Ahmed S. A. Awad

Optimal ESS Allocation for Load Management Application

The recent deployment of distributed generation has led to a revolution in the use of distribution systems and the emergence of “smart grid” concepts. Smart grids are intended primarily as a means of facilitating the integration of renewable energy sources and of achieving greater system reliability and efficiency. Energy storage systems (ESSs) offer a number of benefits that can help utilities move toward those goals. One of those benefits is the capacity to improve the utilization of network infrastructure by means of proper load management. This paper proposes a methodology for allocating ESSs in distribution systems in order to defer system upgrades, minimize system losses, and take advantage of the arbitrage benefit. The cost and arbitrage benefit of energy storage installation are optimized with respect to system upgrade and energy losses costs. The primary goal of this research is to determine the optimal size and location of storage units to be installed, in addition to their optimal operation, so that total system costs are minimized, while system benefits are maximized. In this paper, a probabilistic load model is adopted instead of utilizing time-series based models, which provide an optimal solution that is valid only for the time-series pattern that is applied.

Impact of Energy Storage Systems on Electricity Market Equilibrium

Integration of large-scale energy storage systems (ESSs) is desirable nowadays to achieve higher reliability and efficiency for smart grids. Controlling ESS operation usually depends on electricity market prices so as to charge when the price is low and discharge when the price is high. On the other hand, the market-clearing price itself is determined based on the net demand, i.e., including energy storage output, at every hour. Therefore, it is crucial to develop a mathematical model to determine the optimal ESS operation as well as the market-clearing prices. The problem is formulated as a mixed complementarity problem (MCP) that allows the representation of special (incentive) prices, which cannot be represented in a single optimization model. The proposed model is useful for power system operators to determine the optimal storage dispatch simultaneously with the market-clearing price in addition to the conventional generation dispatch. The impact of energy storage size and location on market price, total generation cost, energy storage arbitrage benefit, and total consumer payment is further investigated in this paper. The latter analysis provides some guidelines for power system planners to identify the optimal size and location for installing large-scale ESSs.

Optimal Distributed Generation Allocation and Load Shedding for Improving Distribution System Reliability

Abstract Recent deployment of distributed generation has led to a revolution in distribution systems and the emergence of “smart grid” concepts. The smart grid mainly intends to facilitate integration of renewable energy sources and to achieve higher system reliability and efficiency. Different distributed generation types found in modern distribution systems can be classified into two main categories: intermittent- and dispatchable-based distributed generation; the latter has a unique capability of enabling successful islanding operation, thus improving system reliability. This article proposes a methodology for allocating dispatchable distributed generation units in distribution systems to economically improve system reliability. Distributed generation installation and operation costs are to be optimized against the reliability value, expressed as customers’ “willingness to pay” (WTP) to avoid power interruptions. Therefore, the main goal of this research work is to determine the optimal combination between distributed generation units to be installed and loads to be shed during all possible contingencies. A probabilistic load model is adopted to determine the optimal size of allocated distributed generation units.

Optimal ESS Allocation for Benefit Maximization in Distribution Networks

Smart grids have been emerging nowadays as an initiative to operate modern distribution systems in a more economic and efficient way. Energy storage systems (ESSs) are one of the promising technologies that can achieve the goals of smart grids via facilitating the connection of renewable sources, improving system reliability, and controlling the net demand through peak load shaving, etc. In this paper, a comprehensive planning framework is introduced for ascertaining the most cost effective siting and sizing of ESSs that maximize their benefits in distribution networks. A probabilistic approach is further adopted that includes the consideration of the stochastic nature of system components. Such approach allows determining the optimal operation of ESS at each load state. Moreover, contingency planning decisions, in the form of load points to be shed during contingencies, are identified through the approach proposed.

Optimal Resource Allocation and Charging Prices for Benefit Maximization in Smart PEV-Parking Lots

The emerging interest in deployment of plug-in electric vehicles (PEVs) in distribution networks represents a great challenge to both system planners and owners of PEV-parking lots. The owners of PEV-parking lots might be interested in maximizing their profit via installing charging units to supply the PEV demand. However, with stringent rules of network upgrades, installing these charging units would be very challenging. Network constraints could be relaxed via controlling the net demand through integrating distributed generation (DG) and/or storage units. This paper presents an optimization model for determining the optimal mix of solar-based DG and storage units, as well as the optimal charging prices for PEVs. The main objective is to maximize the benefit of the PEV-parking lots owner without violating system constraints. Two cases are considered in this paper: uncoordinated and coordinated PEV demand. A novel mathematical model is further developed whereby the behavior of vehicles’ drivers, in response to different charging prices, is considered in generating the energy consumption of PEVs.

Low voltage ride through capability enhancement of wind farms' generators: DVR versus STATCOM

This paper investigates the application of dynamic voltage restorer (DVR) versus static compensator (STATCOM) to enhance low voltage ride through (LVRT) capability of wind farms. The research done in the area of LVRT focused on a single machine compensation analysis; however, no such analysis was done for entire wind farms generators. Therefore, the main contribution of this paper is to study LVRT compensation through STATCOM and/or DVR in order to provide guidelines for the implementation of each solution within large wind farms. In this paper, squirrel cage induction generators (SCIGs) are studied using a simplified approach based on torque-speed characteristics of induction machines. The transient stability margin is proposed as indicator of LVRT capability. Analytical calculations are verified against simulation results using PSCAD/EMTDC package.

Low-voltage Ride-through Capability Characterization of Wind Farms

Abstract This article characterizes low-voltage ride-through capability of wind farms. Critical clearing time has been used in the literature as a measure of the transient stability of induction generators and, hence, an indication for low-voltage ride-through capability of single wind turbine generators. Therefore, this article aims to aggregate entire wind farms into a single induction generator so that low-voltage ride-through capability can be characterized for this wind farm equivalent. The proposed model has the potential to be used for power systems analysis with large amounts of wind energy plants as the wind energy becomes more dominant in the generation mix. Case studies are further presented to show the validity of the introduced equivalent technique compared to exact wind farm modeling.

STATCOM modeling impact on wind turbines' Low Voltage Ride Through capability

Ideal Static Compensator (STATCOM) modeling may be deceiving for determining the protection device settings that will operate to fulfill Low Voltage Ride Through (LVRT) requirements of wind turbines. If these settings are not accurately calculated, premature tripping or machines instability may occur and hence LVRT will not be achieved in such cases. Therefore, a more realistic STATCOM model is introduced in this paper and compared to the ideal one. Squirrel Cage Induction Generator (SCIG) based wind turbines are studied using a simplified approach based on torque speed characteristics of induction machines. The transient stability margin is proposed as an indicator for LVRT capability. Theoretical expectations are verified by digital simulation using EMTDC simulation package.

A probabilistic approach to assess wind generation penetration and market prices

Increasing interest in integrating wind energy, as one of the promising renewable sources, has led to an increase in the uncertainty of power system operation. Probabilistic models are thus necessary to assess the performance of power systems with considerable amounts of wind generation. This paper presents a probabilistic technique for assessing the impact of wind farm location on the penetration level of the wind generation and real-time electricity market prices.