Santiago Grijalva

Prosumer-based smart grid architecture enables a flat, sustainable electricity industry

Managing distributed energy sources, energy storage, and consumers active behavior coupled with sustainability objectives, requires significant changes in the architecture and technologies used to control the electricity infrastructure. Electricity consumers are evolving into economically motivated “prosumers” that not only consume, but can also produce and store electricity. Prosumers can become smart energy ecosystems if they are equipped with technology and intelligence that allow them to achieving their own objectives. This paper demonstrates that any electric power system, from large interconnections to homes and appliances can be modeled as a prosumer. It shows that the emerging interactions and transactions related to electrical energy can be implemented using a prosumer-based architecture, which would replace the traditional, one-way, generation-transmission-distribution-consumer model. We propose a prosumer-based, service-oriented architecture, that is remarkably flexible and scalable, and which would ultimately enable a “flat” business paradigm across the industry. We describe the major components and services of this architecture, present an application to the problem of demand response, and discus several innovative features enabled by the proposed paradigm.

Modeling for Residential Electricity Optimization in Dynamic Pricing Environments

This paper proposes an energy scheduling model and optimization algorithms for residential electricity consumers who attempt to optimally schedule their electricity consumption, generation and storage in a dynamic pricing environment. We describe an optimization problem which integrates electric, thermodynamic, economic, comfort, and possibly environmental parameters. We present the algorithmic solution and provide simulations results, based on a robust optimization approach which minimizes the impact of stochastic input on the objective function. We argue that the scheduling problem is complex enough to be beyond the analytical capabilities of average residential customers. This result supports the need of scheduling controllers deployed as Home Energy Management Systems (HEMS).

Increased Wind Revenue and System Security by Trading Wind Power in Energy and Regulation Reserve Markets

Due to the variability and limited predictability of wind power, wind producers participating in most electricity markets are subject to significant deviation penalties during market settlements, and system operators need to schedule additional reserve to balance the unpredicted wind power variations. This paper proposes a combined energy and regulation reserve market model to encourage wind producers to regulate their short-term outputs. With a reserve market designed with lower deviation penalties, wind producers can increase their revenue by optimally bidding in the energy and reserve markets to reduce their deviation penalties. Meanwhile, part of the intrahour wind variations, which would have appeared in the system energy balance, is diverted into the system regulation reserve. The system then benefits from facing less wind energy intrahour variations, demanding less short-term reserve for wind variations, and having additional fast, although variable, regulation reserve from wind plants, which are likely to enhance grid security and operations in high wind penetration scenarios. A test case is studied to demonstrate the effectiveness of the proposed market model and bidding strategy on increasing the wind plant revenue and grid security.

Enhancement of linear ATC calculations by the incorporation of reactive power flows

Fast, accurate algorithms to compute network capabilities are indispensable for transfer-based electricity markets. Most transfer studies involve contingencies and multipattern scenarios that often can only be performed in reasonable time with the use of linear methods. One of the limitations of linear ATC is the error produced by neglecting the effect of reactive power flows in line loading. This paper describes a fast algorithm to incorporate this effect. The estimation of the line post-transfer complex flow is based on circle equations and a megavar-corrected megawatt limit. The method can be easily integrated into existing linear ATC software because the computation remains based on active power distribution factors. The algorithm is illustrated in a small example and the error correction demonstrated for transfers in larges systems.

The role of big data in improving power system operation and protection

This paper focuses on the use of extremely large data sets in power system operation, control, and protection, which are difficult to process with traditional database tools and often termed big data. We will discuss three aspects of using such data sets: feature extraction, systematic integration for power system applications, and examples of typical applications in the utility industry. The following analytics tasks based on big data methodology are elaborated upon: corrective, predictive, distributed and adaptive. The paper also outlines several research topics related to asset management, operation planning, realtime monitoring and fault detection/protection that present new opportunities but require further investigation.

Realizing smart grid benefits requires energy optimization algorithms at residential level

One of the objectives of smart grid is to enable participation by informed customers in order to realize money and energy savings, and environmental benefits. This paper discusses the critical role that energy optimization algorithms will play at residential level to effectively achieve these benefits. A formulation of the optimization problem based on mixed-integer linear programming theory is proposed, and the implications of energy optimization algorithms on consumers, energy policies and markets are discussed.

Large-Scale Integration of Wind Generation Including Network Temporal Security Analysis

This paper presents a methodology to assess large-scale wind generation projects that considers their effect on network security. The proposed method is based on contingency analysis, including temporal study. Inputs to the simulation are grid model, forecasted load, conventional generation profiles, and wind variability of proposed projects. A time-step simulation is run for the time horizon to produce benefit indices for every location (bus) in the system. The congested transmission elements that require expansion are identified and ranked as part of the simulation. Each wind project in the proposed portfolio can result in benefits or costs for grid security. Policy makers can then use the method to design policies that ensure preservation of long-term system security. Developers could use the tool to identify security effects and assess their wind portfolios. Measuring network security and determining benefits of large-scale wind projects is a complex planning task that involves several aspects: temporal wind variability, spatial distribution of flows, multiple load and generation profiles, and numerous possible contingencies. All these wind project development aspects must be isolated to identify and correctly assign security costs and benefits

Leveraging AMI Data for Distribution System Model Calibration and Situational Awareness

The many new distributed energy resources being installed at the distribution system level require increased visibility into system operations that will be enabled by distribution system state estimation (DSSE) and situational awareness applications. Reliable and accurate DSSE requires both robust methods for managing the big data provided by smart meters and quality distribution system models. This paper presents intelligent methods for detecting and dealing with missing or inaccurate smart meter data, as well as the ways to process the data for different applications. It also presents an efficient and flexible parameter estimation method based on the voltage drop equation and regression analysis to enhance distribution system model accuracy. Finally, it presents a 3-D graphical user interface for advanced visualization of the system state and events. We demonstrate this paper for a university distribution network with the state-of-the-art real-time and historical smart meter data infrastructure.

A Structure-Preserving Model and Sufficient Condition for Frequency Synchronization of Lossless Droop Inverter-Based AC Networks

This paper presents a new method for analysis of frequency synchronization of lossless power networks whose sources are frequency-droop controlled inverters. Unlike most existing approaches, our method focuses on the interaction between inverters and the network to provide new physical insight into how those interactions create frequency synchronization. We introduce two structure-preserving models of such a network (one bus-oriented and one line-oriented), and show that frequency synchronization corresponds to convergence to an equilibrium of these models. We derive a necessary condition for existence of such equilibria, and determine a simple test for their local stability. Finally, we introduce a sufficient condition for frequency synchronization of such networks, and show that it consists of a set of local criteria which can each be determined from local measurements.

Reactive power considerations in linear ATC computation

The paper presents some initial concepts on including reactive power in linear methods for computing Available Transfer Capability (ATC). It proposes a new approach that first determines the reactive power flows using the exact circle equation for the transmission line complex flow, and then determines ATC using active power distribution factors. The ideas are demonstrated on 3-bus and 7-bus systems, and the results are discussed and compared with those obtained without reactive power considerations, and full nonlinear solutions.