algorithm

Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1380 ◽  
Author(s):  
Rui Yang ◽  
Yupeng Yuan ◽  
Rushun Ying ◽  
Boyang Shen ◽  
Teng Long
Keyword(s):  
Solar Energy ◽  
Energy Management ◽  
Optimization Algorithm ◽  
Management Strategy ◽  
Energy System ◽  
Generation System ◽  
Energy Management Strategy ◽  
Swarm Optimization ◽  
Multi Objective ◽  
New Energy

Due to the pressures caused by the energy crisis, environmental pollution, and international regulations, the largest ship-producing nations are exploring renewable resources, such as wind power, solar energy, and fuel cells to save energy and develop more environmentally-friendly ships. Solar energy has recently attracted a great deal of attention from both academics and practitioners; furthermore, the optimization of energy management has become a research topic of great interest. This paper takes a solar-diesel hybrid ship with 5000 car spaces as its research object. Then, following testing on this ship, experimental data were obtained, a multi-objective optimization model related to the ship’s fuel economy and diesel generator’s efficiency was established, and a partial swarm optimization algorithm was used to solve a multi-objective problem. The results show that the optimized energy management strategy for a hybrid energy system should be tested under different electrical loads. Moreover, the hybrid system’s economy should be taken into account when the ship’s power load is high, and the output power from the new energy generation system should be increased as much as possible. Finally, the diesel generators’ efficiency should be taken into consideration when the ship’s electrical load is low, and the injection power of the new energy system should be reduced appropriately.

scholarly journals An Efficient Technique-Based Distributed Energy Management for Hybrid MG System: A Hybrid SBLA-CGO Technique

2021 ◽  
Author(s):  
T Logeswaran ◽  
Francis H Shajin ◽  
Paulthurai Rajesh
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Energy Demand ◽  
Present Method ◽  
Perfect Match ◽  
Energy System ◽  
Photovoltaic System ◽  
Present System ◽  
Prediction Errors ◽  
Electricity Cost

Abstract This manuscript presents an optimal energy management on microgrid (MG) connected to the grid that chooses the energy scheduling based on the proposed method. The present method is the joint implementation of the Side-Blotched Lizard Algorithm (SBLA) and the Chaos Game Optimization Algorithm (CGO) and hence it is named as SBLA-CGO method. Here, the MG system contains a photovoltaic system (PV), wind turbine (WT), battery storage (BS) and fuel cell (FC). Constantly, the necessary load demand of MG system connected to the grid is measured with SBLA method. The CGO increases the perfect match of MG with the expected load requirement. Moreover, renewable energy forecasting errors are evaluated twice by MG energy management for minimizing the control. Through the operation of MG schedule of several RES to decrease the electricity cost using the first method. Balancing the energy flow and minimize the effects of prediction errors according to the rule presented as planned power reference is second method. The main aim of the present method is evaluated with connection of fuel cost, the variation of energy per hour of the electrical grid, the cost of operation and maintenance of MG system connected to the network. According to RES, the energy demand and SOC of the storage elements are the conditions. Renewable energy system units use batteries as energy sources to allow them to operate continuously on stable and sustainable power generation. The analysis of the present method is analyzed by comparing with the other systems. The results of the comparison assess the strength of the present system and confirm their potential for solving the issues.

scholarly journals Holistic Simulation Approach for Optimal Operation of Smart Integrated Energy Systems under Consideration of Resilience, Economics and Sustainability

2021 ◽  
Vol 6 (11) ◽  
pp. 150
Author(s):  
Kai Hoth ◽  
Tom Steffen ◽  
Béla Wiegel ◽  
Amine Youssfi ◽  
Davood Babazadeh ◽  
...  
Keyword(s):  
Energy Management ◽  
Dynamic Models ◽  
Energy Systems ◽  
Energy System ◽  
Optimal Operation ◽  
Distributed Resources ◽  
Holistic Model ◽  
Future System ◽  
Integrated Energy System ◽  
Operational Concept

