Aggregate Impact Analysis of Demand Response Programs, Electric Vehicles, and Combined Heat and Power Units on Integrated Management of Industrial Virtual Power Plant (original) (raw)
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Coordinated Operation of Electric Vehicle Parking Lots and Smart Homes as a Virtual Power Plant
2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2020
In recent years, virtual power plants (VPPs) rose as an effective framework to aggregate the collective potential of distributed energy resources (DERs), including distributed generation (DG) and energy storage systems (ESS), through demand response (DR) program implementation. In this work, the operation of two indispensable DER assets, electric vehicles (EVs) and photovoltaic-equipped parking lots (PVPLs), is coordinated in an optimal energy management framework, in order to study their possible aggregation as a VPP. The proposed energy management system (EMS) was developed using the optimization and simulation tools, namely GAMS and MATLAB, and is intended for use by grid operators to coordinate the operation of PVPLs and home energy management systems (HEMSs) in the context of smart cities. The developed model was validated and tested by considering real-life case studies in the city of Porto, Portugal.
2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2021
In the recent past structural changes in the operation and topology of the electrical system have occurred. These changes have coincided with the emergence of distributed energy resources (DERs). Relating to supply side technologies, distributed generation (DG) units have become increasingly common. The demand side has also seen the growth of new technological applications, including electric vehicles (EVs). These changes to the electrical system are being especially felt at the low voltage network level. Technical Virtual Power Plants (TVPPs) have been used to optimally schedule these DERs to increase the network flexibility and at the same time increasing the reliability and power quality of the network and this can bring economic benefits to both the TVPP operator and the customer. This paper develops a stochastic mixed-integer linear programming (MILP) optimization model to maximize the profit of a TVPP. The main objective of the TVPP is to increase operational flexibility of the low voltage network by aggregating DERs, including DG units, Heating Ventilation and Air Conditioning units, and EVs. The model is examined through the use of the IEEE 119-Bus test system. Results demonstrate that the inclusion of DG units and EVs, the profit of the TVPP increases by approximately 45% and system flexibility is increased while respecting the technical constraints of the network and the thermal comfort of the consumers.
A smart method for multi-zonal virtual power plant scheduling with presence of electric vehicles
2021
Microgrids are practical views of integration of distributed generations (DGs) into distribution systems. In this regard, utilizing appropriate technologies and accurate recognition of energy generation and storage systems, as well as optimal scheduling for these resources are of the paramount importance in microgrids. Therefore, connection of DG resources and storages to the grid in the form of virtual power plant in order to increase efficiency and owners’ interest has attracted significant attention of researchers and distribution network operators. This research presents a model for optimal day-ahead scheduling of heat-power generation units in a multi-zonal virtual power plant (VPP). This VPP includes a number of combined heat-power generations, distribution network loads, and electrical vehicles with smart charging as well as energy storages. In order to approach the reality of distribution systems, uncertainty related to behavior of electrical vehicles was modeled with Monte-...
Electric Vehicle Virtual Power Plant Dilemma: Grid Balancing Versus Customer Mobility
Production and Operations Management, 2018
V irtual power plants (VPP) play a crucial role in balancing the electricity smart grid. VPPs aggregate energy from decentralized sources, for example, biogas, solar panels, or hydropower, to generate and consume electricity on demand. We study the management of electric vehicle (EV) fleets organized in VPPs as a way to address the challenges posed by the inflexible energy supply of renewable sources. In particular, we analyze the potential of parked EVs to absorb electricity from the grid, and provide electricity back to the grid when needed. A fleet owner can either charge, discharge for renting, discharge to the grid, or keep an EV idle. A unique property of our mixed rental-trading strategy is that decisions are made between making an EV available for rental, where the location within the city matters (drivers want a car to be close to their place of departure or arrival) and for discharging it to the grid, where location does not matter (vehicles can discharge to the grid from any capable charging point). We study the feasibility of VPPs for a fleet of 1500 real EVs on the "Nord Pool Spot," a North European electricity spot market. A Fourier series approach captures the demand patterns of carsharing vehicles accurately, especially when our weighted objective function with asymmetric payoffs is applied. We show that the VPP can be profitable to fleet owners, ecologically advantageous through reductions in wind power curtailment, and beneficial to consumers by reducing energy expenses.
CIRED 23rd International Conference on Electricity Distribution , 2015
Presently at EDP Distribuição, LV networks are planned using probabilistic methods. With InovGrid, the smart grid project developed in Portugal, real data from LV networks is becoming available for planning purposes, enabling new planning methods. Part I of this paper analyses the results obtained with both approaches, probabilistic and chronological, while planning a real LV network. Furthermore, Part II of the paper analyses the impact on the distribution MV networks of three different strategies of electric vehicle (EV) charging – Direct Charging, Minimum Cost and Renewable-Following. Finally, we performed a critical analysis of the results obtained, in order to find the strengths and weaknesses of each charging solution, as well as the impact that these have on the medium voltage distribution network.
