Special Issue "Optimisation Models and Methods in Energy Systems"

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (6 May 2019).

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A printed edition of this Special Issue is available here.

Special Issue Editor

Prof. Dr. Carlos Henggeler Antunes
E-Mail Website
Guest Editor
INESC Coimbra, Department of Electrical and Computer Engineering, University of Coimbra, Polo 2, 3030-290 Coimbra, Portugal
Tel. +351239796259
Interests: energy efficiency; demand side management; demand response; optimization models and methods in energy systems; multi-objective optimization; multi-criteria decision analysis
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Special Issue Information

Dear Colleagues,

Challenging problems arise in all segments of energy industries—generation, transmission, distribution and consumption. Optimization models and methods play a key role to offer decision/policy makers better information to assist sounder decisions at different levels, ranging from operational to strategic planning.

Energy systems and networks are increasingly complex; therefore, optimization models and methods are essential tools for the development of smart(er) networks within more integrated and sustainable energy systems, encompassing electricity, gas, district heating/cooling, etc., with pervasive deployment of information and communication technologies.

Technical design, operational, economic, regulatory, social and environmental issues, among others, are at stake requiring interdisciplinary approaches, with contributions from engineering, economics and social sciences fields to the definition of adequate optimization models and methods to support more informed decision processes.

Planning tasks are increasingly complex due to the unbundling of the industry value chain and the emergence of new players (e.g., aggregators) and market structures. The ongoing evolution of energy systems to smart grids comprises the deployment of new network automation technologies, bi-directional communication, smart metering, analysis and extraction of value from massive amounts of data. This process enables the integration of further renewable-based generation, which contributes to the decarbonization of the economy but in turn creates new technical and market challenges due to its variable nature, and the empowerment of consumers who may have a more proactive role through demand response mechanisms. The global aim is to develop more sustainable, reliable and efficient grids.

Contributions are expected to cover a wide range of topics including: Electricity smart grids; gas smart grids; district heating/cooling; integration of renewable generation; storage; demand side management and demand response; selection and location of equipment including communication issues; system reliability and provision of ancillary services; market design and operation. Further topics related to optimization models and methods to tackle challenging problems in energy networks and systems, namely regarding the evolution to smart grids, are welcome. Contributions reporting real-world case studies are particularly appreciated.

All papers will undergo a stringent review procedure according to the quality standards of Energies. Papers must contain original research results including comprehensive mathematical models, algorithmic advances and extensive numerical experiments. Numerical illustrations cannot be toy examples, but real or realistic case studies for which all data should be provided (in the paper or as supplementary material) to ensure the replicability of results. The research reported in contributed papers should convey novel and significant work relative to the relevant literature.

Prof. Dr. Carlos Henggeler Antunes
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • optimization models and methods
  • energy systems
  • smart grids
  • electrical networks
  • gas networks
  • district heating/cooling

Published Papers (9 papers)

