Article
Green & Sustainable Science & Technology
Md Juel Rana, Forhad Zaman, Tapabrata Ray, Ruhul Sarker
Summary: This study introduces a new three-layer real-time scheduling framework for community microgrids (CMG), which incorporates a feedback mechanism between scheduling layers to generate cost-effective schedules and better handle variations in renewable energy generation and demand within the CMG. A heuristic-based differential evolution (DE) algorithm is proposed to solve the real-time scheduling problem of CMG, providing feasible solutions with lower computational effort. Experimental results confirm the efficacy of the proposed scheduling approach over existing methods.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Engineering, Electrical & Electronic
Ningchao Gao, David Wenzhong Gao, Xin Fang
Summary: This paper proposes an integrated alternating current optimal power flow-based generation scheduling and time domain simulation framework to investigate the economic and reliability perspectives of managing the real-time power imbalance caused by the deployment of variable renewable energy. The study analyzes the impacts of adaptive frequency regulation and the requirements for secondary frequency regulation on generation cost and frequency response performance. The results demonstrate that an adaptive frequency regulation with a 5-minute economic dispatch interval is more appropriate and efficient in improving the frequency response and reducing generation cost with renewable energy.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Energy & Fuels
Ahmad Alzahrani, Khizar Sajjad, Ghulam Hafeez, Sadia Murawwat, Sheraz Khan, Farrukh Aslam Khan
Summary: Real-time energy optimization is crucial for load scheduling, cost reduction, demand and supply balance, and power system reliability. However, the unpredictable nature of renewable energy and electric loads poses challenges for real-time optimization. The Lyapunov optimization technique has emerged as a solution to this problem. This research investigates a smart home with various loads and renewable energy sources in a grid-connected mode to optimize cost and energy storage using the Lyapunov optimization technique.
Article
Computer Science, Hardware & Architecture
Kevin Zagalo, Yasmina Abdeddaim, Avner Bar-Hen, Liliana Cucu-Grosjean
Summary: In this paper, it is proven that a mean system utilization smaller than one is a necessary condition for the feasibility of real-time systems. Stable systems, which have two distinct states, a transient state and a steady-state, are defined as systems where the same distribution of response times is repeated infinitely for each task. The Liu and Layland theorem is proved to hold for stable probabilistic real-time systems with implicit deadlines, and an analytical approximation of response times for each of those two states is provided, along with a bound of the instant when a real-time system becomes steady.
IEEE TRANSACTIONS ON COMPUTERS
(2023)
Article
Computer Science, Artificial Intelligence
Sajjad Saeedi, S. M. Hassan Hosseini
Summary: This paper analyzes the stochastic synchronization of wind and solar energy using an energy storage system based on real-time pricing, as well as the potential benefits of demand response programming. The uncertainty of renewable energies, loads, and prices is addressed through optimal bidding propositions that consider wind power, solar system, and energy storage system. The use of batteries as a device to compensate for fluctuations and mitigate uncertainty is highlighted. The paper presents a model that enables retailers to exploit the advantages of the demand response program and real-time pricing system, while ensuring fair prices through regulating constraints. The proposed solution is implemented using a nonlinear integer programming method and provides valuable information for optimizing electricity trading strategies.
Article
Engineering, Electrical & Electronic
Kotakonda Chakravarthi, Pratyasa Bhui, Nalin Kumar Sharma, Bikash Chandra Pal
Summary: This paper proposes a disturbance compensation based Model Predictive Control (MPC) strategy to regulate the line power flow in real-time by re-dispatching generators and battery energy storage systems (BESS). The control strategy has been validated and shown to have better performance compared to the existing technique.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Energy & Fuels
Hui Hou, Zhihua Wang, Tingting Hou, Rengcun Fang, Jinrui Tang, Changjun Xie
Summary: This research establishes a hierarchical scheduling model for microgrid, which is 100% powered by renewable energy and considers the demand response characteristics of electric vehicle users. It includes an EV layer and a REMG layer, and achieves system optimization and cost reduction by adjusting the load and various energy outputs.
Article
Energy & Fuels
Xiaoyu Wang, Zibo Wang, Yunfei Mu, Youjun Deng, Hongjie Jia
Summary: This paper proposes an efficient rolling horizon optimization-based real-time operation strategy for prosumers to minimize the total operational cost in one day, considering the thermal comfort demand. Through a case study of 94 prosumers in an urban community microgrid on a typical summer day, the simulation results show that the proposed strategy can effectively utilize the flexible energy resources of prosumers, achieve local energy supply-demand balance, improve operational economics, and reduce the negative impact of day-ahead forecasting errors on intra-day operation.
