查看更多>>摘要：Energy management problem (EMP) has been a widely researched topic in optimal operation of Energy Internet (EI). However, the rapid growth in energy network scale and penetration of distributed renewable generations (DRGs) bring new challenges to energy management. Therefore, a digital twin (DT) based parallel energy management strategy is proposed for the large-scale EI which consists of We-energy (WE). Firstly, a parallel energy management framework is proposed. By establishing this triple parallel structure, states of energy networks can be observed realtimely, which enables flexible responses to fluctuations of DRGs and energy plug-and-play. Abandoned renewable energy is taken into account in the optimization model, which promotes the utilization of renewable energy. Then, a multi-timescale optimization strategy is proposed to handle different timescales of multi-energy networks. Furthermore, for better obtaining and processing information and avoiding dimensional curse, a DT based deep Q-learning algorithm (DQN) is proposed. Eventually, compared with the traditional benefit consensus based strategy, the simulation verifies the effectiveness of the DT based parallel energy management strategy.
查看更多>>摘要：The effective use of the flexibility sources of transmission and distribution networks necessitates smooth coordination between transmission and distribution system operators (TSO-DSO) as well as proper interfacing between the energy and flexibility markets. In this paper, mathematical centralized/decentralized optimization frameworks of flexibility market structures is proposed for four market mechanisms of a transmission-level centralized market, a local distribution- and centralized transmission-level market, a TSO priority market, and a TSO-DSO price equilibrium market. Further, prioritization mechanisms are developed by allocating ramp flexibilities in multi-interval day-ahead market clearing procedures for the wholesale (transmission level) and local markets (distribution level) to reduce the prediction error and improve the performance of the real-time flexibility market, which is a single-interval optimization market. Accordingly, the concurrent provision of the energy and flexibility requirements of the transmission and distribution networks is explored in a joint energy and flexibility day-ahead market. As a base case, the centralized market model does not prioritize TSO-DSO flexibility. The second market model gives the DSO priority in terms of providing flexibility. The DSO starts by using the resources of the distribution network. It then makes the upstream market an offer for the flexibility capacities of the remaining unused resources. In the third proposed market, the TSO receives priority in providing flexibility. The optimization frameworks proposed for the third market mechanisms are formulated as mixed-integer linear programming models (MILP). In addition, to ensure a higher resilience, a lower complexity of algorithms, and the possibility to better adapt to the efficient flexibility allocation in the TSO/DSO collaboration, an approach of the decentralized alternating direction method of multipliers (ADMM) in the decentralized optimization framework is performed to clear the proposed wholesale market while taking into account the local markets at the distribution level. Finally, to evaluate the proposed multi-level centralized/decentralized optimization frameworks, simulation results are performed on a modified IEEE 30-bus/118-bus transmission network with three/five IEEE 33-node distribution networks connected. In the case studies, various market clearing and prioritization mechanisms are implemented and evaluated through numerical simulations.
查看更多>>摘要：A microgrid's energy management system (EMS) is typically formulated as a deterministic optimization problem. However, more risks and uncertainties are emerging due to the increasing complexity of the power system structure with intelligent distributed energy integration. As a result, different types of risks must be considered while implementing the EMS to improve system resiliency. In this paper, a risk-based EMS is introduced for islanded microgrids. A scenario-based optimization method is formulated for the EMS, where each system component's probability of failure (PoF) is considered in each scenario. In addition, the loads are classified into critical, semi-critical, and non-critical loads to prioritize serving the essential loads during a shortage of generation resources in microgrids. The nonlinear power flow equation of the new problem formulation is relaxed into a convex form to reduce the computational burden. In detail, the system's resiliency is improved by employing three functionalities in the EMS as a preventive measure: a) prioritizing to serve the critical loads, b) lowering the total amount of load served to mitigate the impact of the failure of any system component, and c) reducing the dependency on the generation resources with high PoF. The proposed preventive and risk-based EMS is validated against IEEE-14, 30, and 118 bus systems. The results demonstrate that the proposed EMS sheds more loads than the base EMS, based on the PoF of each system component, due to the knowledge that risks of failure of any component may induce a cascading failure and even blackout if only base EMS is provided. Moreover, the proposed EMS precisely considers the criticality of loads for curtailment to match the available system resources. The curtailment indirectly improves the system's resiliency by increasing the chance of sur-vivability in the islanded mode with the probability of future component failure.
查看更多>>摘要：Energy management system gradually becomes an effective means in smart grid for paving the way to low carbon economy. However, information privacy, a large population of users, and the uncertainties of renewable energy sources and consumers' behaviors have led to significant challenges for energy management system operation in terms of security and robustness. To conquer such difficulties, a bilevel energy management scheme for the day-ahead optimal scheduling of multi-community system combined with distributed energy sources is first proposed. Meanwhile, uncertainties induced by renewable energy sources generation and load consumption are handled through adjustable robust optimization. Secondly, a non-cooperative multi-community aggregative game is formulated to describe the interaction of numerous residential users which are coupled through the dynamic electricity price. Then, to seek the ε-Nash Equilibrium of the proposed game, an improved decentralized iterative algorithm based on Mean-Field control and consensus is presented which is benchmarked with centralized algorithm and a decentralized optimization method based on quadratic programming. Since each player in the proposed algorithm does not need to exchange information directly with other players, the information privacy is fully preserved. Also, the convergence of the proposed algorithm is provided. Case studies of a five-community system are conducted and the comparison results show that our proposed approach has better performance in terms of computational time and electricity cost.
