Hourly Electricity Demand Response in the Stochastic Day-Ahead Scheduling of Coordinated Electricity and Natural Gas Networks (original) (raw)

A Stochastic Two-Stage Model for the Integrated Scheduling of the Electric and Natural Gas Systems

IEEE Open Access Journal of Power and Energy, 2020

The inherent coupling of the electric and natural gas systems due to the operation of gas generating units and power-to-gas facilities, along with the uncertainties faced in both systems due to the variability in electricity and gas demand and the vastly increasing volatile renewable injections, create an imperative need to schedule and operate the two systems in a coordinated manner. In this paper a new model for the fully integrated stochastic day-ahead scheduling of electric and gas systems is presented, coping with the uncertainties of both systems. The stochastic parameters comprise the electricity demand and the renewable injections, which collectively create several net electricity load scenarios, and the gas residential/industrial demand. The integrated scheduling problem concerns a unit commitment for the electricity problem, amended with additional constraints imposed by the underlying natural gas transmission system considering steady-state flow. A two-stage stochastic pr...

Coordination of Interdependent Natural Gas and Electricity Infrastructures for Firming the Variability of Wind Energy in Stochastic Day-Ahead Scheduling

IEEE Transactions on Sustainable Energy, 2015

In this paper, the coordination of constrained electricity and natural gas infrastructures is considered for firming the variability of wind energy in electric power systems. The stochastic security-constrained unit commitment is applied for minimizing the expected operation cost in the day-ahead scheduling of power grid. The low cost and sustainable wind energy could substitute natural gas-fired units, which are constrained by fuel availability and emission. Also, the flexibility and quick ramping capability of natural gas units could firm the variability of wind energy.

Stochastic Security-Constrained Scheduling of Coordinated Electricity and Natural Gas Infrastructures

IEEE Systems Journal, 2015

This paper proposes a coordinated stochastic model for studying the interdependence of electricity and natural gas transmission networks (referred to as EGTran). The coordinated model incorporates the stochastic power system conditions into the solution of security-constrained unit commitment problem with natural gas network constraints. The stochastic model considers random outages of generating units and transmission lines, as well as hourly forecast errors of day-ahead electricity load. The Monte Carlo simulation is applied to create multiple scenarios for the simulation of the uncertainties in the EGTran model. The nonlinear natural gas network constraints are converted into linear constraints and incorporated into the stochastic model. Numerical tests are performed in a six-bus system with a seven-node gas transmission network and the IEEE 118-bus power system with a ten-node gas transmission network. Numerical results demonstrate the effectiveness of EGTran to analyze the impact of random contingencies on power system operations with natural gas network constraints. The proposed EGTran model could be utilized by grid operators for the short-term commitment and dispatch of power systems in highly interdependent conditions with relatively large natural gas-fired generating units.

Market Based Intraday Coordination of Electric and Natural Gas System Operation

Proceedings of the 51st Hawaii International Conference on System Sciences, 2018

This paper outlines the design of an intraday market-based mechanism for coordinated scheduling of gas-fired electric generation, intra-day natural gas purchases, sales and deliveries, and underlying pipeline operation. The mechanism is based on an exchange of physical and pricing data between participants in each market, with price formation in both markets being fully consistent with the physics of energy flow. In organized nodal electricity markets, prices are consistent with the physical flow of electric energy in the power grid because the economic optimization used to clear the market accounts for the physics of power flows. In the gas system, the proposed physical operation and pricing will be based on the transient optimization approach that accounts for physical and engineering factors of pipeline hydraulics and compressor station operations. The paper provides theoretical foundations for the market mechanism.

Demand Response Exchange in the Stochastic Day-Ahead Scheduling With Variable Renewable Generation

IEEE Transactions on Sustainable Energy, 2015

This paper proposes a pool-based demand response exchange (DRX) model in which economic demand response (DR) is traded among DR participants as an alternative for managing the variability of renewable energy sources (RES). Load curtailment bids are provided by individual DRX participants and the DRX is cleared by maximizing the total social welfare, which is subject to supply-demand balance and individual bidders' inter-temporal operation constraints. The proposed DRX model is further integrated in the current context of the ISO's day-ahead scheduling in electricity markets. A two-step sequential market clearing framework is presented in which the ISO's stochastic day-ahead scheduling is simulated first for calculating the expected locational marginal prices (LMPs) and then, the proposed DRX is cleared successively using the expected LMPs. The simulation of the ISO's stochastic day-ahead scheduling incorporates random outages of system components and forecast errors for hourly renewable generation and loads. The decompositionbased method is employed to solve the ISO's day-ahead scheduling in the base case and scenarios. Numerical tests are performed for a 6-bus system and an IEEE 118-bus system. The results demonstrate the benefit of utilizing the DRX model for customer market participation in the ISO's day-ahead market scheduling.