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Research

Open AccessArticle
Including Wind Power Generation in Brazil’s Long-Term Optimization Model for Energy Planning
Energies 2019, 12(5), 826; https://doi.org/10.3390/en12050826 - 02 Mar 2019
Abstract
In the past two decades, wind power’s share of the energy mix has grown significantly in Brazil. However, nowadays planning electricity operation in Brazil basically involves evaluating the future conditions of energy supply from hydro and thermal sources over the planning horizon. In [...] Read more.
In the past two decades, wind power’s share of the energy mix has grown significantly in Brazil. However, nowadays planning electricity operation in Brazil basically involves evaluating the future conditions of energy supply from hydro and thermal sources over the planning horizon. In this context, wind power sources are not stochastically treated. This work applies an innovative approach that incorporates wind power generation in the Brazilian hydro-thermal dispatch using the analytical method of Frequency & Duration. The proposed approach is applied to Brazil’s Northeast region, covering the planning period from July 2017 to December 2021, using the Markov chain Monte Carlo method to simulate wind power scenarios. The obtained results are more conservative than the one currently used by the National Electric System Operator, since the proposed approach forecasts 1.8% less wind generation, especially during peak periods, and 0.67% more thermal generation. This conservatism can reduce the chance of water reservoir depletion and, also an ineffective dispatch. Full article
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Open AccessArticle
Generation Expansion Planning Model for Integrated Energy System Considering Feasible Operation Region and Generation Efficiency of Combined Heat and Power
Energies 2019, 12(2), 226; https://doi.org/10.3390/en12020226 - 11 Jan 2019
Cited by 3
Abstract
Integrated energy systems can provide a more efficient supply than individual systems by using resources such as cogeneration. To foster efficient management of these systems, the flexible operation of cogeneration resources should be considered for the generation expansion planning model to satisfy the [...] Read more.
Integrated energy systems can provide a more efficient supply than individual systems by using resources such as cogeneration. To foster efficient management of these systems, the flexible operation of cogeneration resources should be considered for the generation expansion planning model to satisfy the varying demand of energy including heat and electricity, which are interdependent and present different seasonal characteristics. We propose an optimization model of the generation expansion planning for an integrated energy system considering the feasible operation region and efficiency of a combined heat and power (CHP) resource. The proposed model is formulated as a mixed integer linear programming problem to minimize the sum of the annualized cost of the integrated energy system. Then, we set linear constraints of energy resources and describe linearized constraints of a feasible operation region and a generation efficiency of the CHP resource for application to the problem. The effectiveness of the proposed optimization problem is verified through a case study comparing with results of a conventional optimization model that uses constant heat-to-power ratio and generation efficiency of the CHP resource. Furthermore, we evaluate planning schedules and total generation efficiency profiles of the CHP resource for the compared optimization models. Full article
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Open AccessFeature PaperArticle
Prospects of a Meshed Electrical Distribution System Featuring Large-Scale Variable Renewable Power
Energies 2018, 11(12), 3399; https://doi.org/10.3390/en11123399 - 04 Dec 2018
Cited by 2
Abstract
Electrical distribution system operators (DSOs) are facing an increasing number of challenges, largely as a result of the growing integration of distributed energy resources (DERs), such as photovoltaic (PV) and wind power. Amid global climate change and other energy-related concerns, the transformation of [...] Read more.
Electrical distribution system operators (DSOs) are facing an increasing number of challenges, largely as a result of the growing integration of distributed energy resources (DERs), such as photovoltaic (PV) and wind power. Amid global climate change and other energy-related concerns, the transformation of electrical distribution systems (EDSs) will most likely go ahead by modernizing distribution grids so that more DERs can be accommodated. Therefore, new operational strategies that aim to increase the flexibility of EDSs must be thought of and developed. This action is indispensable so that EDSs can seamlessly accommodate large amounts of intermittent renewable power. One plausible strategy that is worth considering is operating distribution systems in a meshed topology. The aim of this work is, therefore, related to the prospects of gradually adopting such a strategy. The analysis includes the additional level of flexibility that can be provided by operating distribution grids in a meshed manner, and the utilization level of variable renewable power. The distribution operational problem is formulated as a mixed integer linear programming approach in a stochastic framework. Numerical results reveal the multi-faceted benefits of operating distribution grids in a meshed manner. Such an operation scheme adds considerable flexibility to the system and leads to a more efficient utilization of variable renewable energy source (RES)-based distributed generation. Full article
