Multi-objective, multi-year dynamic generation and transmission expansion planning- renewable energy sources integration for Iran's National Power Grid

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TRANSMISSION NETWORK EXPANSION WITH TRANSMISSION LOADING RELIEF

Transmission planning should seek to maintain or improve system security over time and facilitate robust wholesale power markets by improving transmission capacity for bulk power transfers across wide regions It includes finding the optimal plan for the electrical system expansion, it must specify the transmission lines and/or transformers that should be constructed so that the system to operate in an adequate way and in a specified planning horizon. In this paper a methodology is proposed for choosing the best transmission expansion plan using Transmission security based on contingency analysis. A procedure using sensitivity analysis is used to evaluate potential transmission connections and that provide the most improvements to overall system security .The methodology is applied to a six bus Garver system The result obtained with the proposed method are validated with the results reported in the earlier research papers

An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

Multi-level optimisation models for transmission expansion planning under uncertainty

The significant integration of renewable energy sources to electricity grids poses unprecedented challenges to power systems planning. Each of these challenges is implied by a particular circumstance faced by the system planner when devising the expansion plan, which should be tailored to address the needs and objectives of the system under consideration. Within this context, this thesis is dedicated to propose methodologies to address three timely situations that may arise when planning the expansion of the grid. In the first situation, we consider the case in which the system planner must meet established renewable penetration targets while complying with multiple deterministic security criteria. Renewable targets have been largely adopted as an important mechanism to foster the decarbonization of power systems. Hence, we propose a methodology that simultaneously identifies the optimal subset of candidate assets as well as renewable sites to be developed, while introducing the concept of compound GT n-K security criteria. In the second situation, we aim to minimize the regret of the system planner under generation expansion uncertainty. In many cases, e.g. the United Kingdom, the decision on the transmission expansion plan is taken by a market player that does not determine the future generation expansion. Within this context, we propose a 5-level MILP formulation to represent the minimization of the regret of the system planner in light of a set of credible scenarios of generation expansion while enforcing n-1 security criterion. Finally, in the third situation, the objective is to inform the optimal transmission expansion plan under ambiguity in the probability distribution of RES generation output. To do so, we present a methodology capable of determining the transmission plan under deterministic security criterion while accommodating a set of different probability distributions for RES output in order to integrate ambiguity aversion.Open Acces

Transmission Expansion Planning for Large Power Systems

abstract: Transmission expansion planning (TEP) is a complex decision making process that requires comprehensive analysis to determine the time, location, and number of electric power transmission facilities that are needed in the future power grid. This dissertation investigates the topic of solving TEP problems for large power systems. The dissertation can be divided into two parts. The first part of this dissertation focuses on developing a more accurate network model for TEP study. First, a mixed-integer linear programming (MILP) based TEP model is proposed for solving multi-stage TEP problems. Compared with previous work, the proposed approach reduces the number of variables and constraints needed and improves the computational efficiency significantly. Second, the AC power flow model is applied to TEP models. Relaxations and reformulations are proposed to make the AC model based TEP problem solvable. Third, a convexified AC network model is proposed for TEP studies with reactive power and off-nominal bus voltage magnitudes included in the model. A MILP-based loss model and its relaxations are also investigated. The second part of this dissertation investigates the uncertainty modeling issues in the TEP problem. A two-stage stochastic TEP model is proposed and decomposition algorithms based on the L-shaped method and progressive hedging (PH) are developed to solve the stochastic model. Results indicate that the stochastic TEP model can give a more accurate estimation of the annual operating cost as compared to the deterministic TEP model which focuses only on the peak load.Dissertation/ThesisPh.D. Electrical Engineering 201

Return on Investment in Transmission Network Expansion Planning Considering Wind Generation Uncertainties Applying Non-dominated Sorting Genetic Algorithm

Although significant private investment is absorbed in different sectors of power systems, transmission sector is still suffering from appropriate private investment. This is because of the pricing policies of transmission services, tariffs, and especially for investment risks. Investment risks are due to the uncertain behaviour of power systems that discourage investors to invest in the transmission sectors. In uncertain environment of power systems, a proper method is needed to find investment attractive transmission lines with high investment return and low risk. Nowadays, wind power generation has a significant portion in total generation of most power systems. However, its uncontrollable and variable nature has turned it as a main source of uncertainty in power systems. Accordingly, the wind power generation can play a fundamental role in increasing investment risk in the transmission networks. In this paper, impact of this type of generation on investment risk and returned investment cost in transmission network is investigated. With different levels of wind power penetration, the recovered values of investment cost and risk cost in transmission network are calculated and compared. This is a simple method to find investment attractive lines in presence of uncertainties. Wherein, transmission network expansion planning (TNEP) is formulated as a multi-objective optimization problem with objectives of minimizing the investment cost, maximizing the recovered investment cost and network reliability. The point estimation method (PEM) is used to address wind speed variations at wind farms sites in the optimization problem, and the NSGA II algorithm is applied to determine the trade-off regions between the TNEP objective functions. The fuzzy satisfying method is used to decide about the final optimal plan. The proposed methodology is applied on the IEEE 24-bus RTS and simplified Iran 400 kV network