با سلام خدمت کاربران عزیز، به اطلاع می رساند ترجمه مقالاتی که سال انتشار آن ها زیر 2008 می باشد رایگان بوده و میتوانید با وارد شدن در صفحه جزییات مقاله به رایگان ترجمه را دانلود نمایید.
A review of hierarchical control for building microgrids
مروری بر کنترل سلسله مراتبی برای میکرو گریدهای ساختمان-2020
Building microgrids have emerged as an advantageous alternative for tackling environmental issues while enhancing the electricity distribution system. However, uncertainties in power generation, electricity prices and power consumption, along with stringent requirements concerning power quality restrain the wider development of building microgrids. This is due to the complexity of designing a reliable and robust energy management system. Within this context, hierarchical control has proved suitable for handling different requirements simultaneously so that it can satisfactorily adapt to building environments. In this paper, a comprehensive literature review of the main hierarchical control algorithms for building microgrids is discussed and compared, emphasising their most important strengths and weaknesses. Accordingly, a detailed explanation of the primary, secondary and tertiary levels is presented, highlighting the role of each control layer in adapting building microgrids to current and future electrical grid structures. Finally, some insights for forthcoming building prosumers are outlined, identifying certain barriers when dealing with building microgrid communities.
Index Terms: Electricity market | Energy management system | Optimisation algorithms | Renewable energy source | Prosumer
An internet of energy framework with distributed energy resources, prosumers and small-scale virtual power plants: An overview
اینترنت چارچوب انرژی با منابع انرژی توزیع شده ، پیشرانها و نیروگاه های مجازی در مقیاس کوچک: یک مرور کلی-2020
Current power networks and consumers are undergoing a fundamental shift in the way traditional energy systems were designed and managed. The bidirectional peer-to-peer (P–P) energy transactions pushed passive consumers to be prosumers. The future smart grid or the internet of energy (IoE) will facilitate the coordination of all types of prosumers to form virtual power plants (VPP). The paper aims to contribute to this growing area of research by accumulating and summarizing the significant ideas of the integration of distributed prosumers and small-scale VPP to the internet of energy (IoE). The study also reports the characteristics of IoE in comparison to the traditional grid and offers some valuable insights into the control, management and optimization strategies of prosumers, distributed energy resources (DERs) and VPP. As bidirectional P–P energy transaction by the prosumers is a crucial element of IoE, their management strategies including various demand-response approach at the customers’-levels are systematically summarized. The integration of DERs and prosumers to the VPP considering their functions, infrastructure, type, control objectives are also reviewed and summarized. Various optimization techniques and algorithm, and their objectives functions and the types of mathematical formulation that are used to manage the DERs and VPP are discussed and categorized systematically. Finally, the factors which affect the integration of DERs and prosumers to the VPP are identified.
Keywords: Bidirectional energy transactions | Distributed energy resources | Energy management | Internet of energy | Optimization techniques | Prosumers | Virtual power plant
Optimization strategies for Microgrid energy management systems by Genetic Algorithms
استراتژی های بهینه سازی برای سیستم های مدیریت انرژی میکرو گرید توسط الگوریتم های ژنتیک-2020
Grid-connected Microgrids (MGs) have a key role for bottom-up modernization of the electric distribution network forward next generation Smart Grids, allowing the application of Demand Response (DR) services, as well as the active participation of prosumers into the energy market. To this aim, MGs must be equipped with suitable Energy Management Systems (EMSs) in charge to efficiently manage in real time internal energy flows and the connection with the grid. Several decision making EMSs are proposed in literature mainly based on soft computing techniques and stochastic models. The adoption of Fuzzy Inference Systems (FISs) has proved to be very successful due to their ease of implementation, low computational run time cost, and the high level of interpretability with respect to more conventional models. In this work we investigate different strategies for the synthesis of a FIS (i.e. rule based) EMS by means of a hierarchical Genetic Algorithm (GA) with the aim to maximize the profit generated by the energy exchange with the grid, assuming a Time Of Use (TOU) energy price policy, and at the same time to reduce the EMS rule base system complexity. Results show that the performances are just 10% below to the ideal (optimal) reference solution, even when the rule base system is reduced to less than 30 rules.
