Abdullah Abusorrah

Optimal Expansion Planning of Energy Hub With Multiple Energy Infrastructures

This paper presents an optimal expansion planning model for an energy hub with multiple energy systems. Energy hub represents a coupling among various energy infrastructures for supplying electricity, natural gas, and heating loads. Combined heat and power (CHP) and natural gas furnaces are considered within the energy hub to convert energy into other forms. The multiple energy system planning problem would optimally determine appropriate investment candidates for generating units, transmission lines, natural gas furnaces, and CHPs that satisfy electricity and heating load forecasts and hub system constraints. The system performances associated with reliability, energy efficiency, and emission matrices is evaluated for the identified planning schedules. Numerical simulations demonstrate the effectiveness of the proposed multiple energy system expansion planning approach based on energy hub.

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

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. The electricity and natural gas network constraints are considered in the proposed model (referred to as EGTran) and Benders decomposition is adopted to check the natural gas network feasibility. The autoregressive moving average (ARMA) time-series model is used to simulate wind speed forecast errors in multiple Monte Carlo scenarios. Illustrative examples demonstrate the effectiveness of EGTran for firming the variable wind energy by coordinating the constrained electricity and natural gas delivery systems.

Optimal Interconnection Planning of Community Microgrids With Renewable Energy Sources

The optimal planning of the interconnected network of multimicrogrids is discussed in this paper. The interconnection planning will enhance the reliability and the economic operation of a community of microgrids. The proposed approach will apply a probabilistic minimal cut-set-based iterative methodology for the optimal planning of interconnection among microgrids with variable renewable energy sources. The optimal planning takes into account various factors including the economics, reliability, and variability of renewables, network- and resource-based uncertainties, and adaptability to accommodate the prevailing operating concerns. A clustering-based method is considered for analyzing the variable data concerning the potential deployment of renewable energy in microgrids. The proposed interconnection planning methodology is applied to a six-microgrid system and the planning results are discussed. The numerical results demonstrate that the proposed interconnection planning methodology will determine an optimal topology accurately and efficiently for a cluster of microgrids, and show that the proposed adaptive planning methodology can easily be applied to practical microgrid applications.

Thermal Generation Flexibility With Ramping Costs and Hourly Demand Response in Stochastic Security-Constrained Scheduling of Variable Energy Sources

This paper proposes a stochastic day-ahead scheduling of electric power systems with flexible resources for managing the variability of renewable energy sources (RES). The flexible resources include thermal units with up/down ramping capability, energy storage, and hourly demand response (DR). The Monte Carlo simulation (MCS) is used in this paper for simulating random outages of generation units and transmission lines as well as representing hourly forecast errors of loads and RES. Numerical tests are conducted for a 6-bus system and a modified IEEE 118-bus system and the results demonstrate the benefits of applying demand response as a viable option for managing the RES variability in the least-cost stochastic power system operations.

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

This paper studies the role of hourly economic demand response in the optimization of the stochastic day-ahead scheduling of electric power systems with natural gas transmission constraints. The proposed coordinated stochastic model (referred to as EGTran) considers random outages of generating units and transmission lines, and random errors in forecasting the day-ahead hourly loads. The Monte Carlo simulation is applied to create multiple scenarios for representing the coordinated system uncertainties. The nonlinear natural gas network constraints are linearized and incorporated into the stochastic model. Numerical results demonstrate the benefits of applying the hourly economic demand response for enhancing the scheduling coordination of natural gas and electricity networks. It is demonstrated that electricity demand response would offer a less volatile hourly load profile and locational marginal prices, and less dependence on natural gas constraints for the optimal operation of electric power systems. The proposed model for EGTran could be applied by grid operators for the hourly commitment and dispatch of power system units.

Optimal Power Flow Using Adapted Genetic Algorithm with Adjusting Population Size

Abstract In this article, a new approach for the genetic algorithm is applied to solve the optimal power flow problem based on different objective functions. The main distinction of this technique is in using the adapted genetic algorithm with adjusting population size. The objective functions are minimized using various controlled system variables (generator voltages, transformer taps, and shunt capacitors). The feasibility of the proposed method is presented on the IEEE 30-bus system and compared to other well-established techniques. A comparison with other methods shows the effectiveness of the proposed technique.

Security-Constrained Co-Optimization Planning of Electricity and Natural Gas Transportation Infrastructures

This paper presents a co-optimization planning model that considers the long-term interdependency of natural gas and electricity infrastructures. The model incorporates the natural gas transportation planning objective in the co-optimization planning of power generation and transmission systems. The co-optimization planning model is decomposed into a least-cost master investment problem for natural gas and electricity systems which interacts with two operation subproblems representing the feasibility (security) and the optimality (economic) of the proposed co-optimization. In addition, the natural gas subproblem would check the feasibility of fuel supply transportation system as part of the proposed co-optimization planning. The co-optimization planning of electricity and natural gas infrastructures would satisfy the desired power system reliability criterion. The iterative process will continue between the co-optimization investment and the operation subproblems until an economic, secure, reliable, and fuel-supply feasible planning for the two interdependent infrastructures is obtained. Numerical simulations demonstrate the effectiveness of the proposed co-optimization planning approach.

MAF-PLL With Phase-Lead Compensator

A basic approach to improve the filtering capability of a standard phase-locked loop (PLL) is to incorporate a moving average filter (MAF) into its control loop. This improvement, however, is at the cost of a slow transient response for the PLL, which is undesirable in most applications. It is shown in this paper that this problem can be alleviated by adding a phase-lead compensator in the MAF-PLL control loop. The effectiveness of the suggested approach is confirmed through numerical results.

Improved Power Quality Control and Intelligent Protection for Grid Connected Power Electronic Converters, using Real Time Parameter Estimation

This paper presents a method to identify power system impedance in real-time, using signals obtained from grid connected power electronic converters. The method uses wavelets to analyse the transients associated with a small disturbance imposed by the power converter, and determine the net impedance back to source. A data capture period of 5ms only is required for accurate impedance estimation, providing the possibility of ultra fast fault detection (i.e. with one half cycle). The paper describes how the method may be used to enhance operation during faults for distributed generation. This impedance estimation has potential application in renewable/distributed energy systems, STATCOM, and proposed solid state substations

Electricity-Natural Gas Operation Planning With Hourly Demand Response for Deployment of Flexible Ramp

This paper proposes an integrated stochastic day-ahead scheduling model to dispatch hourly generation and load resources and deploy flexible ramping for managing the variability of renewable energy system. A comprehensive framework for the natural gas transportation network is considered to address the dispatchability of a fleet of fuel-constrained natural gas-fired units. System uncertainties include the day-ahead load and renewable generation forecast errors. Illustrative examples demonstrate that the real-time natural gas delivery can directly impact the hourly dispatch, flexible ramp deployment, and power system operation cost. Meanwhile, the demand side participation can mitigate the dependency of electricity on natural gas by providing a viable option for flexible ramp when the natural gas system is constrained.