Participation of Grid-Connected Energy Hubs and Energy Distribution Companies in the Day-Ahead Energy Wholesale and Retail Markets Constrained to Network Operation Indices (original) (raw)
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Wholesale and retail energy markets model for the energy networks in the presence of the energy hubs
Energy Reports, 2023
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2019 International Conference on Smart Energy Systems and Technologies (SEST), 2019
In recent decades, the rising penetration of various types of distributed energy resources has made interactions between all types of energy inevitable. In this respect, energy hubs are created with the aim of considering the interactions between multi-carrier energy systems throughout the smart grids. In this research, optimal scheduling of the multi-energy hubs is considered in the day-ahead market with the aim of minimizing the energy hub's cost. Because of the high usage of the clean energy production potential by employing the wind turbines and PV panels at each energy hub, the proposed model will mitigate the greenhouse gas emissions through reducing the operation of the gas-fired systems over the scheduling horizon. The combined cooling/heating and power system is also used as a backup unit for the stochastic producers to ensure energy supply with minimum load shedding. Moreover, electrical and thermal energy storage devices are also employed for storing energy during time intervals when there is a large amount of clean and free energy production. The Monte-Carlo simulation approach is used for modeling the uncertain behaviors of the stochastic producers and fast forward selection method is also used for the scenario reduction process. The flexibility of the energy demand is also investigated using demand response programs. In order to validate the effectiveness of the proposed model, IEEE 10-bus standard test system integrated with distributed energy resources is used. Simulation results demonstrate the applicability and usefulness of the proposed model in the energy management of multi energy hubs.
Flexibility Pricing of Grid-Connected Energy Hubs in the Presence of Uncertain Energy Resources
International Journal of Energy Research
The paper expresses the problem of flexibility pricing in energy hubs (EHs) that are in connection with electricity, heat, and gas networks considering of uncertain energy generation sources. Scheme includes a bilevel formulation. Its upper-level states for modeling of the flexibility services are provided by various resources within the EH. The problem considers maximization of the expected profit of these resources in the flexibility market. The problem constraints include the flexibility model of flexible resources such as storage devices, responsive loads, and controllable distributed generations (DGs). The flexibility model of resources relies on their active and heat power. The lower-level problem calculates energy and flexibility prices and formulates the flexible operation of energy resources considering EHs. Here, constraints include optimal power flow equations in the energy networks; operation model of EHs with power sources, storage devices, and different responsive load...
Optimal Operation of Distribution Networks through Clearing Local Day-ahead Energy Market
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New energy market players such as micro-grid aggregators (MGA), distributed energy resource aggregators (DERA), and load aggregators (LAs) have all emerged to facilitate the integration of DERs into power systems. These players can participate in wholesale markets either individually or through distribution companies (Discos). In both cases, several operational challenges emerge for transmission system operators (TSOs) and distribution system operators (DSOs). Meanwhile, a transition is occurring from centralized wholesale markets into local energy markets (LEMs). A literature review shows that these LEMs are mostly modeled focusing on the coordination between DSOs and TSOs to meet demand in real-time operation using ancillary service markets and balancing markets. The main contribution of this paper is to model a local day-ahead energy market (LDEM) for optimal operation of a distribution network. This LDEM is cleared by the DSO with the aim of maximizing the social welfare of mark...
Uncertainty-Based Models for Optimal Management of Energy Hubs Considering Demand Response
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Energy hub (EH) is a concept that is commonly used to describe multi-carrier energy systems. New advances in the area of energy conversion and storage have resulted in the development of EHs. The efficiency and capability of power systems can be improved by using EHs. This paper proposes an Information Gap Decision Theory (IGDT)-based model for EH management, taking into account the demand response (DR). The proposed model is applied to a semi-realistic case study with large consumers within a day ahead of the scheduling time horizon. The EH has some inputs including real-time (RT) and day-ahead (DA) electricity market prices, wind turbine generation, and natural gas network data. It also has electricity and heat demands as part of the output. The management of the EH is investigated considering the uncertainty in RT electricity market prices and wind turbine generation. The decisions are robust against uncertainties using the IGDT method. DR is added to the decision-making process ...
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Optimal Scheduling of Energy Hubs in the Presence of Uncertainty-A Review
Energy Hub is an appropriate framework for modeling and optimal scheduling of multi-energy systems (MES). Energy hub provides the possibility of integrated management of various inputs, converters, storage systems, and outputs of multiple energy carrier systems. However, the optimal management problem in the energy hub is affected by various technical, economic, social and environmental parameters. Many of these parameters are inherently ambiguous and uncertain. Fluctuating nature of renewable energy sources (RES), energy prices in competitive and deregulated markets, the behavior of consumers, inherent variations in the surrounding environment, simplifications and approximations in modeling, linguistic terms of experts, etc. are just a few examples of uncertainties in the optimal management problem of energy hub. Ignoring such uncertainties in the process of modeling and optimization of energy hub leads to unrealistic models and inaccurate results. On the other hand adding these uncertainties leads to increased complexity of modeling and optimization. Therefore, to achieve a realistic model of MES in the form of energy hubs, identifying appropriate methods to address these uncertainties is essential. This paper reviews the different methods for the consideration of uncertainty in optimal scheduling of energy hubs. In this paper, different methods of modeling and optimization of energy hub are reviewed and classified and their strengths and weaknesses are discussed. A classification and review of the various methods that offered in the most recent research of MES in the field of uncertainty modeling are done to identify efficient methods for using in energy hub models.
Optimal Operation of an Energy Hub in the Presence of Uncertainties
2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2019
This paper presents an operation strategy of energy hubs in the presence of electrical, heating, and cooling demand as well as renewable power generation uncertainties. The proposed strategy can be used for optimal decision making of energy providers companies, as well as, other private participants of hub operators. The presence of electrical energy storage devise in the assumed energy hub can handle the fluctuations in the operating points raised by such uncertainties. In order to modeling of hourly demands and renewable power generation uncertainties a scenario generation model is adopted in this paper. The considered energy hub in this study follows a centralized framework and the energy hub operator is responsible for optimal operation of the hub assets based on the day-ahead scheduling. The simulation result illustrates that in the presence of electrical energy storage devices the optimal operation of hub assets can be attained.
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This paper presents a day-ahead scheduling approach for a multi-carrier residential energy system (MRES) including distributed energy resources (DERs). The main objective of the proposed scheduling approach is the minimization of the total costs of an MRES consisting of both electricity and gas energy carriers. The proposed model considers both electrical and natural gas distribution networks, DER technologies including renewable energy resources, energy storage systems (ESSs), and combined heat and power. The uncertainties pertinent to the demand and generated power of renewable resources are modeled using the chance-constrained approach. The proposed model is applied on the IEEE 33-bus distribution system and 14-node gas network, and the results demonstrate the efficacy of the proposed approach in the matters of diminishing the total operation costs and enhancing the reliability of the system.
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