The intermittent energy supply from distributed resources and the coupling of different energy and application sectors play an important role for future energy systems. Novel operational concepts require the use of widespread and reliable Information and Communication Technology (ICT). This paper presents the approach of a research project that focuses on the development of an innovative operational concept for a Smart Integrated Energy System (SIES), which consists of a physical architecture, ICT and energy management strategies. The cellular approach provides the architecture of the physical system in combination with Transactive Control (TC) as the system’s energy management framework. Independent dynamic models for each component, the physical and digital system, operational management and market are suggested and combined in a newly introduced co-simulation platform to create a holistic model of the integrated energy system. To verify the effectiveness of the operational concept, energy system scenarios are derived and evaluation criteria are suggested which can be employed to evaluate the future system operations.

Flexibility of Organic Thermoelectric Material for Photovoltaic Solar Energy Management and Conversion

2018 ◽  
Vol 11 (1) ◽  
pp. 44-54
Author(s):  
Emmanuel O.B. Ogedengbe ◽  
Omokehinde Igbekoyi ◽  
Abideen Bakare ◽  
Olufemi J. Alonge ◽  
Manasseh B. Shitta ◽  
...  
Keyword(s):  
Solar Energy ◽  
Energy Management ◽  
Organic Solar Cells ◽  
Energy Demand ◽  
Energy System ◽  
Building Envelope ◽  
Operating Conditions ◽  
Building Automation ◽  
Power Performance ◽  
Automation Systems

Objective:The flexibility on a design maneuvering of building automation systems with the integration of organic solar cells is investigated.Methods:The energy demand load of the Engineering Lecture Theatre (ELT) at the University of Lagos is analyzed and parametric studies of the heat and charge transport within aMimosa pudicabased solar wafer are conducted, along with the modelling of a network of microchannels. A walk-through energy audit of all the devices that are installed or operated within the ELT and the thermophysical properties of the building envelope are considered, with the aim of satisfying the ASHRAE standard for thermal comfort and indoor air quality. A two-dimensional finite volume formulation of the heat and charge transfers within the boundaries of the flexible laminate and the organic extract is utilized.Result:Parametric analysis of the flow phenomenon and temperature distribution, especially across the wafer, at various operating conditions helps to determine significant design criteria, and assists in confirming the feasible power performance of the organic solar cell for building energy management.Conclusion:The results are anticipated for the design of reliable building automation systems for effective demand side monitoring, and for estimation of the economic viability of a proposed development of hybrid organic-inorganic based solar energy system for independent power generation within the Faculty of Engineering.

scholarly journals Optimal Maintenance Thresholds to Perform Preventive Actions by Using Multi-Objective Evolutionary Algorithms

2019 ◽  
Vol 9 (15) ◽  
pp. 3068 ◽  
Author(s):  
Aitor Goti ◽  
Aitor Oyarbide-Zubillaga ◽  
Elisabete Alberdi ◽  
Ana Sanchez ◽  
Pablo Garcia-Bringas
Keyword(s):  
Preventive Maintenance ◽  
Manufacturing Industry ◽  
Industrial Revolution ◽  
Preventive Intervention ◽  
Cost Benefit ◽  
Economic Consequences ◽  
Maintenance Cost ◽  
Optimization Approach ◽  
Multi Objective ◽  
Optimal Maintenance

Maintenance has always been a key activity in the manufacturing industry because of its economic consequences. Nowadays, its importance is increasing thanks to the “Industry 4.0” or “fourth industrial revolution”. There are more and more complex systems to maintain, and maintenance management must gain efficiency and effectiveness in order to keep all these devices in proper conditions. Within maintenance, Condition-Based Maintenance (CBM) programs can provide significant advantages, even though often these programs are complex to manage and understand. For this reason, several research papers propose approaches that are as simple as possible and can be understood by users and modified by experts. In this context, this paper focuses on CBM optimization in an industrial environment, with the objective of determining the optimal values of preventive intervention limits for equipment under corrective and preventive maintenance cost criteria. In this work, a cost-benefit mathematical model is developed. It considers the evolution in quality and production speed, along with condition based, corrective and preventive maintenance. The cost-benefit optimization is performed using a Multi-Objective Evolutionary Algorithm. Both the model and the optimization approach are applied to an industrial case.

