Adaptive Robust Optimization with Dynamic Uncertainty Sets for Multi-Period Economic Dispatch under Significant Wind

The exceptional benefits of wind power as an environmentally responsible renewable energy resource have led to an increasing penetration of wind energy in today's power systems. This trend has started to reshape the paradigms of power system operations, as dealing with uncertainty caused by the highly intermittent and uncertain wind power becomes a significant issue. Motivated by this, we present a new framework using adaptive robust optimization for the economic dispatch of power systems with high level of wind penetration. In particular, we propose an adaptive robust optimization model for multi-period economic dispatch, and introduce the concept of dynamic uncertainty sets and methods to construct such sets to model temporal and spatial correlations of uncertainty. We also develop a simulation platform which combines the proposed robust economic dispatch model with statistical prediction tools in a rolling horizon framework. We have conducted extensive computational experiments on this platform using real wind data. The results are promising and demonstrate the benefits of our approach in terms of cost and reliability over existing robust optimization models as well as recent look-ahead dispatch models.Comment: Accepted for publication at IEEE Transactions on Power System

Economic Evaluation of Biotechnological Progress: The effect of changing management behavior

The paper assesses the welfare effects of biotechnological progress, as exemplified by tree improvements, using a partial equilibrium model. Timber demand is assumed to be stochastic and the distributions of the coefficients of the demand function are known. Assuming that timber supply is a log-linear function of timber price and forest inventory, we determine the coefficients of the supply function by maximizing the expected present value of the total surplus of timber production, both in the presence and in the absence of genetically improved regeneration materials. The supply functions are then used to estimate the expected present values of the total surplus in different cases through simulation. These estimates enable us to assess the direct effect and the total effect of the genetically improved regeneration materials on the expected present value of the total surplus. By taking the difference between these two effects, we obtain an estimate of the effect of changing harvest behavior induced by the use of genetically improved regeneration materials in forestry. The main results of the study are (1) the presence of genetically improved regeneration materials has significant impacts on the aggregate timber supply function; (2) application of genetically improved regeneration materials leads to a significant increase in the expected present value of the total surplus; (3) a considerable proportion of the welfare gain results from the change in timber harvest behavior; and (4) the use of genetically improved regeneration materials reduces the profits of timber production.timber market model; tree improvement; optimal harvesting decision; timber supply

Consensus-based approach to peer-to-peer electricity markets with product differentiation

With the sustained deployment of distributed generation capacities and the more proactive role of consumers, power systems and their operation are drifting away from a conventional top-down hierarchical structure. Electricity market structures, however, have not yet embraced that evolution. Respecting the high-dimensional, distributed and dynamic nature of modern power systems would translate to designing peer-to-peer markets or, at least, to using such an underlying decentralized structure to enable a bottom-up approach to future electricity markets. A peer-to-peer market structure based on a Multi-Bilateral Economic Dispatch (MBED) formulation is introduced, allowing for multi-bilateral trading with product differentiation, for instance based on consumer preferences. A Relaxed Consensus+Innovation (RCI) approach is described to solve the MBED in fully decentralized manner. A set of realistic case studies and their analysis allow us showing that such peer-to-peer market structures can effectively yield market outcomes that are different from centralized market structures and optimal in terms of respecting consumers preferences while maximizing social welfare. Additionally, the RCI solving approach allows for a fully decentralized market clearing which converges with a negligible optimality gap, with a limited amount of information being shared.Comment: Accepted for publication in IEEE Transactions on Power System

Multi objective optimization in charge management of micro grid based multistory carpark

Distributed power supply with the use of renewable energy sources and intelligent energy flow management has undoubtedly become one of the pressing trends in modern power engineering, which also inspired researchers from other fields to contribute to the topic. There are several kinds of micro grid platforms, each facing its own challenges and thus making the problem purely multi objective. In this paper, an evolutionary driven algorithm is applied and evaluated on a real platform represented by a private multistory carpark equipped with photovoltaic solar panels and several battery packs. The algorithm works as a core of an adaptive charge management system based on predicted conditions represented by estimated electric load and production in the future hours. The outcome of the paper is a comparison of the optimized and unoptimized charge management on three different battery setups proving that optimization may often outperform a battery setup with larger capacity in several criteria.Web of Science117art. no. 179

