Implementing agent-based emissions trading for controlling Virtual Power Plant emissions

Skarvelis‐Kazakos, Spyros; Rikos, Evangelos; Kolentini, Efstathia; Cipcigan, Liana; Jenkins, Nick

doi:10.1016/j.epsr.2013.04.004

Cited by 32 publications

(23 citation statements)

References 7 publications

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“…In [54], a model of TVPP is proposed to reduce its cost with a non-linear programming considering the constraints of DGs, distribution systems and DR. One of the most important objectives that can be considered in a VPP is the system emission reduction. A multi-agent system is designed in [55] for the emission regulation of the aggregated microgenerators. In this study, the simulations of the operational system are confirmed by using an experimental system.…”

Section: Operation Systems Of Vppmentioning

confidence: 99%

A review on the virtual power plant: Components and operation systems

Ghavidel

Aghaei

et al. 2016

2016 IEEE International Conference on Power System Technology (POWERCON)

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Abstract--Due to the high penetration of Distributed Generations (DGs) in the network and the presently involving competition in all electrical energy markets, Virtual Power Plant (VPP) as a new concept has come into view, with the intention of dealing with the increasing number of DGs in the system and handling effectively the competition in the electricity markets. This paper reviews the VPP in terms of components and operation systems. VPP fundamentally is composed of a number of DGs including conventional dispatchable power plants and intermittent generating units along with possible flexible loads and storage units. In this paper, these components are described in an all-inclusive manner, and some of the most important ones are pointed out. In addition, the most important anticipated outcomes of the two types of VPP, Commercial VPP (CVPP) and Technical VPP (TVPP), are presented in detail. Furthermore, the important literature associated with Combined Heat and Power (CHP) based VPP, VPP components and modeling, VPP with Demand Response (DR), VPP bidding strategy, and participation of VPP in electricity markets are briefly classified and discussed in this paper.

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Section: Operation Systems Of Vppmentioning

confidence: 99%

A review on the virtual power plant: Components and operation systems

Ghavidel

Aghaei

et al. 2016

2016 IEEE International Conference on Power System Technology (POWERCON)

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“…4 MAS are classified as a distributed control architecture and have been proposed as a promising technology for 5 addressing control and co-ordination issues in the power industry, including DER [15], [16]. In addition, MAS have 6 been proposed for controlling CHP unit clusters [17] and for co-ordinating electric vehicle charging [18], [19], [20], [21]. 7 8 The concept presented in this paper combines the multiple energy carrier modelling approach of energy hubs, with 9 the distributed control approach of multi-agent systems.…”

Section: Introductionmentioning

confidence: 99%

“…Agent-based implementations are by definition market oriented, provided 18 that they use cooperative or competitive negotiation and coordination techniques, and normally use market-like 19 structures to reach an optimal or near-optimal solution [29], [30]. Such market-oriented approaches have also been 20 developed by the authors in previous work [18], [19], [20], [21]. [20], [21], [29], [31].…”

Section: Introductionmentioning

confidence: 99%

“…Such market-oriented approaches have also been 20 developed by the authors in previous work [18], [19], [20], [21]. [20], [21], [29], [31]. 32 (e) The need to address or compensate for planning errors, including operation forecasts [21], [33], [34].…”

Section: Introductionmentioning

confidence: 99%

“…[20], [21], [29], [31]. 32 (e) The need to address or compensate for planning errors, including operation forecasts [21], [33], [34]. 33…”

Section: Introductionmentioning

confidence: 99%

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Multiple energy carrier optimisation with intelligent agents

et al. 2016

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Multiple energy carrier systems stem from the need to evolve traditional electricity, gas and other energy systems to 10 more efficient, integrated energy systems. An approach is presented, for controlling multiple energy carriers, 11 including electricity (AC or DC), heat, natural gas and hydrogen, with the objective to minimise the overall cost 12 and/or emissions, while adhering to technical and commercial constraints, such as network limits and market 13 contracts. The technique of multi-agent systems (MAS) was used. The benefits of this approach are discussed and 14 include a reduction of more than 50% in the balancing costs of a potential deviation. An implementation of this 15 methodology is also presented. In order to validate the operation of the developed system, a number of experiments 16 were performed using both software and hardware. The results validated the efficient operation of the developed 17 system, proving its ability to optimise the operation of multiple energy carrier inputs within the context of an energy 18 hub, using a hierarchical multi-agent system control structure. It is necessary to evolve traditional electricity, gas and other energy systems to more flexible, integrated energy 34 systems [11], referred to as multiple energy carrier, or multi-carrier systems. The points of interaction between 35 different energy carriers have been described as "energy hubs" [5], [12], which present an integrated approach for 36 optimizing systems with multiple energy carriers, such as electricity, hydrogen, or natural gas networks [13]. Devices 37 are incorporated in an energy hub with the purpose of converting from one carrier to another, e.g. a CHP unit 38 converting natural gas to electricity and heat. Storage elements such as batteries or thermal storage may also be 39 considered. The energy carrier inputs to the energy hub are optimised and controlled in order to supply a given set of 40 energy carrier loads / outputs, thus achieving whole-system optimization [12], [14]. In (1), the backward coupling 41 matrix (Dnm) which links the inputs (Pm) with the outputs (Ln) is shown, as this is a formality that is used in Section 2.2. 42The elements of the Dnm matrix are constructed using the conversion efficiencies of individual devices in the energy 43 hub [12]. Matrix dimensions are × 1, × 1 and × , for Pm, Ln and Dnm respectively. 44

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Optimal operational scheduling of a virtual power plant participating in day‐ahead market with consideration of emission and battery degradation cost

Akkaş

Çam

2020

Int Trans Electr Energ Syst

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Implementing agent-based emissions trading for controlling Virtual Power Plant emissions

Cited by 32 publications

References 7 publications

A review on the virtual power plant: Components and operation systems

A review on the virtual power plant: Components and operation systems

Multiple energy carrier optimisation with intelligent agents

Optimal operational scheduling of a virtual power plant participating in day‐ahead market with consideration of emission and battery degradation cost

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