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Energy management and operational planning of renewable energy resources-based microgrid with energy saving

ELECTRIC POWER SYSTEMS RESEARCH 2023年 214卷

作者： Hai, Tao Zhou, Jincheng Muranaka, Kengo Qiannan Normal Univ National Sch Comp & Informat Duyun 558000 Guizhou Peoples R China Key Lab Complex Syst & Intelligent Optimizat Guiz Duyun 558000 Guizhou Peoples R China Univ Teknol MARA Inst Big Data Analyt & Artificial Intelligence IB Shah Alam Selangor 40450 Malaysia Solar Energy & Power Elect Co Ltd Tokyo Japan

Energy resource scheduling is one of the major problems in power systems. This issue has become even more significant as renewable sources with intermittent power output are becoming more and more prevalent. Due to their low environmental impact and low operating costs, renewable energy sources (RESs) have attracted inoterest. The excess power generated by such generation methods may be a negative that affects power systems, hence issues relating to such systems should be properly handled. The optimal operation of a microgrid (MG) with several distributed generation (DG) units and uncertain behavior of RESs is suggested in this research using a stochastic optimization approach. So, for an MG fitted with a solar photovoltaic (PV) unit, this research prooposes a day-ahead scheduling paradigm. In this regard, the effects of various climatic circumstances on the power production of the PV unit and the optimal scheduling of the MG have been examined in this research. In order to achieve this, statistics on solar irradiance were extracted from four distinct days from each of the four seasons. The single-objective optimization framework used to design the scheduling problem states that the objective function should be to minimize the total operating cost across the scheduling period. The aforementioned day-ahead scheduling problem can be solved by the "hybrid whale optimization algorithm and pattern search (HWOA-PS)" optimization algorithm, while both renewable and nonrenewable generating units, as well as an energy storage system are present. In order to confirm the higher performance of the recommended approach, a thorough comparison between the Hybrid WOA-PS algorithm and a few well-known optimization algorithms has also been conducted.

关键词： Resource scheduling Hybrid HWOA-PS algorithm stochastic programming Energy storage systems Photovoltaic

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AI-Based Scheduling Models, Optimization, and Prediction for Hydropower Generation: Opportunities, Issues, and Future Directions

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ENERGIES 2023年第8期16卷

作者： Villeneuve, Yoan Seguin, Sara Chehri, Abdellah Univ Quebec Chicoutimi Grp Res Decis Anal GERAD Chicoutimi PQ G7H 2B1 Canada Royal Mil Coll Canada Dept Math & Comp Sci Kingston ON K7K 7B4 Canada

Hydropower is the most prevalent source of renewable energy production worldwide. As the global demand for robust and ecologically sustainable energy production increases, developing and enhancing the current energy production processes is essential. In the past decade, machine learning has contributed significantly to various fields, and hydropower is no exception. All three horizons of hydropower models could benefit from machine learning: short-term, medium-term, and long-term. Currently, dynamic programming is used in the majority of hydropower scheduling models. In this paper, we review the present state of the hydropower scheduling problem as well as the development of machine learning as a type of optimization problem and prediction tool. To the best of our knowledge, this is the first survey article that provides a comprehensive overview of machine learning and artificial intelligence applications in the hydroelectric power industry for scheduling, optimization, and prediction.

关键词： hydropower hydropower scheduling machine learning optimization stochastic programming linear regression random forest reinforcement learning deep neural networks

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Electric sector investments under technological and policy-related uncertainties: a stochastic programming approach

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CLIMATIC CHANGE 2013年第2期121卷 143-160页

作者： Bistline, John E. Weyant, John P. Stanford Univ Dept Management Sci & Engn Stanford CA 94305 USA

Although emerging technologies like carbon capture and storage and advanced nuclear are expected to play leading roles in greenhouse gas mitigation efforts, many engineering and policy-related uncertainties will influence their deployment. Capital-intensive infrastructure decisions depend on understanding the likelihoods and impacts of uncertainties such as the timing and stringency of climate policy as well as the technological availability of carbon capture systems. This paper demonstrates the utility of stochastic programming approaches to uncertainty analysis within a practical policy setting, using uncertainties in the US electric sector as motivating examples. We describe the potential utility of this framework for energy-environmental decision making and use a modeling example to reinforce these points and to stress the need for new tools to better exploit the full range of benefits the stochastic programming approach can provide. Model results illustrate how this framework can give important insights about hedging strategies to reduce risks associated with high compliance costs for tight CO2 caps and low CCS availability. Metrics for evaluating uncertainties like the expected value of perfect information and the value of the stochastic solution quantify the importance of including uncertainties in capacity planning, of making precautionary low-carbon investments, and of conducting research and gathering information to reduce risk.

