Over the past decade, Renewable Energy Sources (RES) have been rapidly developed to meet the surging demand for electricity consumption. Besides the benefits, the penetration of RES into the power grid raises multiple...
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(纸本)9798350381061
Over the past decade, Renewable Energy Sources (RES) have been rapidly developed to meet the surging demand for electricity consumption. Besides the benefits, the penetration of RES into the power grid raises multiple issues, including the intermittent nature of power output and technical requirements for grid integration. Therefore, the Virtual Power Plant (VPP) model has been implemented to address the drawbacks of RES through aggregating Distributed Energy Resources (DER). This paper applies a mixed-integer linear programming (MILP) model to optimize the VPP's operation and maximize VPP's expected profit in the day-ahead market (DAM). The optimization model is solved by GAMS and CPLEX software. This study applies the proposed model to a VPP trial system, including a Wind Power Plant (WP), a Photovoltaic Power Plant (PV), an Energy Storage System (ESS), an Electric Vehicle (EV) charging station, and residential load. WP, PV, and load uncertainties are viewed as stochastic processes and modeled by a set of scenarios. The shifting of the EV charging schedule is considered. The results show that the proposed model has practical significance.
The dynamic nightlife scene has resulted in a significant increase in late-night passengers utilizing the metro system. However, efficiently serving these passengers during their last train connections in metro while ...
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Given a set of points P on a line, a collection of intervals I along the line, and a positive integer K≤|I|, each point p∈P is associated with a covering requirement qp, the goal of the maximum interval multi-cover ...
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This article presents a methodology aimed at improving mid-term power system resilience at transmission substations in areas potentially affected by floods, combining hardening strategies and quantitative metrics. It ...
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This article presents a methodology aimed at improving mid-term power system resilience at transmission substations in areas potentially affected by floods, combining hardening strategies and quantitative metrics. It takes into account flood forecasts from a hydrological model and the location of electrical equipment to perform impact assessment "as is"and with resilience planning strategies. Thus, the impact of floods on the grid is evaluated over a range of realistic flood scenarios, based on the accumulated cost and load energy unserved as metrics together with future transmission system expansion capacity projections. The mixed-integer linear programming formulation is aimed at minimizing accumulated cost and load energy unserved with optimal hardening of substations, assuming that any non-hardened substation disabled by flooding must be repaired. Furthermore, the methodology is demonstrated in the coastal area of Texas with simulations of floods based on the rainfall of Hurricane Harvey in 2017. Ultimately, the choice of the most appropriate mitigation strategies shall optimize resilience metrics and/or cost indicators with robustness over a range of scenarios.
In order to cope with global climate change, an electric vehicle (EV) and new energy building are constantly being innovated and improved. With the popularity and application of big data and Internet of Things, the ne...
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In order to cope with global climate change, an electric vehicle (EV) and new energy building are constantly being innovated and improved. With the popularity and application of big data and Internet of Things, the new energy building with available charging piles may also become a charging station, which can solve the problem of difficult charging of EVs and promote the local energy consumption of the building. Therefore, this study proposes a shared charging concept for buildings, that is, shared photovoltaic, charging, and energy storage building (sPCEB). First, based on the analysis results of big data in cities or settlements of people, a locating method of the sPCEB system is introduced, and further proposes an optimal operating strategy that maximizes the combined benefit of the building. The efficiency and effectiveness of the proposed methods are verified by simulation.
This paper proposes a new optimization model based on mixed-integer linear programming approach for sizing a solar-windgrid-connected system. The proposed hybrid system aims to supply load demand for an industrial fac...
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This paper proposes a new optimization model based on mixed-integer linear programming approach for sizing a solar-windgrid-connected system. The proposed hybrid system aims to supply load demand for an industrial facility in Saudi Arabia. The developed model determines the optimal number of photovoltaic modules and wind turbines, as well as the optimal hourly energy obtained from the grid and hourly excess energy produced by the system and sold to the grid. The model findings show that 77 photovoltaic modules and 7 wind turbines in addition to the grid are needed to satisfy the load demand. The system produces 450,734 kWh annually which represents 82% of the annual load consumption. Also, the system produces surplus energy of 72,752 kWh which accounts to $6,184 as an income to the industrial facility. The case study is enriched by considering off-grid photovoltaic-wind system with battery storage. The results show that incorporating battery storage increases the cost of energy of the hybrid system. However, the off-grid photovoltaic-wind system shows promising results when considering environmental issues as it will displace around of 279,800 kg of carbon dioxide per year compared to the grid-connected system that will displace around 225,768 kg of carbon dioxide per year. A sensitivity analysis was carried out to identify the effect of the electricity cost on the optimal system design and the cost of energy obtained from the hybrid system.
The real-time optimal load dispatch (OLD) problem in a hydropower plant aims to determine the generation level of each generating unit (GU) in the most efficient way and a few seconds. Due to the hydro production func...
