In the U.S., individual states enact Renewable Portfolio Standards (RPSs) for renewable electricity production with little coordination. Each state imposes restrictions on the amounts and locations of qualifying renewable generation. Using a co-optimization (transmission and generation) planning model, we quantify the long run economic benefits of allowing flexibility in the trading of Renewable Energy Credits (RECs) among the U.S. states belonging to the Western Electricity Coordinating Council (WECC). We characterize flexibility in terms of the amount and geographic eligibility of out-of-state RECs that can be used to meet a state’s RPS goal. Although more trade would be expected to have economic benefits, neither the size of these benefits nor the effects of such trading on infrastructure investments, CO2 emissions and energy prices have been previously quantified. We find that up to 90% of the economic benefits are captured if approximately 25% of unbundled RECs are allowed to be acquired from out of state. Furthermore, increasing REC trading flexibility does not necessarily result in either higher transmission investment costs or a substantial impact on CO2 emissions. Finally, increasing REC trading flexibility decreases energy prices in some states and increases them elsewhere, while the WECC-wide average energy price decreases.

%B The Energy Journal %V 37 %8 10/2016 %N 4 %! EJ %R 10.5547/01956574.37.4.aper %0 Journal Article %J European Journal of Operational Research %D 2016 %T New bounding and decomposition approaches for MILP investment problems: Multi-area transmission and generation planning under policy constraints %A Francisco D. Munoz %A Benjamin F. Hobbs %A Watson, J.-P. %K RM11-002 %XWe propose a novel two-phase bounding and decomposition approach to compute optimal and near-optimal solutions to large-scale mixed-integer investment planning problems that have to consider a large number of operating subproblems, each of which is a convex optimization. Our motivating application is the planning of power transmission and generation in which policy constraints are designed to incentivize high amounts of intermittent generation in electric power systems. The bounding phase exploits Jensen’s inequality to define a lower bound, which we extend to stochastic programs that use expected-value constraints to enforce policy objectives. The decomposition phase, in which the bounds are tightened, improves upon the standard Benders’ algorithm by accelerating the convergence of the bounds. The lower bound is tightened by using a Jensen’s inequality-based approach to introduce an auxiliary lower bound into the Benders master problem. Upper bounds for both phases are computed using a sub-sampling approach executed on a parallel computer system. Numerical results show that only the bounding phase is necessary if loose optimality gaps are acceptable. However, the decomposition phase is required to attain optimality gaps. Use of both phases performs better, in terms of convergence speed, than attempting to solve the problem using just the bounding phase or regular Benders decomposition separately.