关键词： stochastic programming

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Hybrid IGDT-stochastic self-scheduling of a distributed energy resources aggregator in a multi-energy system

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ENERGY 2023年 265卷

作者： Vahid-Ghavidel, Morteza Shafie-khah, Miadreza Javadi, Mohammad S. Santos, Sergio F. Gough, Matthew Quijano, Darwin A. Catalao, Joao P. S. Inst Syst & Comp Engn Technol & Sci INESC TEC Porto Portugal Univ Porto FEUP Fac Engn Porto Portugal Univ Vaasa Sch Technol & Innovat Vaasa 65200 Finland Portucalense Univ Infante D Henrique UPT Porto Portugal REMIT Porto Portugal Univ Estadual Paulista UNESP Ilha Solteira Brazil

The optimal management of distributed energy resources (DERs) and renewable-based generation in multi -energy systems (MESs) is crucial as it is expected that these entities will be the backbone of future energy sys-tems. To optimally manage these numerous and diverse entities, an aggregator is required. This paper proposes the self-scheduling of a DER aggregator through a hybrid Info-gap Decision Theory (IGDT)-stochastic approach in an MES. In this approach, there are several renewable energy resources such as wind and photovoltaic (PV) units as well as multiple DERs, including combined heat and power (CHP) units, and auxiliary boilers (ABs). The approach also considers an EV parking lot and thermal energy storage systems (TESs). Moreover, two demand response (DR) programs from both price-based and incentive-based categories are employed in the microgrid to provide flexibility for the participants. The uncertainty in the generation is addressed through stochastic pro-gramming. At the same time, the uncertainty posed by the energy market prices is managed through the application of the IGDT method. A major goal of this model is to choose the risk measure based on the nature and characteristics of the uncertain parameters in the MES. Additionally, the behavior of the risk-averse and risk -seeking decision-makers is also studied. In the first stage, the sole-stochastic results are presented and then, the hybrid stochastic-IGDT results for both risk-averse and risk-seeker decision-makers are discussed. The pro-posed problem is simulated on the modified IEEE 15-bus system to demonstrate the effectiveness and usefulness of the technique.

关键词： Demand response Distributed energy resources Microgrid Multi -energy system stochastic programming

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A variant SDDP approach for periodic-review approximately optimal pricing of a slow-moving a item in a duopoly under price protection with end-of-life return and retail fixed markdown policy

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EXPERT SYSTEMS WITH APPLICATIONS 2023年 212卷

作者： Yildiz, Baris Sutcu, Muhammed Abdullah Gul Univ Ind Engn Dept TR-38170 Kayseri Turkiye

In this paper, we examine a selling environment where a manufacturer-controlled retailer and an independent retailer sell a slow-moving A item. The manufacturer offers the independent retailer a price protection contract stipulating that the manufacturer reimburses the independent retailer in case of a reduction in the wholesale price. The price set by the independent retailer is assumed to be determined by Retail Fixed Markdown (RFM) policy. The manufacturer also offers the independent retailer a special discount rate for the replenishment orders and the retailers are assumed to follow (R, S) inventory replenishment policy. The manufacturer adopts a periodic-review pricing strategy and the mean demand observed by each retailer in a given period depends on the prices. We also take the customers choosing no-purchase option into account. We employ multinomial logit (MNL) models to forecast customers' preferences based on retail prices. The retailers' market shares are esti-mated by customized choice probability functions. We propose stochastic programming models to determine the manufacturer's pricing strategy. Then, we propose a variant stochastic Dual Dynamic programming (SDDP) algorithm to determine the manufacturer's approximately optimal pricing strategy by getting around three curses of dimensionality. Then, we move on to the observations on the impact of four critically important contractual parameters on the price, the market shares and the expected total net profits and finally discuss some possible approaches for the selection of the best compromise values of those contractual parameters.

