The problem of whether, where, when, and what types of transmission facilities to build in terms of minimizing costs and maximizing net economic benefits has been a challenge for the power industry from the beginning-ever since Thomas Edison debated whether to create longer dc distribution lines (with their high losses) or build new power stations in expanding his urban markets. Today?s planning decisions are far more complex, as grids cover the continent and new transmission, generation, and demand-side technologies emerge.

%B IEEE Power and Energy Magazine %I IEEE %V 14 %8 07/2016 %N 4 %R 10.1109/MPE.2016.2547280 %0 Journal Article %J The Energy Journal %D 2016 %T The Economic Effects of Interregional Trading of Renewable Energy Certificates in the U.S. WECC %A Perez, Andres P. %A Sauma, Enzo E. %A Francisco D. Munoz %A Benjamin F. Hobbs %K RM11-002 %XIn 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 Report %D 2016 %T Planning Transmission for Uncertainty: Applications and Lessons for the Western Interconnection %A Jonathan L. Ho %A Benjamin F. Hobbs %A Pearl E. Donohoo-Vallett %A Qingyu Xu %A Saamrat Kasina %A Sang Woo Park %A Yueying Ouyang %K RM11-002 %XThis report documents the results of a project whose goal is to carefully evaluate the practicality and potential usefulness of a method for planning transmission under uncertainty. This method, called stochastic programming, quantifies the economic value of simultaneously considering multiple scenarios (or “study cases”) of economic, policy, and technology changes over a multidecadal time horizon in a single model. By considering several possible futures in one model, analysts can identify near‐term transmission additions that enhance the adaptability and robustness of the transmission grid in the face of these uncertainties.

%8 01/2016
%0 Conference Paper
%B 2016 49th Hawaii International Conference on System Sciences (HICSS)
%D 2016
%T What is the Benefit of Including Uncertainty in Transmission Planning? A WECC Case Study
%A Benjamin F. Hobbs
%A Saamrat Kasina
%A Qingyu Xu
%A Sang Woo Park
%A Jasmine Ouyang
%A Jonathan L. Ho
%A Pearl E. Donohoo-Vallett
%K RM11-002
%X The electricity industry has undergone a series of radical economic, policy, and technology changes over the past several decades. More changes are to come, to be sure, but their nature and magnitude is highly uncertain. Such changes in market fundamentals profoundly impact the economic value of transmission. This paper quantifies the economic value of stochastic programming for transmission planning over a multidecadal time horizon, considering how generation investment reacts to network reinforcements and how the grid can be adapted later on as circumstances change. The economic value is the difference between the probability-weighted present worth of cost of (1) a stochastic model that chooses first-stage (through 2024) lines to minimize that cost and (2) a stochastic model whose 2024 lines are constrained to be those that were chosen by a suboptimal process, such as deterministic decision making. Even considering a small number of scenarios can drastically improve solutions.

%B 2016 49th Hawaii International Conference on System Sciences (HICSS) %I IEEE %C Koloa, HI, USA %P 2364 - 2371 %8 01/2016 %R 10.1109/HICSS.2016.295 %0 Journal Article %J IEEE Transactions on Power Systems %D 2015 %T ATC-Based System Reduction for Planning Power Systems With Correlated Wind and Loads %A Ebrahim Shayesteh %A Benjamin F. Hobbs %A Lennart Soder %A Mikael Amelin %K CERTS %K power system planning %K reliability and markets %K RM11-002 %XSimulations of production costs, flows, and prices are crucial inputs to generation and transmission planning studies. To calculate average system performance for many alternatives over long time periods, it is necessary to simulate large numbers of hourly combinations of renewable production and loads across large regions. As this is usually impractical for full network representations of such systems, aggregation of buses and lines is desirable. We propose an improved aggregation method for creating multi-area representations of power systems that yields more accurate estimates of the quantities required by planners. The method is based on partitioning the original large system into smaller areas and making a reduced equivalent for each area. The partitioning is based on available transfer capability (ATC) between each pair of network buses. Because ATC depends on net load conditions, separate partitions are defined for subsets of similar load and wind conditions, significantly enhancing the accuracy of optimal power flow solutions. We test the method on the IEEE 118-bus test system and the Polish 3120-bus system considering 150 load/wind scenarios, comparing the results to those of admittance-based partitioning methods. Accuracy is improved with only a negligible increase in simulation time.