%B European Journal of Operational Research %V 248 %P 888 - 898 %8 02/2016 %N 3 %! European Journal of Operational Research %R 10.1016/j.ejor.2015.07.057 %0 Journal Article %J IEEE Transactions on Power Systems %D 2015 %T Economic Analysis of Transmission Expansion Planning With Price-Responsive Demand and Quadratic Losses by Successive LP %A Ozdemir, Ozge %A Francisco D. Munoz %A Jonathan L. Ho %A Benjamin F. Hobbs %K RM11-002 %X The growth of demand response programs and renewable generation is changing the economics of transmission. Planners and regulators require tools to address the implications of possible technology, policy, and economic developments for the optimal configuration of transmission grids. We propose a model for economic evaluation and optimization of inter-regional transmission expansion, as well as the optimal response of generators' investments to locational incentives, that accounts for Kirchhoff’s laws and three important nonlinearities. The first is consumer response to energy prices, modeled using elastic demand functions. The second is resistance losses. The third is the product of line susceptance and flows in the linearized DC load flow model. We develop a practical method combining Successive Linear Programming with Gauss-Seidel iteration to co-optimize AC and DC transmission and generation capacities in a linearized DC network while considering hundreds of hourly realizations of renewable supply and load. We test our approach for a European electricity market model including 33 countries. The examples indicate that demand response can be a valuable resource that can significantly affect the economics, location, and amounts of transmission and generation investments. Further, representing losses and Kirchhoff’s laws is also important in transmission policy analyses. %B IEEE Transactions on Power Systems %P 1 - 12 %8 05/2015 %! IEEE Trans. Power Syst. %R 10.1109/TPWRS.2015.2427799 %0 Journal Article %J IEEE Transactions on Power Systems %D 2014 %T An Engineering-Economic Approach to Transmission Planning Under Market and Regulatory Uncertainties: WECC Case Study %A Francisco D. Munoz %A Benjamin F. Hobbs %A Jonathan L. Ho %A Saamrat Kasina %K RM11-002 %K transmission planning %K WECC %X We propose a stochastic programming-based tool to support adaptive transmission planning under market and regulatory uncertainties. We model investments in two stages, differentiating between commitments that must be made now and corrective actions that can be undertaken as new information becomes available. The objective is to minimize expected transmission and generation costs over the time horizon. Nonlinear constraints resulting from Kirchhoff's voltage law are included. We apply the tool to a 240-bus representation of the Western Electricity Coordinating Council and model uncertainty using three scenarios with distinct renewable electricity mandates, emissions policies, and fossil fuel prices. We conclude that the cost of ignoring uncertainty (the cost of using naive deterministic planning methods relative to explicitly modeling uncertainty) is of the same order of magnitude as the cost of first-stage transmission investments. Furthermore, we conclude that heuristic rules for constructing transmission plans based on scenario planning can be as suboptimal as deterministic plans. %B IEEE Transactions on Power Systems %V 29 %P 307 - 317 %8 01/2014 %N 1 %! IEEE Trans. Power Syst. %R 10.1109/TPWRS.2013.2279654 %0 Report %D 2014 %T New Bounding and Decomposition Approaches for Multi-Area Transmission and Generation Planning Under Policy Constraints %A Francisco D. Munoz %A Benjamin F. Hobbs %A Watson, J.P. %K RM11-002 %K transmission planning %X We propose a novel two-phase bounding and decomposition approach to compute optimal and near-optimal solutions to large-scale mixed-integer investment planning problems that have to consider a large number of operating subproblems, each of which is a convex optimization. Our motivating application is the planning of transmission and generation in which policy constraints are designed to incentivize high amounts of intermittent generation in electric power systems. The bounding phase exploits Jensen's inequality to define a new lower bound, which we also extend to stochastic programs that use expected-value constraints to enforce policy objectives. The decomposition phase, in which the bounds are tightened, improves upon the standard Benders algorithm by accelerating the convergence of the bounds. The lower bound is tightened by using a Jensen's inequality-based approach to introduce an auxiliary lower bound into the Benders master problem. Upper bounds for both phases are computed using a sub-sampling approach executed on a parallel computer system. Numerical results show that only the bounding phase is necessary if loose optimality gaps are acceptable. Attaining tight optimality gaps, however, requires the decomposition phase. Use of both phases performs better, in terms of convergence speed, than attempting to solve the problem using just the bounding phase or regular Benders decomposition separately. %8 05/2014 %U https://cfwebprod.sandia.gov/cfdocs/CompResearch/docs/New-Bounding-and-Decomposition-Approaches.pdf %0 Journal Article %J Journal of Regulatory Economics %D 2013 %T Approximations in power transmission planning: implications for the cost and performance of renewable portfolio standards %A Francisco D. Munoz %A Sauma, Enzo E. %A Benjamin F. Hobbs %K CERTS %K reliability and markets %K renewable portfolio standards (RPS) %K RM11-002 %K transmission planning %X Renewable portfolio standards (RPSs) are popular market-based mechanisms for promoting development of renewable power generation. However, they are usually implemented without considering the capabilities and cost of transmission infrastructure. We use single- and multi-stage planning approaches to find cost-effective transmission and generation investments to meet single and multi-year RPS goals, respectively. Using a six-node network and assuming a linearized DC power flow, we examine how the lumpy nature of network reinforcements and Kirchhoff’s Voltage Law can affect the performance of RPSs. First, we show how simplified planning approaches that ignore transmission constraints, transmission lumpiness, or Kirchhoff’s voltage law yield distorted estimates of the type and location of infrastructure, as well as inaccurate compliance costs to meet the renewable goals. Second, we illustrate how lumpy transmission investments and Kirchhoff’s voltage law result in compliance costs that are nonconvex with respect to the RPS targets, in the sense that the marginal costs of meeting the RPS may decrease rather than increase as the target is raised. Thus, the value of renewable energy certificates (RECs) also depends on the network topology, as does the amount of noncompliance with the RPS, if noncompliance is penalized but not prohibited. Finally, we use a multi-stage planning model to determine the optimal generation and transmission infrastructure for RPS designs that set multiyear goals. We find that the optimal infrastructure to meet RPS policies that are enforced year-by-year differ from the optimal infrastructure if banking and borrowing is allowed in the REC market. %B Journal of Regulatory Economics %V 43 %P 305 - 338 %8 6/2013 %N 3 %! J Regul Econ %R 10.1007/s11149-013-9209-8 %0 Conference Paper %B 2012 IEEE Power & Energy Society General Meeting %D 2012 %T Efficient proactive transmission planning to accommodate renewables %A Francisco D. Munoz %A Benjamin F. Hobbs %A Saamrat Kasina %K CERTS %K reliability and markets %K RM11-002 %K transmission planning %XThere is a growing need for tools to help decision makers to proactively plan for transmission infrastructure to accommodate renewables under gross market and regulatory uncertainties. In this paper, we make three contributions. First, we discuss how the current approaches aiming to proactively plan for transmission to accommodate renewables in the US are mathematically inaccurate, particularly with regards to their treatment of uncertainty. Second, improving existing models, we develop a two-stage stochastic network-planning model that takes into account Kirchhoff's laws, uncertainties, generators' response, and recourse investment decisions. Third, for large-scale networks, we demonstrate the use of Benders decomposition, taking advantage of the block-structure of the constraints. Testing our model on a simplified representation of California, we show that there are costs of ignoring uncertainty and that trying to identify robust solutions from a series of deterministic solutions is not necessarily effective, and indeed could result in higher costs than ignoring uncertainty altogether.

%B 2012 IEEE Power & Energy Society General Meeting %I IEEE %C San Diego, CA %P 1 - 7 %8 07/2012 %@ 978-1-4673-2727-5 %R 10.1109/PESGM.2012.6345237