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This paper studies the optimal clearing problem for prosumers in peer-to-peer (P2P) energy markets. It is proved that if no trade weights are enforced and the communication structure between successfully traded peers is connected, then the optimal clearing price and total traded powers in P2P market are the same with that in the pool-based market. However, if such communication structure is unconnected, then the P2P market is clustered into smaller P2P markets. If the trade weights are imposed, then the derived P2P market solutions can be significantly changed. Next, a novel decentralized optimization approach is proposed to derive a trading mechanism for P2P markets, based on the alternating direction method of multipliers (ADMM) which naturally fits into the bidirectional trading in P2P energy systems and converges reasonably fast. Analytical formulas of variable updates reveal insightful relations for each pair of prosumers on their individually traded prices and powers with their total traded powers. Further, based on those formulas, decentralized learning schemes for tuning parameters of prosumers cost functions are proposed to attain successful trading with total traded power amount as desired. Case studies on a synthetic system and the IEEE European Low Voltage Test Feeder are then carried out to verify the proposed approaches. [ABSTRACT FROM AUTHOR]

This research undertakes an investigation of global fuel cell vehicle (FCV) deployment, cognizant of optimal economic deployment and stakeholder preferences in a case study of Japan out to the year 2050. The model is mathematically formulated as a large‐scale linear optimization problem, aiming to minimize system costs, including generation type, fuel, conversion, and carbon reduction, subject to the constraint of carbon dioxide reduction targets. Results show that between ∼0.8 and 2% of global energy consumption needs can be met by hydrogen by 2050, with city gas and transport emerging as significant use cases. Passenger FCVs and hydrogen buses account for most of the hydrogen‐based transportation sector, leading to a global deployment of ∼120 million FCVs by 2050. Hydrogen production is reliant on fossil fuels, and OECD nations are net importers – especially Japan. To underpin hydrogen production from fossil fuels, carbon capture and storage is required in significant quantities when anticipating a large fleet of FCVs. Stakeholder engagement suggests optimism toward FCV deployment while policy issues identified include the necessity for large‐scale future energy system investment and rapid technical and economic feasibility progress for renewables and electrolysers to achieve a hydrogen economy which is not reliant on fossil fuels. [ABSTRACT FROM AUTHOR]

This paper proposes a novel distributed control architecture for output power regulation of doubly fed induction generator (DFIG) based wind turbines (WTs) with on-site battery energy storage systems (BESSs). The proposed distributed control architecture receives information from adjacent WTs+BESSs to control the DFIG's grid side converter (GSC) and the storage unit for output active/reactive power regulation and energy management purposes. The proposed method guarantees the equal active power sharing and energy management of WTs+BESSs in various wind speed conditions. A distributed controller is also designed to respond to the reactive power demand and share the reactive load demand between the GSC and BESS controllers based on their capacities. Furthermore, a controller is designed to account for the communication delays caused by the communication systems based on the IEEE standards. The proposed method is tested on the modified IEEE 14-bus power system with 10 WTs+BESSs. [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach to design fully distributed consensus controllers for heterogeneous linear Multiagent Systems subjected to randomly switching directed topologies and model uncertainties. The appealing features of this approach are as follows. First, it uses the mildest assumption for the randomly switching topologies that the union of switched graphs has a spanning tree. Second, the consensus is achieved under a class of state multiplicative uncertainties. Moreover, the proposed consensus controllers are low-rank and have nonconservative coupling strengths. Finally, a numerical example is presented to illustrate the effectiveness of the proposed theoretical approach. [ABSTRACT FROM AUTHOR]

This paper investigates stochastic market clearing solutions in peer-to-peer (P2P) energy markets as two parameters of prosumers' cost functions are flexibly and randomly chosen in certain intervals to compensate uncertainties and guarantee their energy preferences. For tractability, the scenarios in which one parameter is varied while the other is fixed are considered. It is then shown that a few distributions, namely normal, Cauchy, and gamma distributions, are invariant for P2P energy markets, i.e., if prosumer cost function parameters follow one of those distributions, then market clearing solutions will follow the same type of distribution. Explicit and analytical formulas for probability density functions of market clearing price and trading powers in P2P energy markets are derived for each type of the above-mentioned distributions. As such, variations on P2P energy market clearing solutions can be assessed and predicted when parameters in the stochastic distribution of prosumer cost function parameters are changed. Simulations are carried out for a modified IEEE European Low Voltage Test Feeder system whose results validate the obtained theoretical characterizations. • Varied prosumer cost function parameters to reflex uncertainties and energy preferences. • Tractable cases include normal, Cauchy and gamma distributions of prosumer parameters. • Analytical formulas for the p.d.f of market-clearing price and trading powers. • Assessment and prediction of trading price and trading power p.d.f variations. [ABSTRACT FROM AUTHOR]