%B IEEE Transactions on Power Systems %V 30 %P 429 - 438 %8 1/2015 %N 1 %! IEEE Trans. Power Syst. %R 10.1109/TPWRS.2014.2326615 %0 Journal Article %J Energy Systems %D 2015 %T Co-optimization of electricity transmission and generation resources for planning and policy analysis: review of concepts and modeling approaches %A Krishnan, Venkat %A Jonathan L. Ho %A Benjamin F. Hobbs %A Liu, Andrew L. %A James D. McCalley %A Shahidehpour, Mohammad %A Zheng, Qipeng P. %K RM11-002 %X The recognition of transmission’s interaction with other resources has motivated the development of co-optimization methods to optimize transmission investment while simultaneously considering tradeoffs with investments in electricity supply, demand, and storage resources. For a given set of constraints, co-optimized planning models provide solutions that have lower costs than solutions obtained from decoupled optimization (transmission-only, generation-only, or iterations between them). This paper describes co-optimization and provides an overview of approaches to co-optimizing transmission options, supply-side resources, demand-side resources, and natural gas pipelines. In particular, the paper provides an up-to-date assessment of the present and potential capabilities of existing co-optimization tools, and it discusses needs and challenges for developing advanced co-optimization models. %B Energy Systems %8 08/2015 %! Energy Syst %R 10.1007/s12667-015-0158-4 %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 Power and Energy Magazine %D 2015 %T The Evolution of the Market: Designing a Market for High Levels of Variable Generation %A Mark Ahlstrom %A Erik Ela %A Jenny Riesz %A Jonathan O'Sullivan %A Benjamin F. Hobbs %A Mark O'Malley %A Michael Milligan %A Paul Sotkiewicz %A Jim Caldwell %K RM11-002 %XRenewable energy was not the initial justification for electricity markets, but it is rapidly becoming a driver for new markets and market design changes. Starting in 1982 with market reforms in Chile, competition has been introduced into wholesale electricity markets around the world. This trend is likely to accelerate with countries such as China planning a major restructuring of power systems that could result in electricity markets.

%B IEEE Power and Energy Magazine %V 13 %P 60 - 66 %8 11/2015 %N 6 %! IEEE Power and Energy Mag. %R 10.1109/MPE.2015.2458755 %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 IEEE Transactions on Power Systems %D 2014 %T Value of Price Responsive Load for Wind Integration in Unit Commitment %A Cedric De Jonghe %A Benjamin F. Hobbs %A Ronnie Belmans %K CERTS %K reliability and markets %K renewables integration %K RM11-002 %XThe ability of load to respond to short-term variations in electricity prices plays an increasingly important role in balancing short-term supply and demand, especially during peak periods and in dealing with fluctuations in renewable energy supplies. However, price responsive load has not been included in standard models for defining the optimal scheduling of generation units in short-term. Here, elasticities are included to adjust the demand profile in response to price changes, including cross-price elasticities that account for load shifts among hours. The resulting peak reductions and valley fill alter the optimal unit commitment. Enhancing demand response also increases the amount of wind power that can be economically injected. Further, wind power uncertainty can be managed at a lower cost by adjusting electricity consumption in case of wind forecast errors, which is another way in which demand response facilitates the integration of intermittent renewables.

