Alberto J. Lamadrid

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.

Scheduling of Energy Storage Systems with Geographically Distributed Renewables

Renewable energy sources (RES) are very likely to continue the upward capacity trend witnessed in the past years. The reasons for adoption are varied and respond to both market pressures, influence of government intervention and a raised awareness of the consequences on the environment of the current generation fleet. The change from dispatch able generation to an environment in which Independent System Operators (ISOs), Regional Transmission Operators (RTOs) and consumers, among others, accommodate the demand to the available generation, requires fundamental changes in the way the system is managed. Also, to better harness the energy from renewable sources, both new methods and technologies need to be adopted, counteracting for the sometimes unpredictable behavior of these sources. This study proposes a method with multi-period optimization to help prescribe the optimal placement and usage of RES and Energy Storage Systems (ESS) with full information of the system. Four cases are analyzed in their dispatches, as well as the benefits to the participants in the wholesale market, for a reduced 30-bus network. While the data requirements are high, and the use of a reduced system limits the applications herein proposed, the policy implications from the results obtained provide useful insights into an ongoing debate regarding on how to direct investment in the electrical system.

Are existing ancillary service markets adequate with high penetrations of variable generation

The inherent variability of wind generation may 1) increase the operating costs of the conventional generators used to follow the net load not supplied by wind capacity (i.e. due to additional ramping costs), and 2) increase the amount of reserve conventional generating capacity needed to maintain Operating Reliability. For customers, the higher operating costs for conventional generators caused by additional ramping are largely offset by lower wholesale prices, due to reductions in the total annual generation from fossil fuels. However, the lower wholesale prices (

The Hidden System Costs of Wind Generation in a Deregulated Electricity Market

/MWh) imply lower annual earnings for conventional generators that lead to higher amounts of missing money (

Alternate mechanisms for integrating renewable sources of energy into electricity markets

/MW) needed to maintain the Financial Adequacy of installed generating units. In addition, the operating costs for the generating units that provide ramping will be higher, and these costs are not covered in the standard markets that supply regulation. The objective of this paper is to determine how wind variability affects the optimal hour-to-hour dispatch of generating units and the corresponding operating costs and wholesale prices. The results show that incorporating the cost of ramping can have substantial effects on these costs and on the optimum amount of wind capacity dispatched and the amount of reserve generating capacity needed for reliability. The Cornell SuperOPF is used to illustrate how the operating costs and wholesale prices can be determined for a reliable network (the amount of conventional generating capacity needed to maintain Operating Reliability is determined endogenously). In previous research using the SuperOPF, the analyses have been based on optimizing the dispatch and reserves for typical hours. In contrast, the results in this paper use a typical daily pattern of load and capture the cost of ramping by including additions to the operating costs of the generating units associated with the hour-to-hour changes in their optimal dispatch. The calculations for determining endogenous up and down reserves are included, and the wind generation cost is assumed to be zero. Additionally, the maximum and minimum available capacities for all hours in the day are constrained to the optimal capacities for the hours with the highest and the lowest loads. Different scenarios are evaluated for a given hourly realization of wind speeds using specified amounts of installed wind capacity with and without ramping costs. The analysis also evaluates the effects of eliminating network constraints and the daily variability of the wind resource.

Is Deferrable Demand an Effective Alternative to Upgrading Transmission Capacity

Earlier research has shown that adding wind capacity to a network can lower the total annual operating cost of meeting a given pattern of loads by displacing conventional generation. At the same time, the variability of wind generation and the need for higher levels of reserve generating capacity to maintain reliability standards impose additional costs on the system that should not be ignored. The important implication for regulators is that the capacity cost of each MW of peak system load is now much higher. Hence, the economic benefits to a network of using storage and controllable load to reduce the peak system load will be higher with high penetrations of wind generation. These potential benefits will be illustrated in a case study using a test network and the SuperOPF. An important feature of the SuperOPF is that the amount of conventional generating capacity needed to maintain Operating Reliability is determined endogenously, and as a result, it is possible to determine the net social benefits of relying more on an intermittent source of generation, such as wind capacity, that lowers operating costs but increases the cost of maintaining System Adequacy. The capabilities of the SuperOPF provide a consistent economic framework for evaluating Operating Reliability in real-time markets and System Adequacy for planning purposes. Basically, a financially viable investment requires that the reductions in the total annual costs of the existing system should be larger than the annualized cost of financing the addition of, for example, wind generation to a network. The scenarios considered make it possible to determine 1) the amount of conventional generating capacity needed to meet the peak system load and maintain System Adequacy, 2) the amount of missing money paid to generators to maintain Financial Adequacy, 3) changes in the congestion rents for transmission that are collected by the system operator, and finally, 4) the total annual system costs paid by customers directly in the Wholesale Market and, indirectly, as missing money. The results show that the benefits (i.e. the reduction in the total annual system costs) from making an investment in wind capacity and/of upgrading a tie line are very sensitive to 1) how much of the inherent variability of wind generation has to be accommodated on the network, and 2) how the missing money paid to conventional generators is determined (e.g. comparing a regulated market and a deregulated market).