Day-Ahead Stochastic Scheduling Model Considering Market Transactions in Smart Grids

2018 Power Systems Computation Conference (PSCC), 2018

The integration of renewable generation and electric vehicles (EVs) into smart grids poses an additional challenge to the stochastic energy resource management problem due to the uncertainty related to weather forecast and EVs user-behavior. Moreover, when electricity markets are considered, market price variations cannot be disregarded. In this paper, a twostage stochastic programming approach to schedule the dayahead operation of energy resources in smart grids under uncertainty is presented. A realistic case study is performed using a large-scale scenario with nearly 4 million variables with the goal to minimize expected operation cost of energy aggregators. Three scenarios are analyzed to understand the effect of market transactions and external suppliers on the aggregator model. The results suggest that the market transactions can reduce expected cost, while the external supplier offers risk-free price. In addition, the performance metric shows the superiority of the stochastic approach over an equivalent deterministic model.

Coordinated scheduling of electricity and natural gas infrastructures with a transient model for natural gas flow

Chaos: An Interdisciplinary Journal of Nonlinear Science, 2011

Effects of magnetomechanical vibrations and bending stresses on three-phase three-leg transformers with amorphous cores J. Appl. Phys. 111, 07E730 Grid-connected photovoltaic-systems design using evolutionary strategies J. Renewable Sustainable Energy 4, 013123 A unit commitment study of the application of energy storage toward the integration of renewable generation J. Renewable Sustainable Energy 4, 013120 (2012)

Optimal Energy Reserve Scheduling in Integrated Electricity and Gas Systems Considering Reliability Requirements

Journal of Modern Power Systems and Clean Energy

With the growing interdependence between the electricity system and the natural gas system, the operation uncertainties in either subsystem, such as wind fluctuations or component failures, could have a magnified impact on the reliability of the whole system due to energy interactions. A joint reserve scheduling model considering the cross-sectorial impacts of operation uncertainties is essential but still insufficient to guarantee the reliable operation of the integrated electricity and natural gas system (IEGS). Therefore, this paper proposes a day-ahead security-constrained unit commitment (SCUC) model for the IEGS to schedule the operation and reserve simultaneously considering reliability requirements. Firstly, the multi-state models for generating units and gas wells are established. Based on the multi-state models, the expected unserved energy cost (EUEC) and the expected wind curtailment cost (EWC) criteria are proposed based on probabilistic methods considering wind fluctuation and random failures of components in IEGS. Furthermore, the EUEC and EWC criteria are incorporated into the day-ahead SCUC model, which is nonconvex and mathematically reformulated into a solvable mixed-integer second-order cone programming (MISOCP) problem. The proposed model is validated using an IEEE 30-bus system and Belgium 20-node natural gas system. Numerical results demonstrate that the proposed model can effectively schedule the energy reserve to guarantee the reliable operation of the IEGS considering the multiple uncertainties in different subsystems and the cross-sectorial failure propagation. Index Terms-Integrated electricity and natural gas system (IEGS), natural gas reserve, electric reserve, expected unserved energy cost, expected wind curtailment, multi-state model, operational reliability.

ISO's Optimal Strategies for Scheduling the Hourly Demand Response in Day-Ahead Markets

IEEE Transactions on Power Systems, 2000

This paper presents a hierarchical demand response ( DR) bidding framework in the day-ahead energy markets which integrates customer DR preferences and characteristics in the ISO's market clearing process. In the proposed framework, load aggregators submit aggregated DR offers to the ISO which would centrally optimize final decisions on aggregators' DR contributions in wholesale markets. The hourly load reduction strategies include l oad shifting and curtailment and the use of onsite generation and energy storage systems. The ISO applies mixed-integer linear programming (MILP) to the solution of the proposed DR model in the dayahead market clearing problem. The proposed model is implemented using a 6 -bus system and the IEEE-RTS, and several studies are conducted to demonstrate the merits of the proposed DR model.

Stochastic Optimization for Network-Constrained Power System Scheduling Problem

Mathematical Problems in Engineering, 2015

The stochastic nature of demand and wind generation has a considerable effect on solving the scheduling problem of a modern power system. Network constraints such as power flow equations and transmission capacities also need to be considered for a comprehensive approach to model renewable energy integration and analyze generation system flexibility. Firstly, this paper accounts for the stochastic inputs in such a way that the uncertainties are modeled as normally distributed forecast errors. The forecast errors are then superimposed on the outputs of load and wind forecasting tools. Secondly, it efficiently models the network constraints and tests an iterative algorithm and a piecewise linear approximation for representing transmission losses in mixed integer linear programming (MILP). It also integrates load shedding according to priority factors set by the system operator. Moreover, the different interactions among stochastic programming, network constraints, and prioritized load ...