This paper presents a small signal stability analysis of a grid-forming inverter when dynamics of transmission lines and nodal voltages are considered or neglected. Electromagnetic transients of lines are usually ignored in traditional power systems small signal stability studies due to separation of time-scales. However, the former assumption may have different implications in the case of inverter dominated power systems, and requires further study. In this paper, we perform an eigenvalue analysis of a virtual synchronous machine connected to an infinite bus under several operating conditions. This allows us to study the effect of line and voltage dynamics approximations on small signal stability. Results show that although the eigenvalues are close for different levels of approximation, the small signal stability regions could significantly differ depending on the approximation used.

Increasing quantities of renewable energy generation has yielded a need for greater energy storage capacity in power systems. Thermal storage in variable air volume (VAV) heating, ventilation, and air conditioning (HVAC) in commercial buildings has been identified as an inexpensive source of grid storage, but the true costs are not known. Recent literature explores the inefficiency associated with providing grid services from these HVAC-based demand response (DR) resources by employing a battery analogy to calculate round-trip efficiency (RTE). Results vary significantly across studies and in some cases reported efficiencies are strikingly low. This article has three objectives to address these prior results. First, we synthesize and expand on insights into existing literature by systematically exploring the potential causes for the discrepancies in results. We reinforce previous work indicating baseline modeling may drive differences across studies and deduce that control accuracy plays a role in the major differences between experiments and simulation. Second, we discuss why the RTE metric is problematic for DR applications, discuss another proposed metric, additional energy consumption (AEC), and propose an extension, which we call uninstructed energy consumption (UEC), to evaluate DR performance. Finally, we explore the merits of different metrics using experimental data and highlight UEC's reduced sensitivity to the characteristics of the DR signal than previously proposed metrics.

Power systems have evolved following a century-old paradigm of planning and operating a grid based on large central generation plants connected to load centers through a transmission grid and distribution lines with radial flows. This paradigm is being challenged by the development and diffusion of modular generation and storage technologies. We use a novel approach to assess the sequencing and pacing of centralized, distributed, and off-grid electrification strategies by developing and employing the grid and access planning (GAP) model. GAP is a capacity expansion model to jointly assess operation and investment in utility-scale generation, transmission, distribution, and demand-side resources. This paper conceptually studies the investment and operation decisions for a power system with and without distributed resources. Contrary to the current practice, we find hybrid systems that pair grid connections with distributed energy resources (DERs) are the preferred mode of electricity supply for greenfield expansion under conservative reductions in photovoltaic panel (PV) and energy storage prices. We also find that when distributed PV and storage are employed in power system expansion, there are savings of 15%-20% mostly in capital deferment and reduced diesel use. Results show that enhanced financing mechanisms for DER PV and storage could enable 50%-60% of additional deployment and save 15 $/MWh in system costs. These results have important implications to reform current utility business models in developed power systems and to guide the development of electrification strategies in underdeveloped grids.

Increased sensing and data collection in electric power systems from utility to minigrid to individual household scale are resulting in an explosion of data collection about users and providers of electricity services. In the push to expand energy access for poor communities, the collection, use, and curation of these data have historically taken a back seat to the goal of expanding energy access but are increasingly being recognized as important issues. We review the nascent literature on this topic, characterize current data management practices, and examine how expanding access to data and data sharing are likely to provide value and pose risks to key stakeholders: end users of electricity, microutilities, macroutilities, governments, development institutions, and researchers. We identify the key opportunities and tensions and provide recommendations for the design and implementation of new data-sharing practices and platforms. Our review and analysis suggest that although a common and open platform for sharing technical data can mitigate risks and enable efficiency, fewer benefits are likely to be realized from sharing detailed financial data. We also recommend codesigning practices with each stakeholder group, increasing legal protections for end users of electricity and using deep qualitative data in addition to quantitative metrics.

Network connectivity is often one of the most challenging aspects of deploying sensors. In many countries, cellular networks provide the most reliable, highest bandwidth, and greatest coverage option for Internet access. While this makes smartphones a seemingly ideal platform to serve as a gateway between sensors and the cloud, we find that a device designed for multi-tenant operation and frequent human interaction becomes unreliable when tasked to continuously run a single application with no human interaction, a seemingly counter-intuitive result. Further, we find that economy phones cannot physically withstand continuous operation, resulting in a surprisingly high rate of permanent device failures in the field. If these observations hold more broadly, they would make mobile phones poorly suited to a range of sensing applications for which they have been rumored to hold great promise.

This paper discusses conceptual frameworks for actively involving highly distributed loads in power system control actions. The context for load control is established by providing an overview of system control objectives, including economic dispatch, automatic generation control, and spinning reserve. The paper then reviews existing initiatives that seek to develop load control programs for the provision of power system services. We then discuss some of the challenges to achieving a load control scheme that balances device-level objectives with power system-level objectives. One of the central premises of the paper is that, in order to achieve full responsiveness, direct load control (as opposed to price response) is required to enable fast time scale, predictable control opportunities, especially for the provision of ancillary services such as regulation and contingency reserves. Centralized, hierarchical, and distributed control architectures are discussed along with benefits and disadvantages, especially in relation to integration with the legacy power system control architecture. Implications for the supporting communications infrastructure are also considered. Fully responsive load control is illustrated in the context of thermostatically controlled loads and plug-in electric vehicles.