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Open AccessArticle
A University Building Test Case for Occupancy-Based Building Automation
Energies 2018, 11(11), 3145; https://doi.org/10.3390/en11113145 - 14 Nov 2018
Cited by 1
Abstract
Heating, ventilation and air-conditioning (HVAC) units in buildings form a system-of-subsystems entity that must be accurately integrated and controlled by the building automation system to ensure the occupants’ comfort with reduced energy consumption. As control of HVACs involves a standardized hierarchy of high-level [...] Read more.
Heating, ventilation and air-conditioning (HVAC) units in buildings form a system-of-subsystems entity that must be accurately integrated and controlled by the building automation system to ensure the occupants’ comfort with reduced energy consumption. As control of HVACs involves a standardized hierarchy of high-level set-point control and low-level Proportional-Integral-Derivative (PID) controls, there is a need for overcoming current control fragmentation without disrupting the standard hierarchy. In this work, we propose a model-based approach to achieve these goals. In particular: the set-point control is based on a predictive HVAC thermal model, and aims at optimizing thermal comfort with reduced energy consumption; the standard low-level PID controllers are auto-tuned based on simulations of the HVAC thermal model, and aims at good tracking of the set points. One benefit of such control structure is that the PID dynamics are included in the predictive optimization: in this way, we are able to account for tracking transients, which are particularly useful if the HVAC is switched on and off depending on occupancy patterns. Experimental and simulation validation via a three-room test case at the Delft University of Technology shows the potential for a high degree of comfort while also reducing energy consumption. Full article
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Open AccessFeature PaperArticle
A Graph Theoretic Approach to Optimal Firefighting in Oil Terminals
Energies 2018, 11(11), 3101; https://doi.org/10.3390/en11113101 - 09 Nov 2018
Abstract
Effective firefighting of major fires in fuel storage plants can effectively prevent or delay fire spread (domino effect) and eventually extinguish the fire. If the number of firefighting crew and equipment is sufficient, firefighting will include the suppression of all the burning units [...] Read more.
Effective firefighting of major fires in fuel storage plants can effectively prevent or delay fire spread (domino effect) and eventually extinguish the fire. If the number of firefighting crew and equipment is sufficient, firefighting will include the suppression of all the burning units and cooling of all the exposed units. However, when available resources are not adequate, fire brigades would need to optimally allocate their resources by answering the question “which burning units to suppress first and which exposed units to cool first?” until more resources become available from nearby industrial plants or residential communities. The present study is an attempt to answer the foregoing question by developing a graph theoretic methodology. It has been demonstrated that suppression and cooling of units with the highest out-closeness index will result in an optimum firefighting strategy. A comparison between the outcomes of the graph theoretic approach and an approach based on influence diagram has shown the efficiency of the graph approach. Full article
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Open AccessArticle
Fuzzy Portfolio Optimization of Power Generation Assets
Energies 2018, 11(11), 3043; https://doi.org/10.3390/en11113043 - 06 Nov 2018
Abstract
Fuzzy theory is proposed as an alternative to the probabilistic approach for assessing portfolios of power plants, in order to capture the complex reality of decision-making processes. This paper presents different fuzzy portfolio selection models, where the rate of returns as well as [...] Read more.
Fuzzy theory is proposed as an alternative to the probabilistic approach for assessing portfolios of power plants, in order to capture the complex reality of decision-making processes. This paper presents different fuzzy portfolio selection models, where the rate of returns as well as the investor’s aspiration levels of portfolio return and risk are regarded as fuzzy variables. Furthermore, portfolio risk is defined as a downside risk, which is why a semi-mean-absolute deviation portfolio selection model is introduced. Finally, as an illustration, the models presented are applied to a selection of power generation mixes. The efficient portfolio results show that the fuzzy portfolio selection models with different definitions of membership functions as well as the semi-mean-absolute deviation model perform better than the standard mean-variance approach. Moreover, introducing membership functions for the description of investors’ aspiration levels for the expected return and risk shows how the knowledge of experts, and investors’ subjective opinions, can be better integrated in the decision-making process than with probabilistic approaches. Full article
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Open AccessArticle
Optimal Energy Management of Building Microgrid Networks in Islanded Mode Considering Adjustable Power and Component Outages
Energies 2018, 11(9), 2351; https://doi.org/10.3390/en11092351 - 06 Sep 2018
Cited by 1
Abstract