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The real-time optimal load dispatch (OLD) problem in a hydropower plant aims to determine the generation level of each generating unit (GU) in the most efficient way and a few seconds. Due to the hydro production function (HPF), it is a nonlinearprogramming (NLP) problem that can be efficiently handled via mixed-integer linear programming (MILP). However, solving the real-time OLD of the Santo Antonio Hydro Plant (SAHP) is particularly challenging, both in terms of modeling and execution time, due to the following issues: (1) there are 50 GUs with different hydraulic efficiency curves;(2) the gross head is dependent of the GU dam location;and (3) significant (and potentially dangerous) losses in the trash racks produced by the Madeira River debris. In this scenario, this paper presents a recommendation system for the real-time OLD of the SAHP based on MILP. In real-time, the system employs gross head and trash rack losses measures to model and solve a MILP problem that obtains the GUs power level to be used by the hydro plant operator. We compare the system solution with the strategy currently used by the plant operator and with the equal dispatch between the identical GUs. The results emphasize the improvement in plant productivity. In the 2019 year, for example, the OLD real-time recommendation system presents a 9852.63 MWh increasing in power energy generation.
In a centralized-based dispatch market, the network-constrained hydrothermal unit commitment (NCHTUC) determines generation decisions that minimize the expected operating cost, usually in a day-ahead planning horizon....
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In a centralized-based dispatch market, the network-constrained hydrothermal unit commitment (NCHTUC) determines generation decisions that minimize the expected operating cost, usually in a day-ahead planning horizon. In this context, hydropower offers unique flexibility features, and an adequate representation is crucial for overcoming operation challenges. However, due to computational burden, simplifications on hydropower production function (HPF) modeling are necessary since NCHTUC is a large-scale nonlinear discrete optimization problem. The plant-based HPF piecewise linear approach is the most common simplification presented for real life cases. In this case, the generating units (GUs) of a plant are aggregated and represented by a single equivalent generator. Although this approach reduces the size and the complexity of the NCHTUC significantly, several operating issues are not considered adequately, especially the forbidden zones and the nonlinearities of the GUs. In this paper, we present a new approach that considers the nonlinearities and forbidden zones of the HPF via aggregation of the GUs and piecewise mixed-integerlinear approximation in an innovative way. Experiments are performed in a modified version of the IEEE 118-bus system to verify the approach's effectiveness, analyzed in terms of the relation between computation burden and the HPF approximation quality.
The technological advancements involving information and communication technologies (ICT), such as Connected and Automated Vehicles (CAVs) and the Intelligent Transport Systems (ITS), have enabled new efficient traffi...
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The technological advancements involving information and communication technologies (ICT), such as Connected and Automated Vehicles (CAVs) and the Intelligent Transport Systems (ITS), have enabled new efficient traffic control and management strategies to mitigate traffic congestion. Specifically, the combined traffic flow-speed advisory systems based on CAVs and ITS technologies could provide the individual vehicle with the optimal speed to reduce the fuel consumption, the number of stops, simultaneously reduce the network-wide traffic congestion and improve road safety. This article develops a novel bi-level control framework underpinned by the mutual interaction between a system optimal traffic flow control strategy at a network level and a speed control policy for an individual vehicle at a link level within a connected traffic environment. Our framework proposes the novel group-based method to guarantee the consistency and interaction between the macroscopic and microscopic models. To this end, it efficiently optimizes vehicular trajectories while meeting the network-wide objectives which have not been investigated previously in the literature. We propose an efficient algorithm for this problem that iteratively solves mixed-integer linear programming (MILP) models for each upper and lower level. Numerical results indicate the effectiveness of the proposed speed advisory method in vehicular emission reduction, favorable network queue formation, and its positive influence on traffic flow patterns over the network.
The high penetration of Distributed Energy Resources (DERs) into the demand side has led to an increase in the number of consumers becoming prosumers. Recently, Peer-to-Peer (P2P) energy trading has gained increased p...
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The high penetration of Distributed Energy Resources (DERs) into the demand side has led to an increase in the number of consumers becoming prosumers. Recently, Peer-to-Peer (P2P) energy trading has gained increased popularity as it is considered an effective approach for managing DERs and offering local market solutions. This paper presents a P2P Energy Management System (EMS) that aims to reduce the absolute net energy exchange with the utility by exploiting two days-ahead energy forecast and allowing the exchange of the surplus energy among prosumers. mixed-integer linear programming (MILP) is used to schedule the day-ahead household battery energy exchange with the utility and other prosumers. The proposed system is tested using the measured data for a community of six houses located in London, UK. The proposed P2P EMS enhanced the energy independency of the community by reducing the exchanged energy with the utility. The results show that the proposed P2P EMS reduced the household operating costs by up to 18.8% when it is operated as part of the community over four months compared to operating individually. In addition, it reduced the community's total absolute net energy exchange with the utility by nearly 25.4% compared to a previous state-of-the-art energy management method.
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