Article
Construction & Building Technology
Giovanni Tumminia, Francesco Sergi, Davide Aloisio, Sonia Longo, Maria Anna Cusenza, Francesco Guarino, Salvatore Cellura, Marco Ferraro
Summary: The study introduces a novel design approach that integrates load match/grid interaction issues and environmental impacts in early design stages to find trade-offs. Results show that an oversized PV system alone may not be the best solution for reducing environmental impact in the building sector, while adding storage systems can decrease grid dependency and increase environmental benefits from renewable energy sources. Conflicting results across specific impact categories highlight the need for a holistic approach in considering different domains and indicators to support the transition towards low-carbon energy technologies.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Construction & Building Technology
Md Alamgir Hossain, Ripon K. Chakrabortty, Michael J. Ryan, Hemanshu Roy Pota
Summary: This paper investigates energy management schemes under uncertain environments and proposes a scheduling scheme to minimize the operating cost of a grid-connected microgrid. The study demonstrates that the proposed modified particle swarm optimization (MPSO) algorithm outperforms other recent algorithms in solving real-time scheduling problems. The results indicate that the MPSO algorithm can save 16.80% operational cost compared to the PSO algorithm, showing significant improvements in cost reduction.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Mathematics
Luyu Wang, Houbo Xiong, Yunhui Shi, Chuangxin Guo
Summary: This paper proposes a multi-stage robust real-time economic dispatch model (MRRTD) for power systems. The MRRTD uses the dynamic form of multi-stage robust optimization as the framework to simulate the operation of temporally coupled equipment, such as utility-level energy storage systems. The effectiveness of the proposed model and solution algorithm is demonstrated through simulation results from benchmark test cases.
Article
Engineering, Electrical & Electronic
Mrityunjay Kumar Mishra, S. K. Parida
Summary: This article introduces two rolling horizon algorithms to solve the demand-side management problem in real time. The algorithms consist of two steps and use a non-cooperative game-theoretic approach to obtain the solution for considered time-slots. The convergence criteria for the formulated problem are derived. The impact of adding discomfort cost on system parameters is analyzed.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Engineering, Electrical & Electronic
Jiamei Zhang, Kai Sun, Canbing Li, Hui Liu, Wentao Huang, Bin Zhou, Xiaochao Hou
Summary: This paper proposes a novel optimal scheduling model for hydrogen generation and storage plants powered by renewable energy. The model aims to enhance the economic feasibility of investment by ensuring a steady and accessible hydrogen supply. Through detailed analysis of the hydrogen generation, processing, and storage process, the model considers the constraints and energy conversion relationships. A multi-energy coupling matrix is developed to represent the interaction of different system modules, and a multi-product optimal scheduling algorithm is formulated to maximize profit. The algorithm incorporates demand response signals and considers uncertainty to further improve operation revenue.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2023)
Article
Energy & Fuels
Peng Qiu, Yi Lu, Wenchao Zhang, Chao Ding
Summary: This paper proposes a real-time low-carbon scheduling method for wind-thermal-hydro-storage integrated systems to address the source-load uncertainty. The method neutralizes the power imbalance caused by uncertainty through the synergetic linear decision of multiple resources. To deal with the source-load uncertainty, a stochastic robust optimization is introduced, which establishes system constraints for resilience operation and optimizes the expected operation cost based on empirical uncertainty distribution for economic efficiency. Moreover, a multi-point estimation method is applied for precise and quick formulation of the expected operation cost.Using dual theory, the proposed real-time power scheduling is formulated as a mixed-integer bilinear constrained programming. A multi-step sequential convexified solution is developed to solve the complex scheduling problem, which linearizes the bilinear constraints and relaxes the state variables of energy storages with an estimation-correction strategy. The superiority of the proposed scheduling method and convexified solution is demonstrated through case studies.
FRONTIERS IN ENERGY RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Chunyang Liu, Hengxu Zhang, Mohammad Shahidehpour, Quan Zhou, Tao Ding
Summary: This paper proposes a two-layer real-time scheduling model for optimizing microgrid operations based on future cost function. The effectiveness of the model is validated through experiments.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)