In this paper, an optimal energy management scheme for islanded building microgrid networks is proposed. The proposed building microgrid network comprises of several inter-connected building microgrids (BMGs) and an external energy supplier. Each BMG has a local combined heat and power (CHP) unit, [...] Read more.
In this paper, an optimal energy management scheme for islanded building microgrid networks is proposed. The proposed building microgrid network comprises of several inter-connected building microgrids (BMGs) and an external energy supplier. Each BMG has a local combined heat and power (CHP) unit, energy storage, renewables and loads (electric and thermal). The external energy system comprises of an external CHP unit, chillers, electric heat pumps and heat pile line, for thermal energy storage. The BMGs can trade energy with other BMGs of the network and can also trade energy with the external energy supplier. In order to efficiently utilize the components of the BMGs and the network, the concept of adjustable power is adopted in this study. Adjustable power can reduce the operation cost of the network by increasing/decreasing the power of dispatchable units. In addition, the failure/recovery of components in the BMGs and the external system are also considered to analyze the performance of the proposed operation method. In order to optimally utilize the available resources during events, precedence among loads of BMGs and the external energy supplier is considered. Simulation results have proved the applicability of the proposed method for both normal islanded mode and with outage/recovery of equipment during the operation horizon. Finally, sensitivity analysis is carried out to analyze the impact of change in components’ parameters values on the saved cost of the network. Full article
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Open AccessArticle
A Stochastic Inexact Robust Model for Regional Energy System Management and Emission Reduction Potential Analysis—A Case Study of Zibo City, China
Energies 2018, 11(8), 2108; https://doi.org/10.3390/en11082108 - 13 Aug 2018
Cited by 1
Abstract
In this study, in order to improve regional energy system adjustment, a multistage stochastic inexact robust programming (MSIRP) is proposed for electric-power generation planning and structure adjustment management under uncertainty. Scenario-based inexact multistage stochastic programming and stochastic robust optimization were integrated into general [...] Read more.
In this study, in order to improve regional energy system adjustment, a multistage stochastic inexact robust programming (MSIRP) is proposed for electric-power generation planning and structure adjustment management under uncertainty. Scenario-based inexact multistage stochastic programming and stochastic robust optimization were integrated into general programming to reflect uncertainties that were expressed as interval values and probability distributions in the objective function and constraints. An MSIRP-based energy system optimization model is proposed for electric-power structure management of Zibo City in Shandong Province, China. Three power demand scenarios associated with electric-power structure adjustment, imported electricity, and emission reduction were designed to obtain multiple decision schemes for supporting regional sustainable energy system development. The power generation schemes, imported electricity, and emissions of CO2 and air pollutants were analyzed. The results indicated that the model can effectively not only provide a more stable energy supply strategies and electric-power structure adjustment schemes, but also improve the balanced development between conventional and new clear power generation technologies under uncertainty. Full article
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Open AccessArticle
A Framework for the Selection of Optimum Offshore Wind Farm Locations for Deployment
Energies 2018, 11(7), 1855; https://doi.org/10.3390/en11071855 - 16 Jul 2018
Cited by 5
Abstract
This research develops a framework to assist wind energy developers to select the optimum deployment site of a wind farm by considering the Round 3 available zones in the UK. The framework includes optimization techniques, decision-making methods and experts’ input in order to [...] Read more.
This research develops a framework to assist wind energy developers to select the optimum deployment site of a wind farm by considering the Round 3 available zones in the UK. The framework includes optimization techniques, decision-making methods and experts’ input in order to support investment decisions. Further, techno-economic evaluation, life cycle costing (LCC) and physical aspects for each location are considered along with experts’ opinions to provide deeper insight into the decision-making process. A process on the criteria selection is also presented and seven conflicting criteria are being considered for implementation in the technique for the order of preference by similarity to the ideal solution (TOPSIS) method in order to suggest the optimum location that was produced by the nondominated sorting genetic algorithm (NSGAII). For the given inputs, Seagreen Alpha, near the Isle of May, was found to be the most probable solution, followed by Moray Firth Eastern Development Area 1, near Wick, which demonstrates by example the effectiveness of the newly introduced framework that is also transferable and generic. The outcomes are expected to help stakeholders and decision makers to make better informed and cost-effective decisions under uncertainty when investing in offshore wind energy in the UK. Full article
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