Keywords: Microgrids | Genetic algorithms | Fuzzy systems | Energy management systems
Ensuring the reduction in peak load demands based on load shifting DSM strategy for smart grid applications
تضمین کاهش تقاضای بار اوج بر اساس تغییر استراتژی DSM برای کاربردهای شبکه هوشمند-2020
In recent year the concept of prosumers (energy producer as well as the consumer) is becoming more popular, and on the other side, demand response has gained attention especially in the smart and micro grid systems. In such power networks, the behaviors of prosumers are highly variable due to many factors and few are price depended, incentive depended etc., Due to the highly dynamic nature of the prosumers, the peak load management is becoming crucial in the power system operation and control especially in smart grids, in which demand side management (DSM) application thought to be useful. This paper presents a simulation study on the role of DSM in the peak load management for a residential community. Here, load shitting-based DSM technique is used. This study considered the daily consumption patterns (hour wise) of electricity using the four types of electric loads. Results showed a considerable decrease in the peak load when compared to the load patterns before applying DSM. The average demand per day in summer is 4.521 kW, and in winter is 3.871 kW. The summary of peak load demands per day in kW without DSM are 14.712 kW, and 18.18 kW for summer and winter respectively. With the load shifting based DSM technique, the peak load per day are reduced to 9.6 kW in the summer season and 9.672 kW in the winter season.
Keywords: Smart grid | demand side management | load shifting | peak loads | load management | energy management
Hierarchical system model for the energy management in the smart grid: A game theoretic approach
مدل سیستم سلسله مراتبی برای مدیریت انرژی در شبکه هوشمند: یک رویکرد تئوری بازی-2020
Nowadays, Demand Side Management (DSM) in the Smart Grids (SG) opens new perspectives on the management of the prosumers’ demands. The use of Information and Communication Technologies (ICT) empowers SG with the capability of supporting two-way energy and information flows, facilitating the integration of renewable energy into the grid and empowering the consumer with tools for optimizing energy consumption and costs. Many researches have highlighted on the active role of consumers in the DSM. However, they limited their role to either negotiating with the providers about the unit energy price, or trading their surplus of energy, if any, with other prosumers or providers. In this paper, we introduce a hierarchical system model where multiple providers and prosumers interact to define the best price and demands. We highlight the capacity of a prosumer to produce energy and minimize the dependency on the providers in the overall proposed energy management. The latter will be able to maximize his satisfaction by trading energy, first, with other prosumers with a suitable price, and by interacting with the providers, if any remaining energy needed, in a distributed way. Hence, we optimize the price and demands while considering multiple constraints and different providers and prosumers by establishing a Stackelberg game to model two types of interactions: (1) prosumer–prosumer and (2) provider–consumer. We prove that a unique equilibrium solution exists and simulation results show that our proposed approach optimizes energy consumption and price.
Keywords:Demand side management | Energy trading | Prosumers | Providers | Game theory
The optimal management of the prosumer’s resources via stochastic programming
مدیریت بهینه منابع prosumer از طریق برنامه نویسی تصادفی-2020
This paper deals with the optimal home energy management problem faced by a smart prosumer equipped with PV panels and storage systems. The stochastic programming framework is adopted with the aim of explicitly accounting for the inherent uncertainty affecting the main problem parameters (i.e. generation from renewable energy sources and demands). The problem provides the prosumer with the optimal scheduling of the shiftable loads and operations of the available storage systems that minimizes the expected overall electricity cost. Preliminary results, collected on three different categories of residential prosumers, have shown the effectiveness of the proposed approach in terms of cost saving.
Keywords: Home energy management systems | Optimal scheduling | Renewable energy | Stochastic programming | Storage device
Energy management for aggregate prosumers in a virtual power plant: A robust Stackelberg game approach
مدیریت انرژی برای پیشرانان کل در نیروگاه مجازی: یک رویکرد بازی Stackelberg قوی-2020
In this paper, a novel two-stage robust Stackelberg game is proposed to solve the problem of day-ahead energy management for aggregate prosumers considering the uncertainty of intermittent renewable energy output and market price. The aggregate prosumers operate in the form of virtual power plant (VPP) and participate in dayahead (DA) and real-time (RT) market transactions. As the initiator and leader of the VPP, the superior prosumer with thermal units and interruptible loads is responsible for formulating the internal price mechanism and energy management strategy of the aggregate prosumers. Inferior prosumers, including renewable energy and shiftable loads, are responsible for providing renewable energy output information and responding to the price signals from the superior prosumer. The two-stage robust Stackelberg game model is linearized and solved by column-and-constraint generation (CC&G) algorithm. In addition, the thermal unit operating in the automatic generation control (AGC) mode ensures the realization of real-time optimal scheduling of aggregate prosumers for the entire dispatching cycle. Simulation results prove the rationality and validity of the proposed model and method.
