Anderson Hoke

Steady-State Analysis of Maximum Photovoltaic Penetration Levels on Typical Distribution Feeders

This paper presents simulation results for a taxonomy of typical distribution feeders with various levels of photovoltaic (PV) penetration. For each of the 16 feeders simulated, the maximum PV penetration that did not result in a steady-state voltage or current violation is presented for several PV location scenarios: clustered near the feeder source, clustered near the midpoint of the feeder, clustered near the end of the feeder, randomly located, and evenly distributed. In addition, the maximum level of PV is presented for single, large PV systems at each location. Maximum PV penetration was determined by requiring that feeder voltages stay within ANSI Range A and that feeder currents stay within the ranges determined by overcurrent protection devices. Generation ramp rates, protection and coordination, and other factors that may impact maximum PV penetrations are not considered here. Simulations were run in GridLAB-D using hourly time steps over a year with randomized load profiles based on utility data and typical meteorological year weather data. For 86% of the 336 cases simulated, maximum PV penetration was at least 30% of peak load.

Electric vehicle charge optimization including effects of lithium-ion battery degradation

This paper presents a method for minimizing the cost of electric vehicle (EV) charging given variable electricity costs while also accounting for estimated costs of battery degradation using a simplified lithium-ion battery lifetime model. The simple battery lifetime model, also developed and presented here, estimates both energy capacity fade and power fade due to temperature, state of charge profile, and daily depth of discharge. This model has been validated by comparison with a detailed model [6], which in turn has been validated through comparison to experimental data. The simple model runs quickly in a MATLAB script, allowing for iterative numerical minimization of charge cost. EV charge profiles optimized as described here show a compromise among four trends: charging during low-electricity cost intervals, charging slowly, charging towards the end of the available charge time, and suppression of vehicle-to-grid power exportation. Finally, simulations predict that batteries charged using optimized charging last longer than those charged using typical charging methods, potentially allowing smaller, cheaper batteries to meet vehicle lifetime requirements.

Accounting for Lithium-Ion Battery Degradation in Electric Vehicle Charging Optimization

This paper presents a method for minimizing the cost of vehicle battery charging given variable electricity costs while also accounting for estimated costs of battery degradation using a simplified lithium-ion battery lifetime model. The simple battery lifetime model, also developed and presented here, estimates both energy capacity fade and power fade and includes effects due to temperature, state of charge profile, and daily depth of discharge. This model has been validated by comparison with a detailed model developed at National Renewable Energy Laboratory, which in turn has been validated through comparison with experimental data. The simple model runs quickly, allowing for iterative numerical minimization of charge cost, implemented on the charger controller. Resulting electric vehicle (EV) charge profiles show a compromise among four trends: 1) charging during low-electricity cost intervals; 2) charging slowly; 3) charging toward the end of the available charge time; and 4) suppression of vehicle-to-grid power exportation. Simulations based on experimental Prius plug-in hybrid EV usage data predict that batteries charged using optimized charging last significantly longer than those charged using typical charging methods, potentially allowing smaller batteries to meet vehicle lifetime requirements. These trends are shown to hold across a wide range of battery sizes and hence are applicable to both EVs and plug-in hybrid EVs.

A microgrid modeling and simulation platform for system evaluation on a range of time scales

This paper presents a simulation platform for the modeling and study of microgrid (MG) power systems. Using MathWorks Simulink modeling software, the platform provides a library of tools for designing and simulating the behavior of an MG on time scales from seconds to days. The library includes a collection of power system and power electronics components (sources, loads, switches, etc.) that may be arbitrarily configured. The platform also facilitates the study of energy management systems (EMS), which optimize the behavior of certain controllable sources and loads according to programmed algorithms. User-generated EMS routines can be integrated into an MG model.

Maximizing lithium ion vehicle battery life through optimized partial charging

The limited lifetime, high cost, and large size of current lithium ion batteries are some of the primary obstacles to wider adoption of electric vehicles and plug-in hybrid electric vehicles. Simulations presented in this paper predict that Li-ion battery life can be extended through intelligent charging, especially when predictions of next-day energy needs are used to charge the battery only as needed. As-needed charging minimizes battery degradation by minimizing time spent at high state-of-charge. Preliminary results presented here indicate that the battery of a vehicle used for daily commuting and short errands could see its useable life extended by up to 150 % over unoptimized charging.

