Cooperation-based transactive energy management for modelling and analysis of low emission multi-vectored networked energy hubs | |
| Author | Tiwari, Shubham |
| Call Number | AIT Diss no.SE-23-07 |
| Subject(s) | Energy storage Power resources--Management Electric power systems--Management Renewable resource integration |
| Note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Engineering in Sustainable Energy Transition |
| Publisher | Asian Institute of Technology |
| Abstract | In past years, the conventional power system was mainly associated with a single carrier electrical network with centralised generating units. These units are mainly fossil fuel based and result in high technical losses and emissions. Recently, the need for electrical and thermal demand has increased manifold. With technological advancement in the renewable energy sources and advance energy conversion units such as combined heat and power (CHPs), electrical heat pumps (EHPs) and Power-to-X, natural gas and electricity systems are deployed parallelly to conceptualize the idea of multi-vector energy hubs (MVEHs). Incorporating the two physical systems (gas and electricity) in the energy portfolio enhances reliability and efficiency. With the growing demand and complexity of energy systems, this research proposes a coalition formation of MVEHs to form networked systems. This facilitates energy hubs to exchange energy among each other and achieves regional global objectives such as minimised operating cost, low emissions and high reliability and independency from the main grid. This cooperation is termed as multi-vectored networked energy hubs (MV-NEHs). Thus, this research focuses on the efficient energy management of multi-vectored networked energy hubs.Further, to form the stable coalition, energy hubs must receive their fair share in the profit (achieved by the coalition action) through an unbiassed profit allocation mechanism. Therefore, this research proposes a new and improved profit allocation mechanism that distributes the profit achieved by the coalition among its participants (i.e., energy hubs) based on their individual features and special attributes.Specifically, chapter 3 presents a cooperative energy management approach for multi-carrier (electricity and heat) networked energy hubs. The proposed scheme facilitates energy hubs to exchange power for higher economic and environmental benefits. Based on the cooperative game theory, individual energy hubs cooperate to secure maximum profit, which is then fairly distributed among the hubs to ensure the economic stability of the coalition. The primary focus of this chapter is to minimise the operating cost of the network and implement the classic Shapely for profit allocation mechanism. The proposed model considers the networked system in which hubs are integrated with multi-energy resources such as electrical and natural gas supply, renewable sources, combined heat and power units (CHPs), gas boilers, electrical and heat energy storage units. A scenario-based generation and reduction algorithm is employed to address the uncertain behaviour of sources. Moreover, a price-based demand response program (DR) and electrical vehicles (EVs) are integrated to make the network more flexible. Results show that operating costs and greenhouse gas (GHG) emissions are reduced with the proposed scheme by 25.36% and 26.5%, respectively. Besides, the self-reliability of the networked system improves as the energy imported from the main grid reduces to 13.86%.Further, the subsequent chapter 4 presents cooperation-based transactive energy management (C-TEM) for networked multi-energy (electricity-heat-ice) hubsto minimise the operating cost. Transactive energy allows free peer-to-peer energy trade between the energy hubs and ensures dynamic energy balance to achieve economic and environmental benefits. The main aim of this work is to extend the above framework to incorporate the cooling energy system and formulate an improved payoff allocation mechanism based on player’s (energy hub) contributions and special features (reward to support emission free generation) to ensure coalitional economic stability. In this regard, four different energy hubs are modelled with integrated heat-electricity ice systems to investigate the effectiveness of the proposed approach. An algorithm based on scenario generation and reduction is employed to capture renewable sources’ uncertainties. Moreover, demand response and electric vehicles are efficiently integrated into the network to improve flexibility and performance. The obtained results prove that C-TEM, along with flexible resources, reduces the operating cost by 38.72%. Moreover, the proposed framework cut downs the net energy imported from grid by 26.9%, while enhancing the self-reliability of the coalition by 42.7% compared to the autonomous operation of the hubs. The free peer-to peer energy trade ensures zero clean energy curtailment and maximise the optimal usage of resources to make network technically, economically and environmentally viable. In addition, energy hubs receive fair and improved payoffs based on their unique features and contribution. The improved payoffs motivate network and EHs to increase the share of clean energy resources like RES and EVs.To extend the above-mentioned model, chapter 5 aims to develop a multi-objective problem framework to optimise the cost, emissions and self-reliability of the coalition at once. To do so, this chapter investigates the two-stage, lexicographic-based compromised programming to solve the three objectives. Further, this chapter focuses to integrate the advance energy storages such as adiabatic-compressed energy storages (A-CAES), pumped hydro storages (PHS) and multi-energy demand response mechanism in addition to electric vehicles and conventional energy resources. In addition, the system further integrates electrical heat pumps (EHPs). Finally, this chapter included additional attributes (RES downward risk) to the improved profit allocation mechanism discussed in the last chapter. Thus, this research proposes a tri-level, including an improved payoff allocation scheme for the MV-NEH system to ensure coalition and microgrids' collective and individual interests. At the first level, the stochasticity of renewables is quantified. Then, a two-stage, multi-objective problem formulation is developed at the second level to address the coalition's collective objectives. Results demonstrate that the proposed scheme allows the coalition to achieve its collective interests by reducing the operating cost by 30.1 % and GHG emissions by 22.1 % while improving the network's self - reliability by 21.3 %. Finally, at the third level, the proposed new payoff allocation mechanism rewards and penalizes the microgrids based on their special characteristics and ensures the individual interests of energy hubs.Moreover, to model low-emission multi-vectored energy hub system, chapter 6 is integrated with hybrid power-to-X (electrolyzer, methanization reactor and fuel cell) to reduce green energy spillage. This research is limited to single multi-vectored (electricity-heat-ice) hub modelling. The model is further integrated with hydrogen storage, adiabatic-compressed air energy storage, electric vehicles and multi-energy demand response to enhance flexibility. The main aim of this research is to integrate and analyse the power-to-X units, carbon capture storage and utilization (CCS-U) units along with emission markets in the existing system to develop a low emission energy system model. Simulation results demonstrate that with flexible resources and power-to-X units, MVEH reduces the operating energy cost by 46.4 % and improves the system independency by 19.06 %. Besides, CCS-U units produce 92 % less emission while increasing the energy cost by 5.1 %. It shows that CCS-U units results in higher energy consumption, thus have higher energy operating costs. However, with an effective emission market mechanism, MVEH gains the right to sell carbon credits in the emission market. Thus, the multi-vectored system's economical, reliable and environmental viability are ensured. Finally, sensitivity analysis proves the robustness of the proposed framework against natural gas and carbon price fluctuations.Hence, the thesis develops the low emission, cooperation-based transactive energy management (C-TEM) for networked multi-vectored hubs integrated with an electrical-heat ice system while considering a coalition game-based profit allocation scheme to ensure global and individual objectives of the cooperation. |
| Year | 2023 |
| Type | Dissertation |
| School | School of Environment, Resources, and Development |
| Department | Department of Energy and Climate Change (Former title: Department of Energy, Environment, and Climate Change (DEECC)) |
| Academic Program/FoS | Sustainable Energy Transition (SE) |
| Chairperson(s) | Singh, Jai Govind |
| Examination Committee(s) | Weerakorn Ongsakul;Salam, P. Abdul |
| Scholarship Donor(s) | His Majesty the King's Scholarships (Thailand) |
| Degree | Thesis (Ph.D.) - Asian Institute of Technology, 2023 |