关键词： Price protection End -of -life returns Price commitment policies Retail fixed markdown policy stochastic dual dynamic programming stochastic programming

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stochastic planning for low-carbon building integrated energy system considering electric-heat-V2G coupling

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2023年 151卷

作者： Xiong, Zuxun Shen, Xinwei Wu, Qiuwei Guo, Qinglai Sun, Hongbin Tsinghua Univ Tsinghua Berkeley Shenzhen Inst Tsinghua Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China Tsinghua Univ Inst Ocean Engn Tsinghua Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

The low-carbon building has been proposed to mitigate the climate change caused by environmental problems and realize carbon neutrality in urban areas. In addition, the integrated energy system (IES) has been developed to reduce renewable energy curtailment in the power distribution system and improve energy efficiency due to the independent operation of traditional energy systems. In this paper, we propose a stochastic planning method for low-carbon building IES, in which the Vehicle to Grid (V2G) is also considered to further increase the flexibility of low-carbon buildings. The proposed planning method optimizes the investment and operation costs, and CO2 emission of the building IES, to achieve the maximum benefit of the low-carbon building and help realize carbon neutrality. By considering the uncertainty of distributed renewable energy, multi-energy load fluctuation and the random behavior of EV users, a two-stage stochastic programming model is formulated with chance constraints, in which the heuristic moment matching scenario generation (HMMSG) and sample average approximation (SAA) methods are applied to deal with the uncertainties. In the case study, a real IES office building in Shanghai, where photovoltaic (PV), energy storage system (ESS), fuel cell (FC), EV, etc. are included as planning options, is used as the test system to verify the effectiveness of the proposed planning method, and the functions of the ESS and EV in IES are analyzed in detail in different operation scenarios. The case study results show that the proposed planning scheme can reduce the total cost and carbon emission significantly. (c) 2017 Elsevier Inc. All rights reserved.

关键词： Chance constraint Energy storage system Electric vehicle Low-carbon building integrated energy system stochastic programming

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Energy management in microgrids using transactive energy control concept under high penetration of Renewables;A survey and case study

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RENEWABLE & SUSTAINABLE ENERGY REVIEWS 2023年 176卷

作者： Alizadeh, Ali Kamwa, Innocent Moeini, Ali Mohseni-Bonab, Seyed Masoud Univ Laval Coll Engn Elect Engn Dept Quebec City PQ Canada Hydro Quebec IREQ Power Syst Simulat & Evolut Varennes PQ Canada Hydro Quebec IREQ Digital Syst Varennes PQ Canada

Transactive Energy Control (TEC) paradigm enables involving Microgrids (MGs) in the energy management procedure to realize the transition of energy systems using market-based mechanisms. This paper, in this regard, proposes a review including state-of-the-art energy management using the TEC concept in MGs, highlighting the types of interactions among prosumers and MG operators, uncertainty models, and Energy Management System (EMS) designs. The proposed review illustrates that the distributed style of interactions with prosumer-centric uncertainty management has scarcely been investigated, while it is more beneficial in terms of financial, computational, and communication aspects. Hence, to pave the path for future research, a distributed TEC is proposed based on the consensus Alternative Direction Method of Multipliers (ADMM), wherein prosumers can solve their prosumption problem using a novel EMS and the MG operator acts as a coordinator to oversee system constraints. The EMS relies on a two-stage stochastic model, whereby prosumers can personally manage the associated risk using conditional value-at-risk (CVaR). The implementation results indicate that the accuracy, runtime, and communication burden are improved using the proposed distributed TEC by 32.76%, 15.68%, and 1094.6% compared to the decentralized TEC. Moreover, prosumers can save a further 5.75% on their bills using prosumer-centric uncertainty management. Consequently, the proposed review illuminates the research direc-tion, while the proposed distributed TEC with the prosumer-centric uncertainty management elaborates on the identified gaps to accelerate the pace of improvement in this area.

关键词： transactive energy control Prosumer-side energy management systems Networked microgrids Consensus alternative direction method of multipliers (ADMM) stochastic programming Distributed transactive energy control Risk management Uncertainties management Conditional value at risk

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Coordinated preparation and recovery of a post-disaster Multi-energy distribution system considering thermal inertia and diverse uncertainties

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APPLIED ENERGY 2023年 336卷

作者： Li, Zhengmao Xu, Yan Wang, Peng Xiao, Gaoxi Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore

