scholarly journals Multi-Objective Optimal Scheduling of a Hybrid Ferry with Shore-to-Ship Power Supply Considering Energy Storage Degradation

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 849 ◽  
Author(s):  
Kyaw Hein ◽  
Xu Yan ◽  
Gary Wilson
Keyword(s):  
Energy Storage ◽  
Power Supply ◽  
Solution Space ◽  
Optimal Operation ◽  
Depth Information ◽  
Multi Objective ◽  
Conflicting Objectives ◽  
Forecast Data ◽  
Operation Scheduling

To improve the operation efficiency and reduce the emission of a solar power integrated hybrid ferry with shore-to-ship (S2S) power supply, a two-stage multi-objective optimal operation scheduling method is proposed. It aims to optimize the two conflicting objectives, operation cost (fuel cost of diesel generators (DGs), carbon dioxide (CO2) emission tax and S2S power exchange) and energy storage (ES/ESS) degradation cost, based on the preference of the vessel operator and solar photovoltaic (PV) power output. For the day-ahead optimization, interval forecast data of the PV is used to map the solution space of the objectives with different sets of weight assignment. The solution space from the day-ahead optimization is used as a guide to determine the operating point of the hour-ahead optimization. As for the hour-ahead scheduling, more accurate short-lead time forecast data is used for the optimal operation scheduling. A detailed case study is carried out and the result indicates the operation flexibility improvement of the hybrid vessel. The case study also provides more in-depth information on the dispatching scheme and it is especially important if there are conflicting objectives in the optimization model.

scholarly journals Optimal Sizing Procedure for Electric Vehicle Supply Infrastructure Based on DC Microgrid with Station Commitment

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1901 ◽  
Author(s):  
Benedetto Aluisio ◽  
Maria Dicorato ◽  
Imma Ferrini ◽  
Giuseppe Forte ◽  
Roberto Sbrizzai ◽  
...  
Keyword(s):  
Energy Storage ◽  
Electric Vehicles ◽  
Power Supply ◽  
Energy Exchange ◽  
Optimal Operation ◽  
Dc Microgrid ◽  
Photovoltaic Panels ◽  
Specific Approach ◽  
Definition Of

The diffusion of electric vehicles (EVs) can be sustained by the presence of integrated solutions offering parking and clean power supply. The recourse to DC systems allows better integration of EV bidirectional energy exchange, photovoltaic panels, and energy storage. In this paper, a methodology for optimal techno-economic sizing of a DC-microgrid for covering EV mobility needs is carried out. It is based on the definition of different scenarios of operation, according to typical EV usage outlooks and environmental conditions. In each scenario, optimal operation is carried out by means of a specific approach for EV commitment on different stations. The sizing procedure is able to handle the modular structure of microgrid devices. The proposed approach is applied to a case study of an envisaged EV service fleet for the Bari port authority.

Multi-Objective Optimization in Multi-Attribute and Multi-Unit Combinatorial Reverse Auctions

2017 ◽  
Vol 26 (05) ◽  
pp. 1760016 ◽  
Author(s):  
Shubhashis Kumar Shil ◽  
Samira Sadaoui
Keyword(s):  
Quality Measures ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Solution Quality ◽  
Winner Determination ◽  
Multi Objective ◽  
Conflicting Objectives ◽  
Trading Constraints ◽  
Significant Superiority

This study introduces an advanced Combinatorial Reverse Auction (CRA), multi-units, multiattributes and multi-objective, which is subject to buyer and seller trading constraints. Conflicting objectives may occur since the buyer can maximize some attributes and minimize some others. To address the Winner Determination (WD) problem for this type of CRAs, we propose an optimization approach based on genetic algorithms that we integrate with our variants of diversity and elitism strategies to improve the solution quality. Moreover, by maximizing the buyer’s revenue, our approach is able to return the best solution for our complex WD problem. We conduct a case study as well as simulated testing to illustrate the importance of the diversity and elitism schemes. We also validate the proposed WD method through simulated experiments by generating large instances of our CRA problem. The experimental results demonstrate on one hand the performance of our WD method in terms of several quality measures, like solution quality, run-time complexity and trade-off between convergence and diversity, and on the other hand, it’s significant superiority to well-known heuristic and exact WD techniques that have been implemented for much simpler CRAs.

Including decision-makers preferences in the cost-deprivation trade-off during disaster interventions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Florian Diehlmann ◽  
Patrick Siegfried Hiemsch ◽  
Marcus Wiens ◽  
Markus Lüttenberg ◽  
Frank Schultmann
Keyword(s):  
Decision Making ◽  
Humanitarian Logistics ◽  
Decision Makers ◽  
Weighted Sum ◽  
Trade Off ◽  
Content Type ◽  
Multi Objective ◽  
Conflicting Objectives ◽  
The Cost

