Energy Management and Control of Smart Power Distribution Systems
With the development of distributed energy resources (DERs) and advancements in technology, microgrids (MGs) appear primed to become an even more integral part of the future distribution grid. In this transition to the smart power grid of the future, MGs must be properly managed and controlled to allow efficient integration of DERs. Over the past years, there has been rapid adoption of roof-top solar photovoltaic (PV) and battery electric vehicles (BEVs). Although roof-top solar PV and BEVs can provide environmental benefits (e.g., reduction of emissions), they also create various challenges for power system operators. For example, roof-top solar PV generation can create larger valleys in the demand before peak periods leading to high demand ramp rates. Furthermore, BEVs can draw large amounts of power when charging, leading to high demand spikes that may further increase the demand during peak time. As DERs become more prominent at the distribution level, actions must be taken to maximize their benefits and minimize any adverse effects they might impose on the distribution grid. The work described in this dissertation proposes a microgrid energy management system (MGEMS) based on a hybrid control algorithm that combines Transactive Control (TC) and Model Predictive Control (MPC) for efficient management and integration of DERs in prosumer-centric networked MGs. The proposed transactive MGEMS determines a charge schedule for the battery electric vehicle (BEV) and a charge-discharge schedule for the roof-top solar photovoltaic (PV) and a battery energy storage system (BESS). By managing the charge of the BEV and the power output of roof-top solar PV through the use of a BESS, the utility or system operator can prevent overloading of their infrastructure, and residential customers can reduce their costs and improve their overall savings. The proposed networked MGEMS strategy is evaluated under different BEV and solar PV-BESS penetration scenarios to study the potential impacts (e.g., voltage violations, overloading transformers and feeders) that large amounts of BEVs and solar PV-BESS systems can have on the distribution systems and how different pricing mechanisms can mitigate these impacts. This dissertation also contributes to examining the impact of DERs on the resiliency of the power distribution system to natural disasters. Test results demonstrate that the proposed microgrid energy management and control strategy shows potential to reduce peak load and power losses as well as to enhance customers’ savings. Moreover, the results also indicate that, when managed effectively, distributed energy resources can enhance the resiliency of the distribution grid. The major contributions of this dissertation are the following. Chapter 3 contributes to the development of (i) an efficient strategy to optimally incorporate and locate renewable energy sources in smart distribution networks to reduce overall power losses, peak load, and GHG emissions; (ii) an integrated energy management system that allows the resolution of unit commitment and economic dispatch problems using forecasted and actual data of wind, solar PV, and demand; (iii) an efficient BESS strategy that utilizes the forecasted data of wind power output to determine the optimal charge/discharge cycle of the BESS. Chapter 4 contributes to (iv) the development of a new hybrid TC-MPC mechanism to manage BEVs, solar PV, and BESS of networked MGs; (v) the development of transactive incentive and feedback signals based on distribution locational marginal price; (vi) provide detailed analysis of the impacts on the distribution grid due to an effective use of transactive controls for DERs management, i.e., bus voltage and power loss impacts; (vii) provide detailed cost/savings analysis for consumers/prosumers under different pricing rates when they are equipped with BEVs, roof-top solar, and BESS. Finally, Chapter 5 contributes to the development of (viii) detailed resiliency analysis of realistic case studies that show the potential benefits that DERs managed in networked MGs can provide a power distribution grid; and (ix) calculation of resilience metrics for electrical service and monetary impacts using DERs, i.e., total customer-hours of outage, total customer energy not served, total and average number of customers experiencing outage, total loss of utility revenue, and total outage costs.
Galvan, Eric, "Energy Management and Control of Smart Power Distribution Systems" (2019). ETD Collection for University of Texas, El Paso. AAI27667667.