Low-probability but high-impact extreme events, such as floods, earthquakes, hurricanes, etc., could threaten the security of a multi-energy system, especially on the distribution level, and cause severe energy supply outages. In this paper, a coordinated restoration method is presented for the renewable energy-integrated multi-energy distribution system (MDS) with several coupling points to coordinate the preparation and load recovery stages after the extreme event. First, the MDS restoration is comprehensively modeled with coupled power and thermal network constraints. Especially, the thermal inertia, which is in the form of pipe storage and thermal demand response of smart buildings to serve as a buffer when the source fails, is fully utilized to reduce the energy supply cost after disasters. Secondly, both preparation and load recovery stage measures are employed to facilitate efficient and reliable system restoration. Furthermore, multiple uncertainties from the renewable generation and power demands in the MDS restoration are dealt with via a risk-averse two-stage stochastic programming approach. Finally, simulation results validate the effectiveness of our method and its superiority over the traditional restoration methods.

关键词： Multi -energy distribution systems (MDSs) Thermal inertia stochastic programming Coordinated restoration

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Infectious waste management during a pandemic: A stochastic location-routing problem with chance-constrained time windows

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COMPUTERS & INDUSTRIAL ENGINEERING 2023年 177卷 109066页

作者： Hassanpour, Saeed Tasouji Ke, Ginger Y. Zhao, Jiahong Tulett, David M. Mem Univ Newfoundland Fac Business Adm St John NF A1B 3X5 Canada Guangdong Univ Technol Sch Civil & Transportat Engn Guangzhou 510006 Peoples R China

The COVID-19 pandemic has presented tremendous challenges to the world, one of which is the management of infectious waste generated by healthcare activities. Finding cost-efficient services with minimum threats to public health has become a top priority. The pandemic has induced extreme uncertainties, not only in the amount of generated waste, but also in the associated service times. With this in mind, the present study develops a mixed-integer linear programming (MILP) model for the location-routing problem with time windows (LRPTW). To handle the uncertainty in the amount of generated waste, three scenarios are defined respectively reflecting different severity levels of a pandemic. Furthermore, chance constraints are applied to deal with the variation of the service times at small generation nodes, and time windows at the transfer facilities. The complexity of the resulting mathematical model motivated the application of a branch-and-price (B&P) algorithm along with an -constraint technique. A case study of the situation of Wuhan, China, during the initial COVID-19 outbreak is employed to examine the performance and applicability of the proposed model. Our numerical tests indicate that the B&P algorithm outperforms CPLEX in the computational times by more than 83% in small-sized problem instances and reduces the gaps by at least 70% in large-scale ones. Through a comparison with the current and deterministic systems, our proposed stochastic system can timely adjust itself to fulfill nearly four times the demand of other systems in an extreme pandemic scenario, while maintaining a cost-efficient operation with no outbreak.

关键词： Infectious waste Location-routing problem Time windows stochastic programming Chance constrained programming Branch-and-price algorithm

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Optimal stochastic self-scheduling of a water-energy virtual power plant considering data clustering and multiple storage systems

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JOURNAL OF ENERGY STORAGE 2023年 65卷

作者： Rezaei, Navid Pezhmani, Yasin Mohammadiani, Rojiar Pir Univ Kurdistan Dept Elect Engn Sanandaj Iran Univ Kurdistan Dept Comp Engn Sanandaj Iran

As the world moves towards the integration of different water and energy resources, as well as storage systems, it is necessary to develop the conventional structure of virtual power plants (VPPs). In this work, a mixed-integer nonlinear programming (MINLP) model is established for stochastic self-scheduling problem of a new VPP structure, namely water-energy VPP. The proposed VPP, which participates in the electricity market to maximize its daily profit, aggregates different energy and water resources including wind turbines, compressed air energy storage (CAES), gas boiler, electrical boiler, absorption chiller, ice storage, water storage, and water well to supply water demand, as well as different types of energy demands such as cooling, power, and heat demands. To cope with the uncertain behavior of wind power, a scenario-based approach is employed. First, with the use of Monte Carlo simulation in MATLAB, a number of scenarios are obtained, and afterwards, K-means technique, which is a fast and efficient data clustering method, is implemented for the scenario reduction. Additionally, the impact of the consideration of CAES system on the performance of the proposed water-energy is discussed. The numerical results indicate that with the deployment of CAES system into the structure of the water-energy VPP, the expected daily profit is increased up to 4.26 %.

关键词： Virtual power plant Water -energy nexus Data clustering Renewable energy stochastic programming

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