Purpose In this contribution, the purpose of this study is to extend the established social cost concept of humanitarian logistics into a preference-based bi-objective approach. The novel concept offers an efficient, robust and transparent way to consider the decision-maker’s preference. In principle, the proposed method applies to any multi-objective decision and is especially suitable for decisions with conflicting objectives and asymmetric impact. Design/methodology/approach The authors bypass the shortcomings of the traditional approach by introducing a normalized weighted sum approach. Within this approach, logistics and deprivation costs are normalized with the help of Nadir and Utopia points. The weighting factor represents the preference of a decision-maker toward emphasizing the reduction of one cost component. The authors apply the approach to a case study for hypothetical water contamination in the city of Berlin, in which authorities select distribution center (DiC) locations to supply water to beneficiaries. Findings The results of the case study highlight that the decisions generated by the approach are more consistent with the decision-makers preferences while enabling higher efficiency gains. Furthermore, it is possible to identify robust solutions, i.e. DiCs opened in each scenario. These locations can be the focal point of interest during disaster preparedness. Moreover, the introduced approach increases the transparency of the decision by highlighting the cost-deprivation trade-off, together with the Pareto-front. Practical implications For practical users, such as disaster control and civil protection authorities, this approach provides a transparent focus on the trade-off of their decision objectives. The case study highlights that it proves to be a powerful concept for multi-objective decisions in the domain of humanitarian logistics and for collaborative decision-making. Originality/value To the best of the knowledge, the present study is the first to include preferences in the cost-deprivation trade-off. Moreover, it highlights the promising option to use a weighted-sum approach to understand the decisions affected by this trade-off better and thereby, increase the transparency and quality of decision-making in disasters.

scholarly journals ROBUST MULTI-OBJECTIVE OPTIMIZATION IN PRODUCT DEVELOPMENT WITH RESPECT TO USER-SCENARIO AND MANUFACTURING UNCERTAINTIES

2021 ◽  
Vol 1 ◽  
pp. 2591-2600
Author(s):  
Philipp Wolniak ◽  
Jakob Cramer ◽  
Roland Lachmayer
Keyword(s):  
Product Development ◽  
Product Design ◽  
Latin Hypercube Sampling ◽  
Automated Analysis ◽  
Multi Objective ◽  
Conflicting Objectives ◽  
User Scenario ◽  
Manufacturing Tolerances ◽  
The Impact

AbstractIn product development, user-scenarios are a way of tailoring requirements to defined customer groups. Furthermore, a product design often involves multiple conflicting objectives that are analyzed within an iterative process. The models typically used for the analysis often do not accurately reflect the real-world representation. This can be alleviated by finding robust product designs. While usually uncertainties due to manufacturing tolerances are investigated, we additionally consider uncertainties in the user-scenario. Therefore, we present a robustness evaluation in a multi-objective numerical optimization in product development. For this, we consider manufacturing tolerances using an adjusted Latin Hypercube Sampling as well as deviations in the user-scenario by means of a Gaussian distribution. In the case study, we present the robust development of a customer specific coffee machine, where we show the robustness evaluation and the impact of the proposed adjustments. The advantage of the presented process is a product design tailored to the customer's requirements under specified uncertainties. In addition, this enables a time benefit in the product development due to the automated analysis used in the optimization.

Optimal operation scheduling of wind power integrated with compressed air energy storage (CAES)

2013 ◽  
Vol 51 ◽  
pp. 53-59 ◽  
Author(s):  
M. Abbaspour ◽  
M. Satkin ◽  
B. Mohammadi-Ivatloo ◽  
F. Hoseinzadeh Lotfi ◽  
Y. Noorollahi
Keyword(s):  
Energy Storage ◽  
Wind Power ◽  
Optimal Operation ◽  
Compressed Air ◽  
Compressed Air Energy Storage ◽  
Operation Scheduling

scholarly journals Capacity Expansion Pathways for a Wind and Solar Based Power Supply and the Impact of Advanced Technology—A Case Study for Germany

Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 324 ◽  
Author(s):  
Philip Tafarte ◽  
Marcus Eichhorn ◽  
Daniela Thrän
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Power Supply ◽  
Electric Energy ◽  
Capacity Expansion ◽  
Advanced Technology ◽  
Series Data ◽  
Solar Pv ◽  
Electric Energy Storage

Wind and solar PV have become the lowest-cost renewable alternatives and are expected to dominate the power supply matrix in many countries worldwide. However, wind and solar are inherently variable renewable energy sources (vRES) and their characteristics pose new challenges for power systems and for the transition to a renewable energy-based power supply. Using new options for the integration of high shares of vRES is therefore crucial. In order to assess these options, we model the expansion pathways of wind power and solar photovoltaics (solar PV) capacities and their impact on the renewable share in a case study for Germany. Therefore, a numerical optimization approach is applied on temporally resolved generation and consumption time series data to identify the most efficient and fastest capacity expansion pathways. In addition to conventional layouts of wind and solar PV, our model includes advanced, system-friendly technology layouts in combination with electric energy storage from existing pumped hydro storage as promising integration options. The results provide policy makers with useful insights for technology-specific capacity expansion as we identified potentials to reduce costs and infrastructural requirements in the form of power grids and electric energy storage, and to accelerate the transition to a fully renewable power sector.

Sign in / Sign up

Export Citation Format

Share Document