Sumit Paudyal

Optimal Operation of Industrial Energy Hubs in Smart Grids

This paper presents the development of a generic optimal industrial load management (OILM) model, which can be readily incorporated into energy hub management systems (EHMSs) for industrial customers, in interaction with local distribution companies (LDCs), for automated and optimal scheduling of their processes. The mathematical models comprise an objective function to minimize the total energy costs and/or demand charges for industrial customers, and a set of equality and inequality constraints to represent the industrial process, storage units, distribution system components, operators requirements, and other relevant constraints. The effectiveness of the proposed OILM model is demonstrated in two industrial customers: 1) a flour mill; and 2) a water pumping facility. The results show that the proposed OILM model, in conjunction with communication and control infrastructures at the customer and LDC levels, would allow optimal operation of industrial EHMSs in smart grids.

Analytic Considerations and Design Basis for the IEEE Distribution Test Feeders

For nearly 20 years, the Test Feeder Working Group of the Distribution System Analysis Subcommittee has been developing openly available distribution test feeders for use by researchers. The purpose of these test feeders is to provide models of distribution systems that reflect the wide diversity in design and their various analytic challenges. Because of their utility and accessibility, the test feeders have been used for a wide range of research, some of which has been outside the original scope of intended uses. This paper provides an overview of the existing distribution feeder models and clarifies the specific analytic challenges that they were originally designed to examine. Additionally, this paper will provide guidance on which feeders are best suited for various types of analysis. The purpose of this paper is to provide the original intent of the Working Group and to provide the information necessary so that researchers may make an informed decision on which of the test feeders are most appropriate for their work.

Bidirectional optimal operation of smart building-to-grid systems

This paper proposes a novel bidirectional optimization of buildings integrated to the smart distribution grid, which possess potential benefits to the customers and utilities both. Mathematical models required for the optimal operations of buildings and grids are developed and a new method is proposed to obtain the solution of the bidirectional optimization. In this work, minimization of the cost of energy is chosen as an objective for the building load management, while the distribution utilities aim to increase load penetration by maximizing the load factor. Case studies are carried out based on actual data collected from an office building at Michigan Technological University, and using a standard distribution test feeder. Studies demonstrate that the proposed bidirectional optimization is beneficial to both the customer and the distribution grid as it shows significant saving in the energy costs and improvement on the system load factor.

Bilevel Optimization Framework for Smart Building-to-Grid Systems

This paper proposes a novel framework suitable for bilevel optimization in a system of commercial buildings integrated to smart distribution grid. The proposed optimization framework consists of comprehensive mathematical models of commercial buildings and underlying distribution grid, their operational constraints, and a bilevel solution approach which is based on the information exchange between the two levels. The proposed framework benefits both entities involved in the building-to-grid (B2G) system, i.e., the operations of the buildings and the distribution grid. The framework achieves two distinct objectives: increased load penetration by maximizing the distribution system load factor and reduced energy cost for the buildings. This study also proposes a novel B2G index, which is based on building’s energy cost and nodal load factor, and represents a metric of combined optimal operations of the commercial buildings and distribution grid. The usefulness of the proposed framework is demonstrated in a B2G system that consists of several commercial buildings connected to a 33-node distribution test feeder, where the building parameters are obtained from actual measurements at an office building at Michigan Technological University.

Optimum Aggregation and Control of Spatially Distributed Flexible Resources in Smart Grid

This paper presents an algorithm to optimally aggregate spatially distributed flexible resources at strategic microgrid/smart-grid locations. The aggregation reduces a distribution network having thousands of nodes to an equivalent network with a few aggregated nodes, thereby enabling distribution system operators (DSOs) to make faster operational decisions. Moreover, the aggregation enables flexibility from small distributed flexible resources to be traded to different power and energy markets. A hierarchical control architecture comprising a combination of centralized and decentralized control approaches is proposed to practically deploy the aggregated flexibility. The proposed method serves as a great operational tool for DSOs to decide the exact amount of required flexibilities from different network section(s) for solving grid constraint violations. The effectiveness of the proposed method is demonstrated through simulation of three operational scenarios in a real low voltage distribution system having high penetrations of electric vehicles and heat pumps. The simulation results demonstrated that the aggregation helps DSOs not only in taking faster operational decisions, but also in effectively utilizing the available flexibility.