scholarly journals Optimal Operating Schedule for Energy Storage System: Focusing on Efficient Energy Management for Microgrid

Processes ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 80 ◽  
Author(s):  
Sooyoung Jung ◽  
Yong Tae Yoon
Keyword(s):  
Energy Storage ◽  
Energy Management ◽  
Power Grid ◽  
Optimal Operation ◽  
Operating Conditions ◽  
Mixed Integer ◽  
Small Scale ◽  
Basic Operation ◽  
Electricity Use ◽  
Operation Schedule

A microgrid is a group of many small-scale distributed energy resources, such as solar/wind energy sources, diesel generators, energy storage units, and electric loads. As a small-scale power grid, it can be operated independently or within an existing power grid(s). The microgrid energy management system is a system that controls these components to achieve optimized operation in terms of price by reducing costs and maximizing efficiency in energy consumption. A post-Industry-4.0 consumer requires an optimal design and control of energy storage based on a demand forecast, using big data to stably supply clean, new, and renewable energy when necessary while maintaining a consistent level of quality. Thus, this study focused on software technology through which an optimized operation schedule for energy storage in a microgrid is derived. This energy storage operation schedule minimizes the costs involved in electricity use. For this, an optimization technique is used that sets an objective function representing the information and costs pertaining to electricity use, while minimizing its value by using Mixed Integer Linear Programming or a Genetic Algorithm. The main feature of the software is that an optimal operation schedule derivation function has been implemented with MATLAB for the following circumstances: when the basic operation rules are applied, when operating with another grid, when the external operating conditions are applied, and when the internal operating conditions are applied.

scholarly journals Optimal Multi-Operation Energy Management in Smart Microgrids in the Presence of RESs Based on Multi-Objective Improved DE Algorithm: Cost-Emission Based Optimization

2021 ◽  
Vol 11 (8) ◽  
pp. 3661
Author(s):  
Mohammad Ghiasi ◽  
Taher Niknam ◽  
Moslem Dehghani ◽  
Pierluigi Siano ◽  
Hassan Haes Alhelou ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Renewable Energy Sources ◽  
Environmental Pollutant ◽  
Optimal Operation ◽  
Energy Sources ◽  
Pollution Effects ◽  
Multi Objective ◽  
Operational Energy ◽  
The Impact

Today, in various leading power utilities in developing countries, achieving optimal operational energy management and planning, taking into account the costs reduction of generation, transmission and distribution of electricity, and also reducing the emission of an environmental pollutant becomes more and more important. Optimal use of renewable energy sources (RESs) is an effective way to achieve these goals. In this regard, in this research article, an improved multi-objective differential evolutionary (IMODE) optimization algorithm is suggested and performed to dispatch electricity generations in a smart microgrid (MG) system, taking into account economy and emission as competitive issues. In this paper, a nonlinear equation of multi-objective optimization issue with various equality and inequality limitations is formulated in order to lower the total operational costs of the MG considering environmental pollution effects simultaneously. In order to address the issue of optimal operation of the MG in single-objective and multi-objective forms, an intelligent method according to the improved differential evolutionary (IDE) optimization is utilized and performed and the proposed algorithm is implemented on different problems. First, it is assumed that there is no limit to the exchange of power overhead, and secondly, the limitation of power exchange with the upstream grid is considered. In multi-objective mode, these two modes are also considered. In order to show the impact of renewable energy on the cost, in the third part of the simulations, the operation is solved with maximum participation of renewable energy sources. In the final section, the sensitivity analysis on the number of populations in this problem is performed. The obtained results of the simulation are compared to differential evolutionary (DE) and particle swarm optimization (PSO) techniques. The effectiveness of the suggested multi-operational energy management method is confirmed by applying a study case system.

Sign in / Sign up

Export Citation Format

Share Document