This paper presents a new and systematic procedure to design sub-optimal hierarchical feedback controllers for the leader–follower consensus problem in homogeneous multi-agent systems. First, the given multi-agent system is treated as a two-layer hierarchical system where the agents perform local actions in the lower layer and interact with others in the upper layer to achieve some global goals. Then the consensus controller design is formulated as a hierarchical state feedback control problem. Employing LQR approach with an appropriately selected performance index, an optimal hierarchical state feedback controller is derived which includes two terms namely local and global terms. Consequently, by removing the local term, the remaining global term is proved to make the multi-agent system consensus which results in a sub-optimal hierarchical consensus controller. Finally, some numerical examples are introduced to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we present a new robust iterative learning control (ILC) design for a class of linear systems in the presence of time-varying parametric uncertainties and additive input/output disturbances. The system model is described by the Markov matrix as an affine function of parametric uncertainties. The robust ILC design is formulated as a min–max problem using a quadratic performance criterion subject to constraints of the control input update. Then, we propose a novel methodology to find a suboptimal solution of the min–max optimization problem. First, we derive an upper bound of the worst-case performance. As a result, the min–max problem is relaxed to become a minimization problem in the form of a quadratic program. Next, the robust ILC design is cast into a convex optimization over linear matrix inequalities (LMIs) which can be easily solved using off-the-shelf optimization solvers. The convergences of the control input and the error are proved. Finally, the robust ILC algorithm is applied to a physical model of a flexible link. The simulation results reveal the effectiveness of the proposed algorithm. [Copyright &y& Elsevier]

This article presents a novel robust iterative learning control algorithm (ILC) for linear systems in the presence of multiple time-invariant parametric uncertainties.The robust design problem is formulated as a min-max problem with a quadratic performance criterion subject to constraints of the iterative control input update. Then, we propose a new methodology to find a sub-optimal solution of the min-max problem. By finding an upper bound of the worst-case performance, the min-max problem is relaxed to be a minimisation problem. Applying Lagrangian duality to this minimisation problem leads to a dual problem which can be reformulated as a convex optimisation problem over linear matrix inequalities (LMIs). An LMI-based ILC algorithm is given afterward and the convergence of the control input as well as the system error are proved. Finally, we apply the proposed ILC to a generic example and a distillation column. The numerical results reveal the effectiveness of the LMI-based algorithm. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the design of iterative learning control based on quadratic performance criterion (Q-ILC) for linear systems subject to additive uncertainty. The robust Q-ILC design can be cast as a min–max problem. We propose a novel approach which employs an upper bound of the worst-case performance, then formulates a non-convex quadratic minimization problem to get the update of iterative control inputs. Applying Lagrange duality, the Lagrange dual function of the non-convex quadratic problem is equivalent to a convex optimization over linear matrix inequalities (LMIs). An LMI algorithm with convergence properties is then given for the robust Q-ILC design. Finally, we provide a numerical example to illustrate the effectiveness of the proposed method. [Copyright &y& Elsevier]

• Novel peer-to-peer electricity trading between FC-CHP systems. • Higher-efficiency operating points for fuel cells. • Increase of self-sufficiency and resilience for local energy systems. • Convexified optimization of gas-electricity optimal management of FC-CHP systems. • Distributed and parallel ADMM method for solving optimal peer-to-peer energy trading. This paper studies the optimal energy management in a group of dwellings having micro fuel cell combined heat and power systems. To increase the self-sufficiency and resilience of such local community, a P2P energy trading system between dwellings is proposed in which output powers from fuel cells working under their rated powers can be sold to those already reach their rated outputs but still lack powers. The arising optimization problem from this optimal P2P energy trading system is non-convex due to the nonlinear dependence of power and heat efficiencies on fuel cell output power. Therefore, a linearization method is proposed to convexify the problem. Consequently, a distributed ADMM approach is introduced to solve the convexified optimization problem in parallel at each dwelling. A case study for a group of six dwellings based on realistic electric consumption data is then presented to demonstrate the proposed approach performance and positive impacts of the P2P energy trading system. More specifically, the proposed distributed ADMM approach is reasonably fast in convergence and is scalable well with system size. In addition, P2P electricity trading system helps operate fuel cells at a higher efficiency and increase the self-sufficiency of such dwellings. [ABSTRACT FROM AUTHOR]

