A fuzzy logic energy management system for polygeneration microgrids

Kyriakarakos, George; Dounis, Anastasios I.; Arvanitis, Konstantinos G.; Papadakis, G.

doi:10.1016/j.renene.2011.11.019

Cited by 134 publications

(50 citation statements)

References 27 publications

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“…All the membership functions of the fuzzy logic routines were designed using the control surfaces ( Figure 6) based on the experience of the research team. The rules for each of the routines were developed based on the previous knowledge and the experience of the members of the research team [17]. …”

Section: First Game Modelmentioning

confidence: 99%

A Game Theory Approach to Multi-Agent Decentralized Energy Management of Autonomous Polygeneration Microgrids

2017

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Abstract:Energy management systems are essential and indispensable for the secure and optimal operation of autonomous polygeneration microgrids which include distributed energy technologies and multiple electrical loads. In this paper, a multi-agent decentralized energy management system was designed. In particular, the devices of the microgrid under study were controlled as interactive agents. The energy management problem was formulated here through the application of game theory, in order to model the set of strategies between two players/agents, as a non-cooperative power control game or a cooperative one, according to the level of the energy produced by the renewable energy sources and the energy stored in the battery bank, for the purpose of accomplishing optimal energy management and control of the microgrid operation. The Nash equilibrium was used to compromise the possible diverging goals of the agents by maximizing their preferences. The proposed energy management system was then compared with a multi-agent decentralized energy management system where all the agents were assumed to be cooperative and employed agent coordination through Fuzzy Cognitive Maps. The results obtained from this comparison, demonstrate that the application of game theory based control, in autonomous polygeneration microgrids, can ensure operational and financial benefits over known energy management approaches incorporating distributed intelligence.

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Section: First Game Modelmentioning

confidence: 99%

A Game Theory Approach to Multi-Agent Decentralized Energy Management of Autonomous Polygeneration Microgrids

2017

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“…The proper operation of a microgrid requires advanced energy managements systems (EMS) in order to manage and operate the SWRO desalination system, satisfy the water and electrical demand, secure microgrid's economical operation and keep the energy interchange between production and consumption stable. Several EMS have been developed based on computational intelligence techniques such as fuzzy logic [21] and fuzzy cognitive maps [22,23].…”

Section: Research On Autonomous Microgrids and Swro Desalination Plantsmentioning

confidence: 99%

Renewable Energy Driven Small-Scale Sea Water Reverse Osmosis Desalination Systems: A Survey

Karavas¹,

Papadakis²

2017

J Fundam Renewable Energy Appl

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EditorialIn recent years, water and energy constitute two of the most important concerns of the worldwide agenda. These resources comprise essential commodities for the preservation of life on Earth and the human survival. At the dawn of the 21st century, there are more than 2 billion people without access to fresh water [1]. Taking into consideration that 97% of the earth's water comes from the oceans, an attractive solution to the lack of potable water is seawater desalination [2]. The main desalination processes are the thermal and the membranes ones. The membrane processes, such as electrodialysis and primarily reverse osmosis (RO), have been implemented not only on desalination but generally on water treatment and now have more global acceptance than thermal processes [3]. RO is a process where the feed water enters a semi-permeable membrane under pressure, larger than the osmotic pressure, and the membrane produces fresh water and concentrate solution [4].Water separation processes such as desalination require energy to produce fresh water and the minimum theoretical energy for desalination is 1.06 kWh/m 3 [5]. However, desalination plants consume higher amounts of energy per unit volume of fresh water produced. The continuous increase of the fossil fuels prices and their environmental impact as compared to the advantages of renewable energy and corresponding renewable energy systems (RES), makes the combination of RES with desalination units a sustainable and economically viable solution [6]. There are numerous studies for desalination plants powered by renewable energy technologies such as RO desalination units using solar energy, wind energy and thermal energy. Most of them focus on the quantity of the water production from the desalination unit with the aim to minimize the specific energy consumption (kWh/m 3 ) and the total investment cost. Research on Stand-Alone SWRO Desalination PlantsIn the past two decades, various SWRO desalination systems were developed in many areas in the world such as islands and regions, which face significant shortage in drinking water supply. Most of them use energy recovery devices (such as pressure exchangers and turbine systems) in order to reduce the energy requirements of the RO plant since more than 90% of the input energy to a RO desalination system is wasted in the brine line. Excellent results have been attained with regard to the specific energy consumption when small-scale SWRO desalination units are combined with energy recovery devices [7]. Specifically, a small-scale SWRO desalination unit with energy recovery device can present more than 80% reduction in its energy consumption compared to a same conventional desalination system (without energy recovery device) [8]. Historically, SWRO desalination systems were designed and developed for steady power input (nominal load operation). However, various studies have shown that lower specific energy consumption can be reached when a SWRO desalination unit operates at variable load conditions (over a range of input...

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“…Similarly, scheduling of battery energy storage systems (BESSs) based on environmental conditions is also stochastic in nature [12]. Therefore, fuzzy logic-based scheduling has been used by various researchers [13][14][15][16][17]. Fuzzy set theory can encompass such subjective decision-making process due to its ability to define human reasoning.…”

Section: Introductionmentioning

confidence: 99%

“…The objective of the developed fuzzy control is to optimize energy distribution and to set up battery SOC parameters. A fuzzy EMS is used for optimal scheduling of an autonomous poly-generation microgrid by [16]. A fuzzy logic-based proportional-integral (PI) controller is used by [17] for integration of electrical vehicles with the utility grid.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic-Based Operation of Battery Energy Storage Systems (BESSs) for Enhancing the Resiliency of Hybrid Microgrids

2017

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Abstract:The resiliency of power systems can be enhanced during emergency situations by using microgrids, due to their capability to supply local loads. However, precise prediction of disturbance events is very difficult rather the occurrence probability can be expressed as, high, medium, or low, etc. Therefore, a fuzzy logic-based battery energy storage system (BESS) operation controller is proposed in this study. In addition to BESS state-of-charge and market price signals, event occurrence probability is taken as crisp input for the BESS operation controller. After assessing the membership levels of all the three inputs, BESS operation controller decides the operation mode (subservient or resilient) of BESS units. In subservient mode, BESS is fully controlled by an energy management system (EMS) while in the case of resilient mode, the EMS follows the commands of the BESS operation controller for scheduling BESS units. Therefore, the proposed hybrid microgrid model can operate in normal, resilient, and emergency modes with the respective objective functions and scheduling horizons. Due to the consideration of resilient mode, load curtailment can be reduced during emergency operation periods. Numerical simulations have demonstrated the effectiveness of the proposed strategy for enhancing the resiliency of hybrid microgrids.

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A fuzzy logic energy management system for polygeneration microgrids

Cited by 134 publications

References 27 publications

A Game Theory Approach to Multi-Agent Decentralized Energy Management of Autonomous Polygeneration Microgrids

A Game Theory Approach to Multi-Agent Decentralized Energy Management of Autonomous Polygeneration Microgrids

Renewable Energy Driven Small-Scale Sea Water Reverse Osmosis Desalination Systems: A Survey

Fuzzy Logic-Based Operation of Battery Energy Storage Systems (BESSs) for Enhancing the Resiliency of Hybrid Microgrids

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