In this paper, the short-term operation problem for a multiple energy carrier hybrid AC/DC microgrid is discussed. The hybrid microgrid consists of AC and DC parts, which are connected by means of inverters as well as natural gas network. The microgrid includes photovoltaic (PV) unit, wind turbine (WT), battery storage unit and gas-fired microturbines. A mixed integer linear programming is formed to minimize the overall cost of the microgrid including cost of natural gas supply, the value of lost load and battery degradation cost. The presented case study explored the importance of inverter characteristics and pipeline capacity.
This paper proposes a novel resilience index, a microgrid survivability rate (SR) under extreme events, and then proposes a novel Resilient Operational Planning (ROP) algorithm to maximize the proposed resilience index SR. The proposed ROP algorithm can incorporate predetermined inverter failure probabilities and generate multiple scenarios accordingly to optimize resilient operations during an extreme event. The implemented ROP algorithm consists of two main steps: (i) optimization of resilient operational planning, and (ii) preventive resilience enhancement if minimum SR is not met per the a…
Hierarchical microgrid control levels range from distributed device level controllers that run at a high frequency to centralized controllers optimizing market integration that run much less frequently. Centralized controllers are often subdivided into operational planning controllers that optimize decisions over a time horizon of one or several days, and real-time optimization controllers that deal with actions in the current market period. The coordination of these levels is of paramount importance. In this paper, we propose a value function-based approach as a way to propagate information f…
Smart programmable microgrids (SPM) is an emerging technology for making microgrids more software-defined and less hardware-independent such that converting distributed energy resources (DERs) to networked community microgrids becomes affordable, autonomic, and secure. As one of the cornerstones of SPM, this paper pioneers a concept of software-defined operation optimization for networked microgrids, where operation objectives, grid connection, and DER participation will be defined by software and plug-and-play, and can be quickly reconfigured, based on the development of modularized and tight…
This paper presents a supervised multi-agent safe policy learning (SMAS-PL) method for optimal power management of networked microgrids (MGs) in distribution systems. While conventional reinforcement learning (RL) algorithms are black-box decision models that could fail to satisfy grid operational constraints, our proposed method is constrained by AC power flow equations and other operational limits. Accordingly, the training process employs the gradient information of operational constraints to ensure that the optimal control policy functions generate safe and feasible decisions. Furthermore,…
As multi-microgrids become readily available, some limited models have been proposed that study operational and power quality constraints with local energy markets independently. This paper proposes a convex optimization model of an energy management system with operational and power quality constraints and interactions in a Local Energy Market (LEM) for unbalanced microgrids (MGs). The LEM consists of a pre-dispatch step and an energy transactions step (ETS). The ETS combines the MGs' objectives while considering two strategies: minimize the cost of buyers or maximize the revenue of sellers. …
Mobile energy storage systems (MESS) offer great operational flexibility to enhance the resiliency of distribution systems in an emergency condition. The optimal placement and sizing of those units are pivotal for quickly restoring the curtailed loads. In this paper, we propose a model for load restoration in a microgrid while concurrently optimizing the MESS routes required for the same. The model is formulated as a mixed integer second order cone program by considering the state of charge and evolution of the lower and upper bounds of battery capacities. Simulation results tested on the IEEE…
This paper proposes a novel hierarchically coordinated energy management system (EMS) for a regional community (e.g., residential area, campus, industrial park, etc.) comprising multiple small-scale microgrids (MGs) (e.g., houses, buildings, etc.). It aims to minimize the total operational cost of the MG community and maximize the individual benefit of each MG simultaneously. At the local level inside each MG, with the detailed modeling of various energy resources including photovoltaics (PVs), energy storages (ESs), electric vehicles (EVs) and dispatchable loads, the individual optimization p…