A comprehensive review of demand-side management in smart grid operation with electric vehicles
Demand-side management of smart grid with electric vehicles (EVs) is overviewed in this review paper. The major objective of the work is to reduce the hourly peak load to obtain a steady load schedule, maximize user satisfaction and reduce cost. This review allows for the probability of leveling the everyday energy load arc and unstable demand response to hourly prices from one time period to another. To obtain a balanced everyday load schedule, increase user satisfaction, and cut costs, the main aim is to reduce peak hourly load. A management system for an EV connected to the national grid for a future household with controllable electric loads. The approach that has been presented enables the integration of EVs and renewable resources while also optimizing the demand and generation in hourly distribution. The agents are taken into account for managing load, storage, and generation; specifically, they are EV aggregators. The vehicle-to-grid (V2G) combination of electric vehicles is a key aspect of this study; with this capability, EVs may offer power grid-specific services like load shifting and congestion management. By maximizing the hourly distribution of demand as well as generation, accounting for technical limitations, and enabling the addition of EVs and RES.
Operation of a Technical Virtual Power Plant Considering Diverse Distributed Energy Resources
IEEE Transactions on Industry Applications, 2022
Virtual Power Plants (VPP) have emerged as a way to coordinate and control the growing number of Distributed Energy Resources (DERs) within power systems. Typically, VPP models have focused on financial or commercial outcomes and have not considered the technical constraints of the distribution system. The objective of this paper is the development of a technical VPP (TVPP) operational model to optimize the scheduling of a diverse set of DERs operating in a day-ahead energy market, considering grid management constraints. The effects on network congestion, voltage profiles and power losses are presented and analyzed. In addition, the thermal comfort of the consumers is considered and the trade-offs between comfort, costs and technical constraints are presented. The model quantifies and allocates the benefits of the DER operation to the owners in a fair and efficient manner using the Vickrey Clarke Grove mechanism. This paper develops a stochastic mixedinteger linear programming (MILP) model and various case studies are thoroughly examined on the IEEE 119 bus test system. Results indicate that electric vehicles provide the largest marginal contribution to the TVPP, closely followed by solar PV units. Also, the results show that the operations of the TVPP improve financial metrics and increase consumer engagement while improving numerous technical operational metrics. The proposed TVPP model is shown to improve the ability of the system to incorporate DERs, including those from commercial buildings.
IEEE Access, 2022
A suitable energy management scheme and integrating renewable energy resources (RERs) can significantly increase energy efficiency and the stability of future grids operation. This work modeled a household energy management comprising a microgrid (MG) system and demand response programs (DRPs). Residential loads with price-based tariffs are introduced to reduce peak load demands and energy costs. For incorporating the uncertainties in RERs, their stochastic nature is modeled with a probabilistic method. This paper proposes a joint optimization approach for the optimal planning and operation of grid-connected residential, rural MG integrated into renewable energy and electric vehicles (EVs) in view of DRPs. The investigation focuses on energy saving of residential homes under different DRPs and RERs integration. The EVs are integrated into MG by including photovoltaic (PV), wind turbine (WT), fuel cell (FC), and diesel engines (DEs). A multi-objective optimization problem has been formulated to minimize the operating cost, pollutant treatment cost, and carbon emissions cost defined as C1, C2, and C3, respectively. The load demand has been rescheduled because of three DRPs, i.e., critical peak pricing (CPP), real-time electricity pricing (RTEP), and time of use (TOU). Further, the EV load has also been analyzed in autonomous and coordinated charging strategies. Using a judgement matrix, the proposed multi-objective problem is transformed into a single-objective problem. The results of an artificial bee colony (ABC) algorithm are compared with the particle swarm optimization (PSO) algorithm. The simulation analysis was accomplished by employing ABC and PSO in MATLAB. The mathematical model of MG was implemented, and the effects of DRPs based MG were investigated under different numbers of EVs and load data to reduce different costs. To analyze the impact of DRPs, the residential, rural MG is implemented for 50 homes with a peak load of 5 kW each and EV load with 80 EVs and 700 EVs, respectively. The simulation results with different test cases are formulated while analyzing the tradeoff between ABC and PSO algorithms. The simulation analysis shows that multiple DRPs, EVs, and RERs offered a substantial trade-off. INDEX TERMS Demand response programs (DRPs), distributed generations (DG), electric vehicles (EVs), joint sequential optimization, multi-objective optimization, residential microgrids. NOMENCLATURE
Current status and new business models for electric vehicles demand response design in smart grids
2016
Global electric vehicles sales increased about 10 times from 2011, reaching more than 1 million vehicles in roads by 2015. This number is very likely to increase at a steady pace as more models are made available and battery technology improves and costs decrease. It is recognized that the electric vehicles mass integration will imply more complexity to the operation and planning tasks of power systems, but also allow additional opportunities. Indeed, demand response can play a major role to integrate electric vehicles in the future smart grid. This paper discusses the current initiatives from the retailing business in Portugal, Spain and Germany to deal with electric vehicles integration and discusses some new demand response models shaped for the smart grid that can be the new business model of tomorrow energy providers. Currently, the electric vehicles demand response measures adopted by the industry are very limited, mostly offering time of use tariffs with a discount rate.
Demand side management by using electric vehicles as Distributed Energy Resources
2012 IEEE International Electric Vehicle Conference, 2012
This paper aims at demonstrating the potential benefits of using electrical vehicles (EVs) as Distributed Energy Resources (DERs) in smart distribution system. It discusses the options of grid-to-vehicle (G2V) and vehicle-to-building (V2B) operating modes that might be used to support the power grid through demand side management (DSM) program. The V2B mode is particularly promising since it provides an option to use the energy stored in a battery in Electric Vehicles (EVs) to support the local load in the power grid during severe system loading and outages, hence alleviating the demand on the grid and its reliability requirements. The implementation and benefits of using EVs as DERs for demand-side management are discussed and demonstrated with test cases and numerical results.