%B IEEE Transactions on Power Systems %V 29 %P 675 - 685 %8 03/2014 %N 2 %! IEEE Trans. Power Syst. %R 10.1109/TPWRS.2013.2283516 %0 Generic %D 2014 %T What Investments Should be Made Now? Long Run Transmission Planning Under Uncertainty %A Benjamin F. Hobbs %K CERTS %K reliability and markets %K RM11-002 %K transmission planning %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 Journal Article %J IEEE Transactions on Power Systems %D 2012 %T Dynamic Modeling of Thermal Generation Capacity Investment: Application to Markets With High Wind Penetration %A Dan Eager %A Benjamin F. Hobbs %A Janusz W. Bialek %K electricity markets %K load modeling %K pricing %K reliability and markets %K risk analysis %K RM11-002 %K wind power %XModeling the dynamics of merchant generation investment in market environments can inform the making of policies whose goals are to promote investment in renewable generation while maintaining security of supply. Such models need to calculate expected output, costs and revenue of thermal generation subject to varying load and random generator outages in a power system with high penetrations of wind. This paper presents a dynamic investment simulation model where the short-term energy market is simulated using probabilistic production costing using the Mix of Normals distribution (MOND) technique to represent residual load (load net of wind output). Price mark-ups due to market power are accounted for. An “energy-only” market setting is used to estimate the economic profitability of investments and forecast the evolution of security of supply. Simulated results for a Great Britain (GB) market case study show a pattern of increased relative security of supply risk during the 2020s. In addition, many new investments can recover their fixed costs only during years in which more frequent supply shortages push energy prices higher.

%B IEEE Transactions on Power Systems %V 27 %P 2127 - 2137 %8 11/2012 %N 4 %! IEEE Trans. Power Syst. %R 10.1109/TPWRS.2012.2190430 %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 %0 Journal Article %J IEEE Transactions on Power Systems %D 2012 %T Optimal Generation Mix With Short-Term Demand Response and Wind Penetration %A Cedric De Jonghe %A Benjamin F. Hobbs %A Ronnie Belmans %K demand response %K load management %K power system economics %K reliability and markets %K renewables integration %K RM11-002 %X Demand response, defined as the ability of load to respond to short-term variations in electricity prices, plays an increasingly important role in balancing short-term supply and demand, especially during peak periods and in dealing with fluctuations in renewable energy supplies. However, demand response has not been included in standard models for defining the optimal generation technology mix. Three different methodologies are proposed to integrate short-term responsiveness into a generation technology mix optimization model considering operational constraints. Elasticities are included to adjust the demand profile in response to price changes, including cross-price elasticities that account for load shifts among hours. As energy efficiency programs also influence the load profile, interactions of efficiency investments and demand response are also modeled. Comparison of model results for a single year optimization with and without demand response shows peak reduction and valley filling effects, impacting the optimal amounts and mix of generation capacity. Increasing demand elasticity also increases the installed amount of wind capacity, suggesting that demand response yields environmental benefits by facilitating integration of renewable energy. %B IEEE Transactions on Power Systems %V 27 %P 830 - 839 %8 05/2012 %N 2 %! IEEE Trans. Power Syst. %R 10.1109/TPWRS.2011.2174257 %0 Conference Paper %B 2012 IEEE Power & Energy Society General Meeting %D 2012 %T Transmission planning and pricing for renewables: Lessons from elsewhere %A Benjamin F. Hobbs %K reliability and markets %K RM11-002 %K transmission planning %XTransmission operating and planning procedures in Europe and elsewhere are changing in response to the new challenges posed by wind integration. Evolving procedures for managing transmission congestion and augmenting transmission capacity in Europe and Alberta are summarized and contrasted.

%B 2012 IEEE Power & Energy Society General Meeting %I IEEE %C San Diego, CA %P 1 - 5 %8 07/2012 %@ 978-1-4673-2727-5 %R 10.1109/PESGM.2012.6344744 %0 Report %D 2011 %T Planning electricity transmission to accommodate renewables: Using two-stage programming to evaluate flexibility and the cost of disregarding uncertainty %A van der Weijde, A.H. %A Benjamin F. Hobbs %K reliability and markets %K renewables %K RM11-002 %K transmission planning %K uncertainty %X We develop a stochastic two-stage optimisation model that captures the multistage nature of electricity transmission planning under uncertainty and apply it to a stylised representation of the Great Britain (GB) network. In our model, a proactive transmission planner makes investment decisions in two time periods, each time followed by a market response. This model allows us to identify robust first-stage investments and estimate the value of information in transmission planning, the costs of ignoring uncertainty, and the value of flexibility. Our results show that ignoring risk has quantifiable economic consequences, and that considering uncertainty explicitly can yield decisions that have lower expected costs than traditional deterministic planning methods. Furthermore, the best plan under a risk-neutral criterion can differ from the best under risk-aversion. %8 01/2011 %U www.econ.cam.ac.uk/research/repec/cam/pdf/cwpe1113.pdf