Daniel L. Shawhan

A Simultaneous Perturbation Approach for Solving Economic Dispatch Problems With Emission, Storage, and Network Constraints

In this paper, an environmental economic dispatch problem with storage, network, and inter-temporal constraints is considered. An approach based on the simultaneous perturbation technique is proposed to deal with the equality and inequality constraints in the economic dispatch problem. The algorithm has been implemented using Matlab and tested on a 6-bus, 5-generator system and a 140-bus, 48-generator system. The effects of cap-and-trade policies, energy storage, and transmission line flow limits in economic dispatch are discussed. The simulations reveal that the method can handle a variety of constraints with good convergence performance.

Optimal generation investment planning: Pt. 1: network equivalents

The requirements of a network equivalent to be used in new planning tools are very different from those used in traditional equivalencing procedures. For example, in the classical Ward equivalent, each generator in the external system is broken up into fractions. For newer long-term investment applications that take into account such things as greenhouse gas (GHG) regulations and generator availability, it is computationally impractical to model fractions of generators located at many buses. To overcome this limitation, a modified- Ward equivalencing scheme is proposed in this paper. The proposed scheme is applied to the entire Eastern Interconnection (EI) to obtain several backbone equivalents and these equivalents are tested for accuracy under a range of operating conditions. In a companion paper, the application of an equivalent developed by this procedure is used to perform optimal generation investment planning.

Stochastically Optimized, Carbon-Reducing Dispatch of Storage, Generation, and Loads

We present a new formulation of a hybrid stochastic-robust optimization and use it to calculate a look-ahead, security-constrained optimal power flow. It is designed to reduce carbon dioxide (CO2) emissions by efficiently accommodating renewable energy sources and by realistically evaluating system changes that could reduce emissions. It takes into account ramping costs, CO2 damages, demand functions, reserve needs, contingencies, and the temporally linked probability distributions of stochastic variables such as wind generation. The inter-temporal trade-offs and transversality of energy storage systems are a focus of our formulation. We use it as part of a new method to comprehensively estimate the operational net benefits of system changes. Aside from the optimization formulation, our method has four other innovations. First, it statistically estimates the cost and CO2 impacts of each generators electricity output and ramping decisions. Second, it produces a comprehensive measure of net operating benefit, and disaggregates that into the effects on consumers, producers, system operators, government, and CO2 damage. Third and fourth, our method includes creating a novel, modified Ward reduction of the grid and a thorough generator dataset from publicly available information sources. We then apply this method to estimating the impacts of wind power, energy storage, and operational policies.

Optimal generation investment planning: Pt. 2: Application to the ERCOT system

Power system planning and market behavioral analysis using the full model of a large-scale network, such as the entire ERCOT system, are computationally expensive. Reducing the full network into a small equivalent is a practical way to reduce the computational burden. In a companion paper, a modified-Ward equivalencing procedure has been proposed. In this paper, the proposed scheme is applied to the ERCOT system to obtain several backbone equivalents, the accuracy of which are tested under a range of operating conditions. The ERCOT equivalent is used in a system planning tool to perform optimal generation investment studies with promising results observed.

Mapping Energy Futures Using the SuperOPF Planning Tool: An Integrated Engineering, Economic and Environmental Model

Energy futures for modern economies depend critically on the electric power system. Estimating the long-run benefits and costs of proposed energy or environmental policies requires tools that optimize investment in generation, account for physical constraints on the delivery network while maintaining desired reliability, and characterize the adverse impacts of pollutants. An integrated engineering, economic, environmental modeling framework is described (SuperOPF Planning Tool) that maximizes the net expected benefits of electricity production, optimizes retirements and investment in new generation by location, accounts for environmental and other regulations, and includes likely demand responses to resulting price changes. Simulations testing the SuperOPF Planning Tool using a reduced network model of the Northeast power system are described, and they suggest that policies that assess the full cost for energy-use usually result in more effective outcomes in terms of lives saved at lower prices than do regulatory alternatives.

The Engineering, Economic and Environmental Electricity Simulation Tool (E4ST): Description and an Illustration of Its Capability and Use as a Planning/Policy Analysis Tool

A new planning tool for analyzing power systems in detail, including the long-run technical, economic and environmental consequences of policy or investment interventions, is now available for download by the public, without charge, at E4ST.com. The Engineering, Economic and Environmental Electricity Simulation Tool and its components are described here, and its accuracy is assessed through predictions of actual LMPs in the Eastern Interconnection. The usefulness of the tool is illustrated by an evaluation of the commercial feasibility of a proposed electric transmission line connecting Hydro Quebec to New York City, the Champlain-Hudson Power Express.

A Detailed Power System Planning Model: Estimating the Long-Run Impact of Carbon-Reducing Policies

In this paper, a much more detailed representation of the nations electricity system than has been traditionally used in policy models is employed. This detailed representation greatly increases the computational difficulty of obtaining optimal solutions, but is necessary to accurately model the location of new investment in generation. Given the proposed regulation of CO2 emissions from US power plants, an examination of economically efficient policies for reducing these emissions is warranted. The model incorporates realistic physical constraints, investment and retirement of generation, and price-responsive load to simulate the effects of policies for limiting CO2 emissions over a twenty-year forecast horizon. Using network reductions for each of the three electric system regions in the U.S. And Canada, an optimal economic dispatch, that satisfies reliability criteria, is assigned for 12 typical hour-types in each year. Three scenarios are modeled that consider subsidies for renewables and either CO2 emissions regulation on new investment or cap-and-trade. High and low gas price trends are also simulated and have large effects on prices of electricity but small impacts on CO2 emissions. Low gas prices with cap-and-trade reduce CO2 emissions the most, large subsidies for renewables alone do not reduce carbon emissions much below existing levels. Extensive retirement of coal-fired power plants occurs in all cases.

Economic cost-benefit analysis for power system operations with environmental considerations

This paper presents a model aimed at evaluating the effects of integrating Renewable Energy Sources (RES) in the electricity system, from the perspective of a system operator, taking into account the cost of Carbon Dioxide (C02) emissions. The model is especially suited to analyze the interactions of energy storage systems (ESS) with conventional generation sources, in the framework of reliable operation (n - 1). One of the most important consequences of high levels of RES in the network is the variability induced on the existing generation fleet, and the wear-and-tear derived from ramping conventional units to counteract the changes in RES output. Our Security-Constrained Optimal Power Flow (SC-OPF) optimizes the injection into the network, including the cost of changes between periods for a given horizon. The results show that the main benefits derived from ESS are the reduction in the provision of ancillary services from conventional generation sources. These services are instead provided by ESS units. This is an important additional revenue stream for storage system owners, especially in the face of the cost of capital of these resources.