Real-time photovoltaic plant maximum power point estimation for use in grid frequency stabilization

As the amount of solar photovoltaic (PV) generation connected to electric grids grows, PV displaces conventional rotating machines whose inertia stabilizes the grid frequency on fast time scales. Therefore, especially in low-inertia grids, it may be desirable for PV inverters to control their output power to emulate the inertial response of conventional generators. This paper presents and validates through dynamic simulation a method of providing primary frequency regulation and inertia-like response from PV without energy storage by operating somewhat below maximum power. A novel method of ensuring sufficient power reserve in real time using measured irradiance and temperature is presented and validated against experimental data.

A power hardware-in-the-loop framework for advanced grid-interactive inverter testing

This paper presents a power hardware-in-the-loop (PHIL) framework for testing advanced inverter features such as voltage regulation and frequency response that interact dynamically with the electric grid. The PHIL model simulates grid voltage dynamics using a simplified Thévenin-based model and simulates grid frequency dynamics using a turbine-governor model including droop, inertia, and damping. Also presented are a statistical analysis of short-circuit impedances in the IEEE 8500-node test feeder, and analytical justification for approximating Thévenin impedances at inverter connection points as short-circuit impedances. Test results are presented for two inverters performing volt-VAr control, high-frequency power curtailment, voltage and frequency ride-through, and abnormal voltage disconnection while connected to the PHIL system. Results confirm advanced grid support functions have the desired effects when performing voltage regulation and high-frequency power curtailment while riding through large voltage and frequency transients. Some PHIL tests presented here replicate IEEE 1547.1-style conformance tests; no evidence is seen that grid dynamic response emulation affects the results of such conformance tests.

Power hardware-in-the-loop testing of multiple photovoltaic inverters' volt-var control with real-time grid model

Traditional testing methods fall short in evaluating interactions between multiple smart inverters providing advanced grid support functions due to the fact that such interactions largely depend on their placements on the electric distribution systems with impedances between them. Even though significant concerns have been raised by the utilities on the effects of such interactions, little effort has been made to evaluate them. In this paper, power hardware-in-the-loop (PHIL) based testing was utilized to evaluate autonomous volt-var operations of multiple smart photovoltaic (PV) inverters connected to a simple distribution feeder model. The results provided in this paper show that depending on volt-var control (VVC) parameters and grid parameters, interaction between inverters and between the inverter and the grid is possible in some extreme cases with very high VVC slopes, fast response times and large VVC response delays.

Rapid Active Power Control of Photovoltaic Systems for Grid Frequency Support

As deployment of power electronic coupled generation such as photovoltaic (PV) systems increases, grid operators have shown increasing interest in calling on inverter-coupled generation to help mitigate frequency contingency events by rapidly surging active power into the grid. When responding to contingency events, the faster the active power is provided, the more effective it may be for arresting the frequency event. This paper proposes a predictive PV inverter control method for very fast and accurate control of active power. This rapid active power control (RAPC) method will increase the effectiveness of various higher-level controls designed to mitigate grid frequency contingency events, including fast power-frequency droop, inertia emulation, and fast frequency response, without the need for energy storage. The RAPC method, coupled with a maximum power point estimation method, is implemented in a prototype PV inverter connected to a PV array. The prototype inverter’s response to various frequency events is experimentally confirmed to be fast (beginning within 2 line cycles and completing within 4.5 line cycles of a severe test event) and accurate (below 2% steady-state error).

Testing advanced photovoltaic inverters conforming to IEEE standard 1547 - Amendment 1

This paper introduces a new test plan and provides results for testing photovoltaic inverters with advanced grid support features including voltage regulation, wider voltage and frequency operating ranges, and voltage and frequency ride-through, as allowed by IEEE Standard 1547-Amendment 1. The test plan emphasizes testing for interactions between and among advanced inverter features and conventional features (e.g., unintentional islanding), and it includes testing of inverter dynamic response when regulating voltage. Results are included from testing of a single-phase inverter and a three-phase inverter.