On the Economic Value and Price-Responsiveness of Ramp-Constrained Storage

The primary concerns of this paper are twofold: to understand the economic value of storage in the presence of ramp constraints and exogenous electricity prices, and to understand the implications of the associated optimal storage management policy on qualitative and quantitative characteristics of storage response to real-time prices. We present an analytic characterization of the optimal policy, along with the associated finite-horizon time-averaged value of storage. We also derive an analytical upperbound on the infinite-horizon time-averaged value of storage. This bound is valid for any achievable realization of prices when the support of the distribution is fixed, and highlights the dependence of the value of storage on ramp constraints and storage capacity. While the value of storage is a non-decreasing function of price volatility, due to the finite ramp rate, the value of storage saturates quickly as the capacity increases, regardless of volatility. To study the implications of the optimal policy, we first present computational experiments that suggest that optimal utilization of storage can, in expectation, induce a considerable amount of price elasticity near the average price, but little or no elasticity far from it. We then present a computational framework for understanding the behavior of storage as a function of price and the amount of stored energy, and for characterization of the buy/sell phase transition region in the price-state plane. Finally, we study the impact of market-based operation of storage on the required reserves, and show that the reserves may need to be expanded to accommodate market-based storage

Distributed Stochastic Market Clearing with High-Penetration Wind Power

Integrating renewable energy into the modern power grid requires risk-cognizant dispatch of resources to account for the stochastic availability of renewables. Toward this goal, day-ahead stochastic market clearing with high-penetration wind energy is pursued in this paper based on the DC optimal power flow (OPF). The objective is to minimize the social cost which consists of conventional generation costs, end-user disutility, as well as a risk measure of the system re-dispatching cost. Capitalizing on the conditional value-at-risk (CVaR), the novel model is able to mitigate the potentially high risk of the recourse actions to compensate wind forecast errors. The resulting convex optimization task is tackled via a distribution-free sample average based approximation to bypass the prohibitively complex high-dimensional integration. Furthermore, to cope with possibly large-scale dispatchable loads, a fast distributed solver is developed with guaranteed convergence using the alternating direction method of multipliers (ADMM). Numerical results tested on a modified benchmark system are reported to corroborate the merits of the novel framework and proposed approaches.Comment: To appear in IEEE Transactions on Power Systems; 12 pages and 9 figure

Robust Optimal Power Flow with Wind Integration Using Conditional Value-at-Risk

Integrating renewable energy into the power grid requires intelligent risk-aware dispatch accounting for the stochastic availability of renewables. Toward achieving this goal, a robust DC optimal flow problem is developed in the present paper for power systems with a high penetration of wind energy. The optimal dispatch is obtained as the solution to a convex program with a suitable regularizer, which is able to mitigate the potentially high risk of inadequate wind power. The regularizer is constructed based on the energy transaction cost using conditional value-at-risk (CVaR). Bypassing the prohibitive high-dimensional integral, the distribution-free sample average approximation method is efficiently utilized for solving the resulting optimization problem. Case studies are reported to corroborate the efficacy of the novel model and approach tested on the IEEE 30-bus benchmark system with real operation data from seven wind farms.Comment: To Appear in Proc. of the 4th Intl. Conf. on Smart Grid Communication

Experience of Policy Instruments used to promote renewable energy - Case study of Maharashtra, India

Policy instruments are used to support the introduction and diffusion of renewable energy technologies as the cost of renewable energy is generally higher than fossil-based energy. The commonly used policy instruments for supporting renewable electricity are quota-based system and the price based feed-in system. While quota based systems specify minimum targets for renewable electricity procurement by electricity suppliers, price based systems provide fixed selling price for the entire renewable electricity generation over a long time frame. This research attempts to study the influence of policy instruments on the renewable sector in Maharashtra, an Indian state. In Maharashtra, Renewable Purchase Obligation (RPO), a policy instrument similar to feed-in system was operational for two years, from 2004 to 2006. Thereafter, RPO was replaced by a new instrument called Renewable Purchase Specification (RPS) in year 2006, which was similar to quota based system. The renewable sector experienced two different development patterns during the regime of the two policy instruments. While capacity growth rate increased rapidly under RPO regime, the same declined sharply under RPS regime. This study looks into the various issues that influenced the developments in renewable sector during the regime of these policy instruments. The results of the study show that the provision of penalty under the RPS for nonachievement of targets was one of the most significant issues that affected the renewable sector. While the purpose of penalty was to support renewable growth by ensuring compliance among the electricity consumers for meeting targets, it instead created barriers to capacity growth. As the supply of renewable electricity was much lower than what was required to meet the targets specified under RPS, the price of renewable electricity registered a sharp increase and the market started favoring the generators. The substantial gap between demand and supply of renewable electricity indicates that the market was not mature enough to support competition based RPS system. Based on the findings, it is felt that price based system would be better than quota based system in such markets which are yet to mature

Acceleration of the Transition to a Sustainable and Renewable Energy Future in Mexico through Clean Energy Certificates

Currently, there is a constant commitment of governments around the world for reducing the emissions of pollutants and mitigate the effects of the climate change through the deployment of renewable energy for electricity generation. Governments have adopted policies and targets for fostering the use of clean technologies in order to be cost-competitive with fossil fuels technologies. The clean energy certificate markets have been created by the governments as an incentive for integrating the participation of renewable energies into their energy portfolios. In 2013, Mexico enacted an Energy Reform with the purpose to oversight a gradual participation of renewable energies in the electricity industry with a renewable target of 35% as a minimum in electricity generation from clean energy sources by 2024. In 2018, a clean energy certificate market will be launched by the Mexican government in order to accelerate the pace to reach the renewable energy target. This research project outlined the need for identifying best global practices in the design features of clean energy certificate markets through the analytical method of the socio-technical system approach for the Mexican clean energy certificate market to accelerate the transition to a sustainable energy in Mexico. The aim of this research project is to evaluate the countries with high penetration of renewable energies through the implementation of a clean energy certificate market. It is worth noting that the evaluations of the countries are presented as follows: Sweden and Norway, United Kingdom, Australia, India and the state of California in the United States. The research project highlights the findings of the best international practices and failures as result of the evaluations made with the socio-technical system approach and the recommendations for the Mexican clean energy certificate market

Efficient Decentralized Economic Dispatch for Microgrids with Wind Power Integration

Decentralized energy management is of paramount importance in smart microgrids with renewables for various reasons including environmental friendliness, reduced communication overhead, and resilience to failures. In this context, the present work deals with distributed economic dispatch and demand response initiatives for grid-connected microgrids with high-penetration of wind power. To cope with the challenge of the wind's intrinsically stochastic availability, a novel energy planning approach involving the actual wind energy as well as the energy traded with the main grid, is introduced. A stochastic optimization problem is formulated to minimize the microgrid net cost, which includes conventional generation cost as well as the expected transaction cost incurred by wind uncertainty. To bypass the prohibitively high-dimensional integration involved, an efficient sample average approximation method is utilized to obtain a solver with guaranteed convergence. Leveraging the special infrastructure of the microgrid, a decentralized algorithm is further developed via the alternating direction method of multipliers. Case studies are tested to corroborate the merits of the novel approaches.Comment: To appear in IEEE GreenTech 2014. Submitted Sept. 2013; accepted Dec. 201