Keywords: Energy management | Aggregate prosumers | Virtual power plant | Two-stage robust Stackelberg game | Column-and-constraint generation algo
FaaVPP: Fog as a virtual power plant service for community energy management
FaaVPP: مه به عنوان یک سرویس نیروگاه مجازی برای مدیریت انرژی جامعه-2020
The fossil fuel based power generators emit CO2 and expensive electricity. In this paper, fog as a virtual power plant (FaaVPP) is proposed to integrate power of distributed renewable power generators and the utility for a community. A prosumer–consumer and service providing company oriented linear model is proposed to minimize power consumption cost for prosumers and maximize profit for the company. The mathematical proof of linear model validates the significance for service provider and energy users. Moreover, outcome of case studies advocate the efficiency of the model. Efficient resource utilization techniques of fog resources ensure the near-real time service provision to the community. In the paper, effects of resource utilization techniques e.g., processing time (PT), response time (RT), computing cost and energy consumed by the resources are also analyzed.
Keywords: Virtual power plant | Fog as a service | FaaVPP | Computational energy | Response time | Processing time | Virtual retail energy provider
A residential energy management system with bi-level optimization-based bidding strategy for day-ahead bi-directional electricity trading
یک سیستم مدیریت انرژی مسکونی با استراتژی مناقصه مبتنی بر بهینه سازی دو سطح برای تجارت برق دو طرفه پیش رو-2020
Bi-directional electricity trading of demand response (DR) and transactive energy (TE) frameworks allows the traditionally passive end-users of electricity to play an active role in the local power balance of the grid. Appropriate building energy management systems (BEMSs), coupled with an optimized bidding strategy, can provide significant cost savings for prosumers (consumers with on-site power generation and/or storage facility) when they participate in such bi-directional trading. This paper presents a BEMS with an optimization-based scheduling and bidding strategy for small-scale residential prosumers to determine optimal day-ahead energyquantity bids considering the expected cost of real-time imbalance trading under uncertainty. The proposed scheduling and bidding strategy is formulated as a stochastic bi-level minimization problem that determines the day-ahead energy-quantity bids by minimizing the energy cost in the upper level considering expected cost of uncertainty, whereas a number of lower-level sub-problems ensure optimal operation of building loads and distributed energy resources (DERs) for comfort reservation, minimization of consumers’ inconveniences and degradation of residential storage units. A modified decomposition method is used to reformulate the nonlinear bi-level problem as a mixed-integer linear programming (MILP) problem and solved using ‘of the shelf’ commercial software. The effectiveness of the proposed BEMS model is verified via case studies for a residential prosumer in Sydney, Australia with real measurement data for building energy demand. The efficacy of the proposed method for overall financial savings is also validated by comparing its performance with state-of-theart day-ahead scheduling strategies. Case studies indicate that the proposed method can provide up to 51% and 22% cost savings compared to inflexible non-optimal scheduling strategies and deterministic optimization-based methods respectively. Results also indicate that the proposed method offers better economic performance than standard cost minimization models and multi-objective methods for simultaneous minimization of energy cost and user inconveniences.
Keywords: Demand response | Building energy management system | Distributed energy resources | Mixed-integer programming | Bi-level optimization
A distributed Peer-to-Peer energy transaction method for diversified prosumers in Urban Community Microgrid System
روش توزیع انرژی همتا به همتا برای پیشرانهای متنوع در سیستم ریز شبکه جامعه شهری توزیع شده -2020
As massive integration of Distributed Energy Resources (DERs), the role of end-users in the Urban Community Microgrid System (UCMS) has transformed from traditional consumers into prosumers with capabilities of both energy production and consumption. The exchange of energy between autonomous microgrid prosumers can be achieved with the introduction of Peer-to-Peer (P2P) energy transaction, promoting the efficient allocation of energy in the UCMS. However, the existing centralized P2P energy transaction approaches require microgrid transaction brokers to obtain prosumers’ private data, including energy resource configuration, operation status, and energy production/consumption schedule. With the enhancement of prosumers’ awareness of privacy protection, it will be increasingly more difficult for the brokers to obtain such private data in practical application scenarios, resulting in obstacles on the implementation of such centralized approach. Thus, a novel distributed P2P energy transaction method based on the double auction market is proposed in this paper. Prosumers first generate the information of energy supply and demand autonomously utilizing distributed energy management model, then set the price targeting profit maximization, and finally initiate P2P energy transaction mutually in the double auction energy market. Compared with the existing centralized approaches, the method proposed in this paper can achieve the coordination and complementarity of energy in the UCMS, promoting economic benefit, energy self-sufficiency, and renewable energy self-consumption without sacrificing privacy preservation and robustness.
Keywords: Urban Community Microgrid System | Distributed Peer-to-Peer (P2P) energy | transaction | Autonomous energy management | Autonomous pricing | Supply-demand coordination