A looming revolution: Implications of self-generation for the risk exposure of retailers. ESRI WP597, September 2018

Managing the risk associated with uncertain load has always been a challenge for retailers in electricity markets. Yet the load variability has been largely predictable in the past, especially when aggregating a large number of consumers. In contrast, the increasing penetration of unpredictable, small-scale electricity generation by consumers, i.e. self-generation, constitutes a new and yet greater volume risk. Using value-at-risk metrics and Monte Carlo simulations based on German historical loads and prices, the contribution of decentralized solar PV self-generation to retailers’ load and revenue risks is assessed. This analysis has implications for the consumers’ welfare and the overall efficiency of electricity markets

Determinants of power spreads in electricity futures markets: A multinational analysis. ESRI WP580, December 2017

The growth in variable renewable energy (vRES) and the need for flexibility in power systems go hand in hand. We study how vRES and other factors, namely the price of substitute fuels, power price volatility, structural breaks, and seasonality impact the hedgeable power spreads (profit margins) of the main dispatchable flexibility providers in the current power systems - gas and coal power plants. We particularly focus on power spreads that are hedgeable in futures markets in three European electricity markets (Germany, UK, Nordic) over the time period 2009-2016. We find that market participants who use power spreads need to pay attention to the fundamental supply and demand changes in the underlying markets (electricity, CO2, and coal/gas). Specifically, we show that the total vRES capacity installed during 2009-2016 is associated with a drop of 3-22% in hedgeable profit margins of coal and especially gas power generators. While this shows that the expansion of vRES has a significant negative effect on the hedgeable profitability of dispatchable, flexible power generators, it also suggests that the overall decline in power spreads is further driven by the price dynamics in the CO2 and fuel markets during the sample period. We also find significant persistence (and asymmetric effects) in the power spreads volatility using a univariate TGARCH model

Multifractal analysis of Power Markets. Some empirical evidence

This work is intended to offer a comparative analysis of the statistical properties of hourly prices in the day–ahead electricity markets of several countries. Starting from the intermittent nature of typical price fluctuations in many power markets, we will provide evidence that working into a stochastic multifractal analysis framework can be of help to asses typical features of day–ahead market prices.Multifractals, Hurst Coefficient, Power Markets

Spot price modeling and the valuation of electricity forward contracts : the role of demand and capacity.

We propose a model where wholesale electricity prices are explained by two state variables: demand and capacity. We derive analytical expressions to price forward contracts and to calculate the forward premium. We apply our model to the PJM, England and Wales, and Nord Pool markets. Our empirical findings indicate that volatility of demand is seasonal and that the market price of demand risk is also seasonal and positive, both of which exert an upward (seasonal) pressure on the price of forward contracts. We assume that both volatility of capacity and the market price of capacity risk are constant and find that, depending on the market and period under study, it could either exert an upward or downward pressure on forward prices. In all markets we find that the forward premium exhibits a seasonal pattern. During the months of high volatility of demand, forward contracts trade at a premium. During months of low volatility of demand, forwards can either trade at a relatively small premium or, even in some cases, at a discount, i.e. they exhibit a negative forward premiumPower prices; Demand; Capacity; Forward premium; Forward bias; Market price of capacity risk; Market price of demand risk; PJM; England and Wales; Nord Pool;

Buyback and return policies for a book publishing firm = Egy könyvkiadó vállalat visszavásárlási stratégiája

A dolgozat célja egy vállalati gyakorlatból származó eset elemzése. Egy könyvkiadót tekintünk. A kiadó kapcsolatban van kis- és nagykereskedőkkel, valamint a fogyasztók egy csoportjával is vannak kapcsolatai. A könyvkiadók projekt rendszerben működnek. A kiadó azzal a problémával szembesül, hogy hogyan ossza el egy frissen kiadott és nyomtatott könyv példányszámait a kis- és nagykereskedők között, valamint mekkora példányszámot tároljon maga a fogyasztók közvetlen kielégítésére. A kiadóról feltételezzük, hogy visszavásárlási szerződése van a kereskedőkkel. A könyv iránti kereslet nem ismert, de becsülhető. A kis- és nagykereskedők maximalizálják a nyereségüket. = The aim of the paper is to analyze a practical real world problem. A publishing house is given. The publishing firm has contacts to a number of wholesaler / retailer enterprises and direct contact to customers to satisfy the market demand. The book publishers work in a project industry. The publisher faces with the problem how to allocate the stocks of a given, newly published book to the wholesaler and retailer, and to hold some copies to satisfy the customers direct from the publisher. The publisher has a buyback option. The distribution of the demand is unknown, but it can be estimated. The wholesaler / retailer maximize the profits. The problem can be modeled as a one-warehouse and N-retailer supply chain with not identical demand distribution. The model can be transformed in a game theory problem. It is assumed that the demand distribution follows a Poisson distribution

Spot price modeling and the valuation of electricity forward contracts : the role of demand and capacity.

We propose a model where wholesale electricity prices are explained by two state variables: demand and capacity. We derive analytical expressions to price forward contracts and to calculate the forward premium. We apply our model to the PJM, England and Wales, and Nord Pool markets. Our empirical findings indicate that volatility of demand is seasonal and that the market price of demand risk is also seasonal and positive, both of which exert an upward (seasonal) pressure on the price of forward contracts. We assume that both volatility of capacity and the market price of capacity risk are constant and find that, depending on the market and period under study, it could either exert an upward or downward pressure on forward prices. In all markets we find that the forward premium exhibits a seasonal pattern. During the months of high volatility of demand, forward contracts trade at a premium. During months of low volatility of demand, forwards can either trade at a relatively small premium or, even in some cases, at a discount, i.e. they exhibit a negative forward premiumPower prices; Demand; Capacity; Forward premium; Forward bias; Market price of capacity risk; Market price of demand risk; PJM; England and Wales; Nord pool;

Quantitative analysis of multi-periodic supply chain contracts with options via stochastic programming

We propose a stochastic programming approach for quantitative analysis of supply contracts, involving flexibility, between a buyer and a supplier, in a supply chain framework. Specifically, we consider the case of multi-periodic contracts in the face of correlated demands. To design such contracts, one has to estimate the savings or costs induced for both parties, as well as the optimal orders and commitments. We show how to model the stochastic process of the demand and the decision problem for both parties using the algebraic modeling language AMPL. The resulting linear programs are solved with a commercial linear programming solver; we compute the economic performance of these contracts, giving evidence that this methodology allows to gain insight into realistic problems.stochastic programming; supply contract; linear programming; modeling software; decision tree

The structure of the optimal combined sourcing policy using capacity reservation and spot market with price uncertainty

This contribution focuses on the cost-effective management of the combined use of two procurement options: the short-term option is given by a spot-market with random price, whereas the long-term alternative is characterized by a multi period capacity reservation contract with fixed purchase price, reservation level and capacity reservation cost. Considering a multiperiod problem with stochastic demand, the structure of the optimal combined purchasing policy is derived using stochastic dynamic programming.Capacity reservation, spot market, purchasing policy, supply contracts, stochastic inventory control