查看更多>>摘要：Driven by environmental policies and cost reduction efforts, renewable energy sources (RESs) become increasingly popular worldwide. It is a promising way to integrate dispersed RESs in the form of aggregators into the electricity market. This paper focused on collaborative bidding for an aggregator that integrates wind, solar, hydropower and energy storage system (ESS) in day-ahead (DA) and intraday (ID) markets. We propose a comprehensive data-driven based information gap theory-robust (DIGDT-RO) to handle the multi-stage optimal bidding for the RES aggregator. The RO approach is presented to model the uncertainty of ID electricity price, while uncertainties related to wind and solar generation are considered in DIGDT, which allows the aggregator to adopt risk-averse or risk-seeking strategies towards generation fluctuations. In DIGDT, the forecasted error of wind and solar is estimated by a novel confidence interval-based ambiguity set construction method (CIAS), and then the possibility of hydropower and ESS compensating for power deviation is modeled by chance constraints. The numerical results verify the good profitability and superior adaptability of the proposed model towards uncertainties.
Christian BuzzioYamil S. PoloniGerman G. OggierGuillermo O. Garcia...
109399.1-109399.10页
查看更多>>摘要：This paper presents a two-stage current-source DC-AC converter for grid-connected PV applications which is composed of an input step-up stage, followed by a step-down stage and an unfolding inverter. A decentralized control strategy of the DC-DC stage allows maximizing the renewable energy harvest using an Incremental Conductance MPPT algorithm and synthesizing an output current to be injected into the grid with low harmonic distortion. Double-loop PI controllers are used for the boost stage. The DC bus voltage of the buck stage is regulated using a PI controller, and an inner Proportional-Resonant (PR) controller tracks a sinusoidal reference. The PR controller proposed in this paper, includes a reduced number of resonant stages meeting the energy quality required by standards, which results in good stability margins. Finally, a SOGI-FLL algorithm synchronizes the inverter operation with the grid. Experimental results show an excellent dynamic response of the system, and the injected current complies with the IEEE Std. 1547-2018 specifications regarding harmonic content using a control law with a low computational burden.
查看更多>>摘要：The flexible traction power supply system (FTPSS) is a promising solution to solve the electric phase break and power quality problems existing in traditional traction power supply systems. To promote the balance of train power distribution among multiple substations, power sharing control is proposed by combining average power control and P-f and Q-V droops based on virtual power decoupling method. The active and reactive power is decoupled through introducing the impedance angle without knowing specific values of the line inductance and resistance. This system level control poses new challenges to the stability of the electric railway due to complex interactions between power electronic-based substations of the FTPSS. To address this issue, the frequency-domain model of the FTPSS with power sharing control is established. Then, the eigenvalue-based stability criterion is introduced to predict the stability of the interconnected system. In particular, to obtain how the power sharing control is sensitive to some controller/circuit parameters, a parameter-oriented stability analysis method is developed through assessing the influence of the key influential factors, including the time delay of wide-area communication, the controller parameters of the power sharing scheme, the circuit parameters, the length of the traction network and the train power requirement. The time-domain simulation and the downscaled prototype experiment are conducted to validate the effectiveness of the established model and the theoretical analysis. This lays the foundation for the design and stability analysis of the FTPSS.
查看更多>>摘要：Unknown integrated locations caused by unpredictable consumers' willingness and uncertainty in outputs induced by variable natural conditions are acknowledged challenges in the evaluation process of distributed generation (DG) hosting capacity (DGHC). For the former factor, this paper first proposes a novel assessment model to obtain the maximum feasible capacity no matter consumers in which locations have the possibility to stall DG. The decision variables of max operator and min operator are DG capacities and integrated locations respectively. Notably, unlike the previous works for one radial feeder, the interplay of DGHC in multi-feeders interconnected by tie lines and soft open points is also taken into consideration. After that, to combine uncertainties in integrated locations and outputs simultaneously, the above DGHC assessment model is further transformed into an improved information gap decision theory (IGDT) model with worst-case constraints for DG integrated locations. The specific solution procedure is also developed to solve this nonlinear IGDT model effectively. Case studies demonstrate that the evaluation results of DGHC based on this method always have the applicability and feasibility for any nodes in distribution system.
查看更多>>摘要：With the user-side heterogeneous power IoT devices (UPIDs) integrating into power systems, the cyber security of UPIDs brings a hidden danger to the power system due to their high-wattage terminals, and there is a new attack plan that can leverage such terminal botnets in order to manipulate the power demand, referred to as Manipulation of demand (MAD) attacks. To this end, a collaborative management mechanism for UPIDs operation is needed to mitigate the malicious impact of MAD attacks. Firstly, taking into account the vulnerability of the deployed cyber security defense measures, a cyber security vulnerability assessment method for UPIDs is proposed, which provides a criterion for the security control strategy. Besides, the security control strategy is constructed considering the security factors in the cyber domain and the physical domain, ensuring the reliability of power systems. The effectiveness of the proposed collaborative management mechanism is verified by simulations on a modified IEEE 14-bus system, highlighting the importance of the active defense scheme against MAD attacks.
查看更多>>摘要：This paper investigates the energy management of an Energy Internet (EI) that integrates multiple energy networks. Based on the structure of EI and the fluctuation of load, an optimal energy management model considering part of the load as time-varying factor is proposed. Under the influence of load, the actual energy management problem (EMP) is formulated as a time-varying optimization problem subject to a set of global and local constraints. Its optimal solution varies continuously with time, which leads to difficulties in obtaining optimal solutions by conventional algorithms. Consequently, to obtain better tracking performance, this paper proposes a distributed inertial projection neurodynamics algorithm (DIPNA) based on the Nesterov accelerated gradient descent method. This algorithm tracks the optimal solution of the EMP with a fast convergence rate O(1/t~2), providing a referenceable active power for each energy unit in real time. Finally, the performance evaluation results demonstrated the effectiveness and fast convergence of the proposed algorithm.
NETL
NSTL
Elsevier