Recent massive failures in the power grid acted as a wake up call for all utilities and consumers. This leads to aggressive pursue a more intelligent grid which addresses the concerns of reliability, efficiency, security, quality and sustainability for the energy consumers and producers alike. One of the many features of the smart grid is a discrete energy system consisting of distributed energy sources capable of operating independently from the main grid known as the microgrid. The main focus of the microgrid is to ensure a reliable and affordable energy security. However, it also can be vulnerable to cyber attack and we study the effect of price modification of electricity attack on the microgrid, given that they are able to operate independently from the main grid. This attack consists of two stages, 1) Separate the microgrids from the main grid (islanding) and 2) Failing the nodes inside the microgrid. Empirical results on IEEE Bus data help us evaluate our approach under various settings of grid parameters.
In this paper, we present a mitigation methodology that leverages battery energy storage system (BESS) resources in coordination with microgrid (MG) ancillary services to maintain power system operations during cyberattacks. The control of MG agents is achieved in a distributed fashion, and once a misbehaving agent is detected, the MG's mode supervisory controller (MSC) isolates the compromised agent and initiates self-healing procedures to support the power demand and restore the compromised agent. Our results demonstrate the practicality of the proposed attack mitigation strategy and how gri…
In this study, a cooperative game model is presented to schedule the day-ahead operation of multi-microgrid (MMG) systems. In the proposed model, microgrids are scheduled to achieve a global optimum for the cost of the multi-microgrid system. The minimum cost is achieved by transactions of microgrids with each other. Also, price-based demand response is implemented in the model to build a cost-reducing opportunity for consumers. Applying Shapley value, the optimum cost of the MMG system is fairly allocated between microgrids. To enhance the confidence level of results, data uncertainties are i…
Microgrids present an effective solution for the coordinated deployment of various distributed energy resources and furthermore provide myriad additional benefits such as resilience, decreased carbon footprint, and reliability to energy consumers and the energy system as a whole. Boosting the resilience of distribution systems is another major benefit of microgrids. This is because they can also serve as a backup power source when the utility grid operations are interrupted due to either high-probability low-impact events like a component failure or low-probability high-impact events - be it a…
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. …
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）
We consider the problem of energy management in microgrid networks. A microgrid is capable of generating a limited amount of energy from a renewable resource and is responsible for handling the demands of its dedicated customers. Owing to the variable nature of renewable generation and the demands of the customers, it becomes imperative that each microgrid optimally manages its energy. This involves intelligently scheduling the demands at the customer side, selling (when there is a surplus) and buying (when there is a deficit) the power from its neighboring microgrids depending on its current …
COVID19s widespread distribution is wreaking havoc on peoples lives all over the world. This pandemic has also had a significant impact on energy consumption. Its influence can be seen in the power systems operation and the market as well. The power consumers habits and demand curves have been changed at a breakneck pace. In this work, a one year mixed integer programming (MIP) problem has been developed to compare the power consumption between 2019 and 2020 in the United States as an example regarding the COVID19 pandemic effect in order to better prepare for possible similar future events. 1…
The Intergovernmental Panel on Climate Change proposes different mitigation strategies to achieve the net emissions reductions that would be required to follow a pathway that limits global warming to 1.5°C with no or limited overshoot. The transition towards a carbon-free society goes through an inevitable increase in the share of renewable generation in the energy mix and a drastic decrease in the total consumption of fossil fuels. Therefore, this thesis studies the integration of renewables in power systems by investigating forecasting and decision-making tools. Indeed, in contrast to conven…
Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI)（穆罕默德·本·扎耶德人工智能大学）
The increase in renewable energy on the consumer side gives place to new dynamics in the energy grids. Participants in a microgrid can produce energy and trade it with their peers (peer-to-peer) with the permission of the energy provider. In such a scenario, the stochastic nature of distributed renewable energy generators and energy consumption increases the complexity of defining fair prices for buying and selling energy. In this study, we introduce a reinforcement learning framework to help solve this issue by training an agent to set the prices that maximize the profit of all components in …
Renewable energy-based microgrids play a critical role in future smart grids. Due to the uncertainties of renewable generations, the microgrids face potential risk of load shedding during operation. To address this problem, we propose a contract-based approach to enhance the resilience of microgrids. Specifically, in the framework, the microgrids who may not be self-efficient to meet their local demands can purchase the needed power from their connected microgrids by signing a contract that specifies the power price in advance. We leverage a principal-agent model to capture the energy trading …
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 …
In this report, several control strategies for microgrids with renewable energy resources and battery energy storage systems are proposed. Renewable energy has the potential to reduce global carbon emissions, while higher penetration of renewable energy is hindered by the inherent variability and intermittency of renewable resources. This motivates the development of microgrids supplied by renewable energy resources. With proper control of storage units and communications with the energy market, the non-dispatchable energy can be regulated to reduce the difficulty of power scheduling in the gr…
Changchun Institute of Technology（长春工程学院）；National and Local Joint Engineering Research Center for Smart Distribution Network Measurement, Control and Safe Operation Technology（智能配电网测控与安全运行技术国家地方联合工程研究中心）；Qilu University of Technology (Shandong Academy of Sciences)（齐鲁工业大学（山东省科学院））；Institute of Oceanographic Instrumentation（海洋仪器研究所）
As an efficient way to integrate multiple distributed energy resources and the user side, a microgrid is mainly faced with the problems of small-scale volatility, uncertainty, intermittency and demand-side uncertainty of DERs. The traditional microgrid has a single form and cannot meet the flexible energy dispatch between the complex demand side and the microgrid. In response to this problem, the overall environment of wind power, thermostatically controlled loads, energy storage systems, price-responsive loads and the main grid is proposed. Secondly, the centralized control of the microgrid o…
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 …
To accommodate the advent of microgrids (MG) managing distributed energy resources (DER) in distribution systems, an interactive two-stage joint retail electricity market mechanism is proposed to provide an effective platform for these prosumers to proactively join in retail transactions. Day-ahead stochastic energy trading between the distribution system operator (DSO) and MGs is conducted in the first stage of a centralized retail market, where a chance-constrained uncertainty distribution locational marginal price (CC-UDLMP) containing the cost of uncertainty precautions is used to settle t…
Efforts to utilize 100% renewable energy in community microgrids require new approaches to energy markets and transactions to efficiently address periods of scarce energy supply. In this paper we contribute to the promising approach of peer-to-peer (P2P) energy trading in two main ways: analysis of a centralized, welfare-maximizing economic dispatch that characterizes optimal price and allocations, and a novel P2P system for negotiating energy trades that yields physically feasible and at least weakly Pareto-optimal outcomes. Our main results are 1) that optimal pricing is insufficient to indu…
Keele University（基尔大学）；Luxembourg Institute of Science and Technology（卢森堡科学技术研究院）
In this paper, multi-agent reinforcement learning is used to control a hybrid energy storage system working collaboratively to reduce the energy costs of a microgrid through maximising the value of renewable energy and trading. The agents must learn to control three different types of energy storage system suited for short, medium, and long-term storage under fluctuating demand, dynamic wholesale energy prices, and unpredictable renewable energy generation. Two case studies are considered: the first looking at how the energy storage systems can better integrate renewable energy generation unde…