Water allocation policies for the Dong Nai River Basin in Vietnam: an integrated perspective

Recent water sector reforms, increased scarcity and vulnerability of existing water resources, combined with declining public funding available for large-scale infrastructure investment in the sector have led to an increased awareness by the Government of Vietnam for the need to analyze water resource allocation and use in an integrated fashion, at the basin scale, and from an economic efficiency perspective. This paper presents the development, application, and results from an integrated economic-hydrologic river basin model for the Dong Nai River Basin in southern Vietnam that attempts to address these issues. The model framework takes into account the sectoral structure of water users (agriculture, industry, hydropower, households, and the environment), the location of water-using regions, and the institutions for water allocation in the basin. Water benefit functions are developed for the major water uses subject to physical, system control, and policy constraints. Based on this modeling framework, policies that can affect water allocation and use at the basin level, including both basin-specific and general macroeconomic policies, are analyzed.River basin model, water allocation policy, integrated assessment, Vietnam, Dong Nai basin, Water resources Economic aspects,

Factor demand modelling: the theory and the practice

Since the work of Cobb and Douglas [18], two main innovations have been introduced in applied factor demand analysis, i.e. the use of flexible functional forms and the modelling of dynamics, expectations, and the interrelatedness of the adjustment process. Recently, cointegration theory has provided an additional important contribution, yielding empirical content to the notion of equilibrium employed in economic analysis, encompassing both the idea of centre of gravity relationship, suggested byClassical economists, and the notion of market-clearing position, employed by Neoclassical economist. Also in the light of the most recent generalizations of the concept of cointegration, allowing for economic attractors changing over time, as the evolution of the structural features of the economy proceeds, this paper critically assess the key theoretical and empirical issues in factor demand analysis.factor demand, flexible functional forms, error correction model, cointegration.

Optimal Participation of Power Generating Companies in a Deregulated Electricity Market

The function of an electric utility is to make stable electric power available to consumers in an efficient manner. This would include power generation, transmission, distribution and retail sales. Since the early nineties however, many utilities have had to change from the vertically integrated structure to a deregulated system where the services were unbundled due to a rapid demand growth and need for better economic benefits. With the unbundling of services came competition which pushed innovation and led to the improvement of efficiency. In a deregulated power system, power generators submit offers to sell energy and operating reserve in the electricity market. The market can be described more as oligopolistic with a System Operator in-charge of the power grid, matching the offers to supply with the bid in demands to determine the market clearing price for each interval. This price is what is paid to all generators. Energy is sold in the day-ahead market where offers are submitted hours prior to when it is needed. The spot energy market caters to unforeseen rise in load demand and thus commands a higher price for electrical energy than the day-ahead market. A generating company can improve its profit by using an appropriate bidding strategy. This improvement is affected by the nature of bids from competitors and uncertainty in demand. In a sealed bid auction, bids are submitted simultaneously within a timeframe and are confidential, thus a generator has no information on rivals’ bids. There have been studies on methods used by generators to build optimal offers considering competition. However, many of these studies base estimations of rivals’ behaviour on analysis with sufficient bidding history data from the market. Historical data on bidding behaviour may not be readily available in practical systems. The work reported in this thesis explores ways a generator can make security-constrained offers in different markets considering incomplete market information. It also incorporates possible uncertainty in load forecasts. The research methodology used in this thesis is based on forecasting and optimization. Forecasts of market clearing price for each market interval are calculated and used in the objective function of profit maximization to get maximum benefit at the interval. Making these forecasts includes competition into the bid process. Results show that with information on historical data available, a generator can make adequate short-term analysis on market behaviour and thus optimize its benefits for the period. This thesis provides new insights into power generators’ approach in making optimal bids to maximize market benefits