• A novel emissions trading system model is proposed. • Aspects of resilience and the energy mix are modeled. • Introducing the trading scheme engenders significant CO 2 reductions for Japan. • Detailed economic feasibility analysis is undertaken to establish payback periods. • CO 2 price sensitivity effects identified for model outcomes. The issue of climate change and the development of international agreements around carbon targets such as the Paris agreement have engendered the prospect of a carbon constrained future. As a result, individual nations who are signatory to the Paris Agreement have developed ambitious carbon reduction targets in order to restrict temperature rises to two degrees Celsius compared to pre-industrial levels. To achieve these ambitious goals, nations have a variety of policy approaches at their disposal including feed in tariffs, fossil fuel restrictions, carbon capture and storage, renewable portfolio standards and carbon trading regimes. This study investigates carbon trading, and, using Japan as a case study assesses the economic feasibility and environmental efficiency of a carbon trading scheme underpinned by renewable energy deployment. The model employed uses an optimization approach, cognizant of technological, geographic and economic constraints. Findings identify that such an approach incorporating the 47 prefectures of Japan could engender a 42% reduction in emissions without resilience constraints and 34% incorporating a best-mix, resilient approach. Both approaches prove feasible at moderate carbon prices, considering international norms. The findings underpin policy implications for a future national Japanese emission trading scheme to improve previous single prefecture attempts which did not engender carbon trading. [ABSTRACT FROM AUTHOR]

When controlling a Dual-Active-Bridge (DAB) DC/DC converter, the high frequency terminal current is usually measured for use in the current feedback controller. In order to measure that current, a wide bandwidth sensor accompanied with high-speed amplifiers are required. Furthermore, a high Analog-to-Digital sampling rate is also necessary for sampling and processing the measured data. To avoid those expensive requirements, this paper proposes an alternative control method for the DAB converter. In the proposed method, the terminal current is estimated by a reduced-order proportional integral observer. A technique is also proposed to reduce the phase drift effect when the voltages at two terminals are not matched. Afterwards, a combined current feedforward—voltage feedback control system is developed to enhance the system dynamics and to regulate the output voltage. This control system needs only the information of the terminal voltages and no current sensor is required. Experimental results show that the observer can estimate the terminal current very quickly with the accuracy of more than 98 % . In addition, the output voltage is well regulated with a fluctuation of less than ± 2.6 % and a settling time of less than 6.5 ms in the presence of a 30 % load change. [ABSTRACT FROM AUTHOR]

Background: Mediastinal mature teratomas are rare tumors with diverse surgical approaches. The aim of this study is to review our experience of thoracoscopic surgery management in patients with teratomas.Methods: We retrospectively reviewed 28 consecutive patients with mediastinal mature teratomas who underwent thoracoscopic surgery at Viet Duc University Hospital from January 2008 to August2018. Patients were divided into 2 groups with 2 types of thoracoscopic surgery, closed thoracoscopic surgery (CTS) group and video-assisted thoracoscopic surgery (VATS) group. The selection of sugical approach was based on sizes, locations and characteristics of tumors. Post-operative outcomes were assessed and compared between these 2 groups.Results: There were 14 female and 14 male patients with a median age of 41.2 ± 13.8 years. A total of 22 teratomas were located on the right side of the chest cavity and 6 on the left side. We performed CTS in 21 patients (75%) and VATS in 7 patients (25%) for tumor resection. There were 3 cases (10.7%) required conversion to minithoracotomy (5 cm in incision length). Skin appendages accounted for the highest rate (96.4%) in pathology. There was no record of mortality or tumor recurrence detected by computerized tomography.Conclusion: A thoracoscopic surgery for a mediastinal mature teratoma was a feasible choice. Challenging factors such as large tumors, intraoperative bleeding and strong tumor cell adhesion were considered handling by conversion to mini-thoracotomy that could ensure safety procedures and complete removal of tumors. Extraction of tumor contents might be performed for patients with large mature cystic teratomas to facilitate thoracoscopic surgery. [ABSTRACT FROM AUTHOR]