Mohammad Reza Hesamzadeh

Bio: Mohammad Reza Hesamzadeh is an academic researcher from Royal Institute of Technology. The author has contributed to research in topics: Electricity market & Electric power system. The author has an hindex of 12, co-authored 90 publications receiving 499 citations. Previous affiliations of Mohammad Reza Hesamzadeh include Stanford University.

Data-Driven Probabilistic Optimal Power Flow With Nonparametric Bayesian Modeling and Inference

Abstract: In this paper, we propose a data-driven algorithm for probabilistic optimal power flow (POPF). In particular, we develop a nonparametric Bayesian framework based on the Dirichlet process mixture model (DPMM) and variational Bayesian inference (VBI) to establish a probabilistic model for capturing the uncertainties involved with wind generation and load power in power systems. In the proposed setup, the number of components in the mixture model can be automatically and analytically obtained from the consistently updated data. Moreover, we develop an efficient quasi-Monte Carlo sampling method to draw samples from the obtained DPMM, then propose the dynamic data-driven POPF algorithm. Performance of uncertainty modeling framework on publicly available datasets is examined by extensive numerical simulations. Furthermore, the proposed POPF algorithm is verified on multiple IEEE benchmark power systems. Numerical results show the feasibility and superiority of the proposed DPMM-based POPF algorithm for better informed decision-making in power systems with high level of uncertainties.

Second-order cone AC optimal power flow: convex relaxations and feasible solutions

Abstract: Optimal power flow (OPF) is the fundamental mathematical model to optimize power system operations. Based on conic relaxation, Taylor series expansion and McCormick envelope, we propose three convex OPF models to improve the performance of the second-order cone alternating current OPF (SOC-ACOPF) model. The underlying idea of the proposed SOC-ACOPF models is to drop assumptions of the original SOC-ACOPF model by convex relaxation and approximation methods. A heuristic algorithm to recover feasible ACOPF solution from the relaxed solution of the proposed SOC-ACOPF models is developed. The proposed SOC-ACOPF models are examined through IEEE case studies under various load scenarios and power network congestions. The quality of solutions from the proposed SOC-ACOPF models is evaluated using MATPOWER (local optimality) and LINDOGLOBAL (global optimality). We also compare numerically the proposed SOC-ACOPF models with other two convex ACOPF models in the literature. The numerical results show robust performance of the proposed SOC-ACOPF models and the feasible solution recovery algorithm.

Transmission Augmentation With Mathematical Modeling of Market Power and Strategic Generation Expansion—Part II

Abstract: This paper describes a numerical approach to solving the mathematical structure proposed in the first part of this paper. The numerical approach employs a standard genetic algorithm (GA) embedded with an island parallel genetic algorithm (IPGA). The GA handles the decision variables of the transmission network service provider, (TNSP) while the IPGA module finds the equilibrium of the electricity market. The IPGA module uses the concept of parallel islands with limited communication. The islands evolve in parallel and communicate with each other at a specific rate and frequency. The communication pattern helps the IPGA module to spread the best-found genes across all isolated islands. The isolated evolution removes the fitness pressure of the already-found optima from the chromosomes in other islands. A stability operator has been developed which detects stabilized islands and through a strong mutation process re-employs them in exploring the search space. To improve the efficiency of the proposed numerical solution, two high performance computing (HPC) techniques are used - shared-memory architecture and distributed-memory architecture. The application of the proposed approach to the assessment of transmission augmentation is illustrated using an IEEE 14-bus example system.

Production efficiency of nodal and zonal pricing in imperfectly competitive electricity markets

Abstract: Electricity markets employ different congestion management methods to handle the limited transmission capacity of the power system. This paper compares production efficiency and other aspects of nodal and zonal pricing. We consider two types of zonal pricing: zonal pricing with Available Transmission Capacity (ATC) and zonal pricing with Flow-Based Market Coupling (FBMC). We develop a mathematical model to study the imperfect competition under zonal pricing with FBMC. Zonal pricing with FBMC is employed in two stages, a day-ahead market stage and a re-dispatch stage. We show that the optimality conditions and market clearing conditions can be reformulated as a mixed integer linear program (MILP), which is straightforward to implement. Zonal pricing with ATC and nodal pricing is used as our benchmarks. The imperfect competition under zonal pricing with ATC and nodal pricing are also formulated as MILP models. All MILP models are demonstrated on 6-node and the modified IEEE 24-node systems. Our numerical results show that the zonal pricing with ATC results in large production inefficiencies due to the inc-dec game. Improving the representation of the transmission network as in the zonal pricing with FBMC mitigates the inc-dec game.

Analytic Considerations and Design Basis for the IEEE Distribution Test Feeders

Abstract: 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.

Bilateral Contract Networks for Peer-to-Peer Energy Trading

Abstract: This paper proposes bilateral contract networks as a new scalable market design for peer-to-peer energy trading Coordinating small-scale distributed energy resources to shape overall demand could offer significant value to power systems, by alleviating the need for investments in upstream generation and transmission infrastructure, increasing network efficiency and increasing energy security However, incentivising coordination between the owners of large-scale and small-scale energy resources at different levels of the power system remains an unsolved challenge This paper introduces real-time and forward markets, consisting of energy contracts offered between generators with fuel-based sources, suppliers acting as intermediaries and consumers with inflexible loads, time-coupled flexible loads and/or renewable sources For each type of agent, utility-maximising preferences for real-time contracts and forward contracts are derived It is shown that these preferences satisfy full substitutability conditions essential for establishing the existence of a stable outcome—an agreed network of contracts specifying energy trades and prices, which agents do not wish to mutually deviate from Important characteristics of energy trading are incorporated, including upstream–downstream energy balance and forward market uncertainty Full substitutability ensures a distributed price-adjustment process can be used, which only requires local agent decisions and agent-to-agent communication between trading partners

Voltage Stability Of Electric Power Systems

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A Survey of Relaxations and Approximations of the Power Flow Equations

Abstract: The power flow equations model the relationship between voltage phasors and power injections at nodes (buses) in an electric power system and are fundamental in their analysis and operation. A wealth of literature exists on these equations, many providing different representations of them. This monograph provides the first comprehensive survey of representations in the context of optimization. To achieve this the power flow representations surveyed are categorized as either relaxations or approximations. The techniques described in here form the basis of running an optimally efficient modern day power system. A Survey of Relaxations and Approximations of the Power Flow Equations is a must-read for all students and researchers working on the cutting edge of electric power systems.