Risk analysis is currently not quantified in microgrid resource scheduling optimization. This paper conducts a conditional value at risk (cVaR) analysis on a grid-disconnected residential microgrid with distributed energy resources (DER). We assume the infrastructure to set up an ad-hoc microgrid is already in place for a residential neighborhood with power sources such as photovoltaic (PV), diesel, and battery energy storage system (BESS). With this scenario in mind, we solve day-ahead scheduling to optimally allocate various resources to match demand in scenarios where neighborhoods, especia…
This paper proposes a disturbance observer-based control (DOBC) method for frequency and voltage regulation of a solar photovoltaic (PV)-diesel generator(DG) based hybrid microgrid during islanding conditions. The DOBC is integrated as a feed-forward control to the synchronous generator based DG, which handles real-time power mismatches and regulates the microgrid frequency and voltage under islanding. To substantiate the operational robustness of the developed controller under real-time uncertainties arising due to variability in PV output and load, the controller has been tested under worstc…
Community-Centered Resilience Enhancement of Urban Power and Gas Networks via Microgrid Partitioning, Mobile Energy Storage, and Data-Driven Risk Assessment
The emerging paradigm of interconnected microgrids advocates energy trading or sharing among multiple microgrids. It helps make full use of the temporal availability of energy and diversity in operational costs when meeting various energy loads. However, energy trading might not completely absorb excess renewable energy. A multi-energy management framework including fuel cell vehicles, energy storage, combined heat and power system, and renewable energy is proposed, and the characteristics and scheduling arrangements of fuel cell vehicles are considered to further improve the local absorption …
Microgrids are being increasing deployed to improve the operational flexibility, resilience, coordinated-energy management capabilities, self-adequacy, and increased reliability of power systems. This strong market growth is also driven by advances in power electronics, improved control systems, and the rapidly falling price and increased adoption of distributed energy generation technologies, like solar photovoltaics and storage. In the event of grid outages, microgrids can provide a backup source of power; providing resilience to the critical loads; however, this requires that the microgrid …
University of Tennessee, Knoxville（田纳西大学诺克斯维尔分校）；Naval Postgraduate School（海军研究生院）
Microgrids have more operational flexibilities as well as uncertainties than conventional power grids, especially when renewable energy resources are utilized. An energy storage based feedback controller can compensate undesired dynamics of a microgrid to improve its stability. However, the optimal feedback control of a microgrid subject to a large disturbance needs to solve a Hamilton-Jacobi-Bellman problem. This paper proposes a machine learning-based optimal feedback control scheme. Its training dataset is generated from a linear-quadratic regulator and a brute-force method respectively add…
Demand Response (DR) has a widely recognized potential for improving grid stability and reliability while reducing customers energy bills. However, the conventional DR techniques come with several shortcomings, such as inability to handle operational uncertainties and incurring customer disutility, impeding their wide spread adoption in real-world applications. This paper proposes a new multiagent Reinforcement Learning (RL) based decision-making environment for implementing a Real-Time Pricing (RTP) DR technique in a prosumer dominated microgrid. The proposed technique addresses several short…
An Overview of the Prospects and Challenges of Using Artificial Intelligence for Energy Management Systems in Microgrids
Department of Electrical Engineering, University of Sharjah（电气工程系，谢贾哈大学）；Department of Electric, Electronic and Computer Engineering, University of Pretoria（电气电子与计算机工程系，普里蒂亚大学）
Universitat Pompeu Fabra（庞培法布拉大学）；University of Liège（列日大学）
The lifelong control problem of an off-grid microgrid is composed of two tasks, namely estimation of the condition of the microgrid devices and operational planning accounting for the uncertainties by forecasting the future consumption and the renewable production. The main challenge for the effective control arises from the various changes that take place over time. In this paper, we present an open-source reinforcement framework for the modeling of an off-grid microgrid for rural electrification. The lifelong control problem of an isolated microgrid is formulated as a Markov Decision Process…
Grid-forming inverter-based autonomous microgrids present new operational challenges as the stabilizing rotational inertia of synchronous machines is absent. The design of efficient control policies for grid-forming inverters is, however, a non-trivial problem where multiple performance objectives need to be satisfied, including voltage/frequency regulation, current limiting capabilities, as well as active power sharing and a scalable operation. We propose in this paper a novel control architecture for frequency and voltage control which allows current limitation via an inner loop, active powe…
