Journal of Energy Engineering

We construct a general analytic framework for the transmission network investment problem in the market environment and demonstrate its application to some test systems. We define a set of metrics to quantify the improvement attained in terms of welfare for all the participants and make use of them in the evaluation of the impacts of new transmission investments under competition. The proposed metrics are useful to the central entity responsible for transmission planning to provide meaningful measures of the effects of a modification in the grid over the planning horizon. The proposed framework is particularly useful to transmission network planners to support desired environmental targets. The analysis of the effects of new investments on the participants affected by the expansion includes the assessment of appropriate environmental attributes. The consistency of the measured values in terms of these metrics allows the comparison of disparate transmission investment projects and their effective prioritization. A key element of the framework is the deployment of an optimization scheme to maximize the social welfare with and without the transmission asset investments under various bidding behaviors of the market players and contracting conditions. We report the application of the proposed framework to investigate several transmission expansion scenarios on the IEEE 24-bus reliability test system network. The results on both pool-based markets and combined pool-bilateral contract markets provide a good illustration of the capability of the framework to effectively address realistic questions in transmission investment.

Conventional transmission planning models are subject to constant debate in the context of competitive markets, due to the functional unbundling of transmission sector from generation and distribution sectors and due to the new environment regulations. A value-based transmission planning model is proposed, suitable for an unbundled transmission network service provider having no assets in the generation sector. The model minimizes the long-term transmission investment costs and the expected social costs incurred to its clients, energy producers, and consumers, in the power auctions due to transmission bottlenecks. The uncertainties involved when incorporating short-term market models into long-term planning models are modeled with probabilistic representations for the bid prices, the component availabilities, and the hourly load variations. These features make this model suitable in the new environment paradigm. Generalized Benders decomposition technique with nonsequential Monte Carlo technique is employed to solve the final stochastic mixed-integer optimization model. Case studies are given to illustrate the performance of this model by implementing it in the modified Garver’s six-bus test system and the IEEE 24-bus reliability test system for a single planning year.

In the new environmental era, electricity markets change rapidly, requiring dynamic strategic responses from market agents and regulators. In this paper, we study the intertemporal dimension of the network planner decision process. In particular, we formulate a dynamic model of transmission investments and use this model to compare the behavior of a network planner when considering and when ignoring the dynamic nature of transmission investments. This paper’s analysis focuses on the situation faced by some hubs with growing demand which meet their demand with power generated by distant sources subject to uncertainty. This is the case of a large city, which demand is satisfied by hydro or wind power supplied from sources located far away. For this kind of systems (typified as a simple two-node network that satisfies certain properties), we characterize the structure of a socially efficient transmission investment policy. It is shown that, in such a network, an optimal open-loop transmission investment policy has a multiperiod $\left(s,S\right)$ structure. The results are illustrated with a numerical example.

With the growing concern regarding climate change, the integration of renewable electric technologies into the grid has taken on increased importance over the past decade. In particular, the integration of wind energy is increasing the attention paid to power transmission investment planning, generation adequacy, and secure system operation. This attention calls for the development of new tools that can simultaneously address the economics, transmission, ancillary services, and reserve requirements associated with wind energy. This paper proposes a method for choosing the optimal plan for expanding transmission and generation considering optimal power flow, discrete plant sizes, and the resource variability of wind energy. The method minimizes total cost, i.e., the sum of the construction cost and the operation cost, to fulfill expected load. Due to the nature of transmission expansion planning and the economies of scale associated with conventional power plants, finding the expansion plan is an integer programming problem solved by a branch and bound method. The proposed method is tested by applying it to a nine-bus system.

This paper is aimed at presenting a methodology leading to the incorporation of large wind farms to the transmission planning of hydrothermal systems. We resorted to a simulation program for an optimum operation of a generation-transmission system based on stochastic dual dynamic programming and incorporated the wind energy features as well as undertook the simulations. This work was applied to an existing hydrothermal system; chiefly for evaluating the wind farm impact in three specific areas: the network expansion, the energy cost, and the effect on the reservoir water level.

A procedure is proposed to determine where and when to increase the capacity of lines and transformers in a power subtransmission network. The expansion plan must minimize cost while supplying the demand for energy over a time horizon, keeping the quality and reliability standards of the network and minimizing the impact over the environment. The procedure is iterative and takes into account AC flows, reliability analysis, different scenarios, demand uncertainty, discrete investment costs, voltage constraints, capacity, and power factor. A significant contribution of this procedure is that, along with the expansion plan, it considers the optimization of the operation, specifically the movement of transformer taps and the location and sizing of reactive banks. This allows significantly reducing or delaying the investment, thus reducing its present value. The approach ensures convergence when computing the power flows and allows making an analysis of the effects of distributed generation and, if necessary, load curtailment. The model is tested on the power subtransmission network of the most important electric power distribution company in Chile, serving a city of 6 million people.