Hierarchical optimization framework for demand dispatch in building-grid systems

This paper develops a hierarchical framework required to solve optimal demand dispatch of multiple buildings coordinating building energy management systems (BEMSs) and distribution system operation (DSO) control center. The proposed framework consists of mathematical model of heating, ventilation and air-conditioning (HVAC) load in buildings, model of distribution grid, objectives of BEMSs and DSO, operational requirements at building and grid levels, and a coordination algorithm. Usefulness of the proposed framework is demonstrated through HVAC loads in 27 commercial buildings connected to the IEEE 13-node test feeder. In the study, the objectives of the BEMSs and DSO are set to minimize the energy costs in dynamic pricing and power losses in distribution network, respectively. Results demonstrate that coordinated demand dispatch process honors objectives and operational constraints set by both entities, i.e., BEMSs and DSO, and benefits both entities involved in the demand dispatch process.

Out-of-step protection for multi-machine power systems using local measurements

The classical equal area criterion in the power-angle domain, which is typically used for power systems planning/stability studies, is modified to the time domain for out-of-step protection. Wide-area measurements are necessary to obtain the power-angle information if the traditional equal area criterion is applied for out-of-step detection. However, its time-domain modification requires only the information local to the out-of-step relay. The proposed method evaluates the transient energy, which is the area under the power-time curve, and by comparing the areas, differentiation between stable and out-of-step swings is made. The proposed method can be directly applied to multimachine power systems without network reduction, unlike the conventional equal area criterion in which the equivalent two area of the multimachine system needs to be obtained. The proposed out-of-step detection method has been tested on a Single Machine Infinite Bus System and a 17-Bus Multimachine system.

Optimal capacitor placement and sizing considering load profile variations using moth-flame optimization algorithm

This paper develops a mathematical model for optimal capacitor placement and sizing in radial distribution systems. The optimization model finds placement and sizes of capacitors considering variations on load profiles with 15-minute resolution. A recently developed heuristic algorithm, Moth-flame Optimization Algorithm, is modified and used to solve the model. Optimization model is tested on a modified 33-node distribution feeder. Two simulation cases are considered: the first one assumes a constant tap position of the regulators, the second one adjusts the tap positions optimally to some constant daily values. The simulation results show the improvement of the voltage profiles with the modified Moth-flame Optimization.

Selecting control input type for a building predictive controller integrated in a power grid

Application of Model Predictive Control (MPC) for a Smart Building in a Smart Grid environment is studied by using an experimentally validated building thermal model. The goal is to compare three control input types for an office buildings Heating, Ventilation, and Air Conditioning (HVAC) system, and select the control type with the best performance. Three types of MPC control input are considered for the HVAC system: (1) solitary control over the supply air temperature, (2) solitary control over the air mass flow rate, and (3) combined control over the supply air temperature and mass flow rate. An objective function is defined based on an introduced Normalized Performance Index (NP-Index) which balances price minimization while maintaining a balanced steady load profile in the grid which benefits customers and the distribution grid utility. The results show that using the combined control approach leads to 20% improvement on NP-Index compared to the solitary mass flow rate control. Additionally, controlling both the supply air temperature and air mass flow rate reduces power consumption by 4% and 13% compared to solitary air temperature control and solitary air mass flow rate control, respectively.

Out-of-step detection using Zubov's approximation stability boundaries

This paper presents a new out-of-step detection method for multi-machine power systems based on approximate stability boundaries. The boundaries are constructed based on Zubovs method of stability analysis. The proposed out-of-step detection method first constructs a series of boundaries in power angle - frequency (δ-ω) plane, and tracks the trajectory of each generator in the δ-ω plane after the disturbance to differentiate out-of-step from stable power swings. The electrical parameters needed to construct approximate stability boundaries are obtained directly from Phasor Measurement Units (PMUs) located at the generators terminal. The effectiveness of the proposed method is tested in a Single Machine Infinite Bus (SMIB) and the IEEE 3-machine 9-bus system. Simulation results show that the proposed algorithm is capable of detecting out-of-step conditions in multi-machine power systems without using network reduction techniques.