The Effect of Stochastic Wind Generation on Ramping Costs and the System Benefits of Storage

The objective of this paper is to contrast the effect of demand side versus supply side policies aimed at operating a secured system, while maintaining the sustainability of the system by analyzing: 1) the role that load following costs can have in counteracting the impact of unpredictable Renewable Energy Sources (RES) on system operation and 2) The optimal management of Deferrable (or controllable) demand, given the inter-temporal constraints they face, to be coupled with RES. This will extend the concept of controllable loads to include thermal storage, and in particular, the use of ice batteries to replace standard forms of air-conditioning (AC). The analysis is done by simulation in Matpower ([1]) for a Multi-period, stochastic, security constrained AC optimal power flow. This is a continuation of work in stochastic AC-OPF modeling ([2]). A set of constraints reflecting specific ramping costs for all generation is included. The expected amount of Load Not Served (LNS) is also endogenously solved. Wind is modeled as the RES, with a characterization similar to historical data from New York and New England. The network model is a reduction of the Northeastern Power Coordinating Council (NPCC, [3]), modified to focus on New York and New England. Since the adoption of renewables leads to higher cost of capacity for conventional generation, new investments need to be made to be able to manage the load in more economical ways. A load-following ramping reserve product is proposed as an example of a mechanism for participants to signal their technical characteristics and constraints. Investments in storage and controllable load management can also improve the system efficiency. Our results illustrate the importance of market designs that provide participants with the correct economic incentives and signaling mechanisms.

Dynamic optimization for the management of stochastic generation and storage

AbstractWith high penetrations of variable generation from wind turbines in remote locations, transmission capacity may be inadequate to transfer this relatively inexpensive source of generation to demand centers. The major reason is that transmission corridors into load centers are often congested when the system load is high, and additional wind generation is effectively shut out. In contrast, when the system load is low and the wind is blowing, wind generation may be able to meet most of the load throughout the network subject to the specific limitations of the network’s topology. This paper compares the system costs of two very different ways of reducing congestion on the network to increase the annual amount of potential wind capacity dispatched. The first way uses the standard supply side solution of upgrading transmission capacity on the network. The second way uses a demand-side approach in which deferrable demand shifts the system load from on-peak periods to off-peak periods. In addition, the de...

Multi-step forecasting of wave power using a nonlinear recurrent neural network

The objective of this paper is to demonstrate 1) how adding storage capacity to a network can mitigate the variability of wind generation and increase the system benefits, and 2) how the stochastic characteristics of the wind generation affect the system benefits of storage capacity. Two types of storage are considered. One represents utility-scale storage that is collocated at the wind sites, and the other represents an identical amount of deferrable demand located at load centers. The simulation is based on a multi-period, stochastic, Security Constrained Optimal Power Flow (SCOPF) and a reduction of the NPCC network. The results demonstrate that storage capacity can dispatch more wind, mitigate the ramping costs associated with wind variability, and reduce the amount of reserve capacity needed. Deferrable demand can further enhance the system operation, by flattening the typical daily pattern of load, reducing the peak system load and reducing the amount of installed capacity needed on the supply side.

Barriers to Increasing the Role of Demand Resources in Electricity Markets

In order to increase the amounts of renewable energy accommodated in the system, new tools that take into account the horizon of the decision taken are necessary. Feature like the availability of new information can be included in a dynamic optimization framework and therefore help mitigate congestion in the system and have positive effects on distribution systems. This study proposes a new algorithm and shows some preliminary results for the use of Energy Storage Systems (ESS) interacting with stochastic sources of generation. The initial motivation came from the study of the adoption of renewables for electricity, and how to better harness the power of sources that are inherently oscillatory in power output. The benefits of ESS in a dynamic optimization go beyond the amount of renewable energy actually dispatched in the system. The current debate and probable adoption of electrified transportation will most likely increase the pressure on local distribution systems. However, the availability of distributed energy will also increase, in the form of energy storage, once the interface between the grid and the power sources in the vehicles is developed in a mass scale.