Ensuring a consistent and regular availability of food is crucial for food security. Food markets, supplied through both domestic production and international trade, are governed by several risks ...emerging from unpredictable supply chain disruptions, volatility of commodity prices, along with other unforeseen circumstances such as natural disasters. To mitigate the challenges threatening the stability of food systems, decision-making within the food sector should be enhanced and robust to accommodate any changes that might cause food shortages. Dynamic models, that can predict the behavior of food systems in order to avoid potential future knock-on effects and deficits, are incumbent to ensure the sustainable performance of food systems. This study proposes a dynamic decision-making scheme that simulates strategies of the perishable food market under different circumstances. An agent-based model (ABM) is developed and implemented using python MESA library for a case study in Qatar, illustrating the potential performance of tomato under three different scenarios to be considered, namely: (a) baseline scenario - aiming to reflect current production and market conditions; (b) water resource efficiency scenario - basing decisions on crop water requirement (CWR) depending on weather conditions; and (c) economic risk scenario - applying the concept of forward contracts to hedge against future uncertainties in crop prices. The findings of this study demonstrate that under the baseline conditions, a tomato crop can be supplied through a combination of domestic production and imports depending on the available inventories and prices imposed by exporters. The results obtained for the CWR scenario suggest the need for total reliance on imports in order to meet domestic demand, as there is potentially high-water loss, which amounts to an average of 4.9 Billion m3 per year, if tomato is grown locally. In contrast, the results from the forward contract scenario recommend a 57% dependency on local production in order to mitigate the effects of volatility in global food prices, which contributes to a 63% reduction in environmental emissions. Findings of this research provide insight into the factors that influence strategic decision making by the food sector to enhance its economic and environmental performances under diverse circumstances.
•A dynamic decision-making framework to ensure consistent availability of food is developed.•An agent-based simulated is used to advise the strategic planning of tomato crops supply in Qatar.•Three scenarios are investigated to demonstrate the impact of crop water requirement and forward contracts on strategies of the food sector.•A yearly average of 4.9 Bm3 is globally saved when the water requirement is considered in the decision-making.•A reduction of 63% in environmental emissions is recorded while adopting forward contracts.
•Proposing equilibrium models for the joint forward contracts and electricity market.•Proposing equilibrium model for day-ahead market considering agreed forward contracts.•Modeling the mutual ...interactions between electricity market and forward contracts.•Proposing equilibrium models for uniform and pay-as-bid pricing methods in day-ahead market.•Updating the available proposed ‘concern scenario’ risk management method.
Utilization of renewable energy resources, especially wind power, for producing electric energy is growing fast in the world. Besides the environmental advantages, the variability, unpredictability, and uncontrollability of the wind turbines’ output power face the market players with different financial risks. Producers and consumers prefer to have a stable income in the power system and try to avoid the uncertainties and fluctuations in their profits. In this situation, forward contracts are used as efficient tools for helping the market players to hedge themselves against these risks. Since market players participate in both forward and day-ahead markets, their actions in each market affect the other market. So, day-ahead and forward markets affect each other. In this paper, the behavior of market players in the forward and day-ahead electricity markets in the presence of large-scale wind farms are studied. To this end, first, the contracting period is modeled considering different outcomes for the delivery period and then, the delivery period is modeled considering the contracting period outcomes. Equilibrium models are presented for each model. Both uniform and pay-as-bid pricing models for the day-ahead market are considered in the modeling procedure. A recently introduced risk management method called concern scenarios is upgraded and applied to model the risk management preferences of market players. Simulation results are presented, analyzed, and compared for models by applying them to a test system case study.
We propose a novel semi-parametric structural model to estimate the electricity forward curves based on elementary forward prices. The proposed model (i) explores the non-arbitrage relations between ...contracts with overlapping delivery periods, (ii) considers a parametric structure for price seasonality and exogenous variables, and (iii) uses non-parametric techniques to extract the remaining inter-temporal and cross-maturity information from data. Thus, our model allows users to estimate and complete the historical prices of any swap contract. We address the multi-objective estimation problem by hierarchical optimization. First, arbitrage levels are minimized. Then, the parametric part of the model is estimated. Finally, smoothness in the maturity and trading date dimensions are jointly considered in the estimation of the non-parametric part of the model. Based on a controlled study with real data from the Nordic power market, we show that our model outperforms benchmarks in terms of estimation error for missing data. We also isolate the effect of accounting for overlaps and smoothing in the trading dates dimension. Results show that these two key features of our model are crucial for improving the model accuracy. Finally, we apply our method to estimate the Brazilian forward curve and reconstruct the historical data.
This paper proposes a decision-making framework, based on stochastic programming, for a retailer: 1) to determine the sale price of electricity to the customers based on time-of-use (TOU) rates, and ...2) to manage a portfolio of different contracts in order to procure its demand and to hedge against risks, within a medium-term period. Supply sources include the pool, self-production facilities and several instruments such as forward contracts, call options, and interruptible contracts. The objective is to maximize the profit and simultaneously to minimize the risks in terms of a multi-period risk measure. Moreover, the risks are measured using conditional value at risk (CVaR) methodology. The reaction of the customers to the retailers' selling prices as well as the competition between the retailers is modeled through a market share function. The problem is formulated as a mixed-integer stochastic programming. It is solved by a decomposition technique, and the decomposed parts are solved by a branch-and-bound algorithm.
New grid management schemes have created exciting opportunities for end customers to maximize their utility by becoming active participants. In particular, Transactive Energy Systems (TES) allow ...customers to cooperate and negotiate in energy markets, increasing social welfare. These interactions also reduce demand-side uncertainties and simplify grid balancing at different levels. In TES, it is beneficial to employ forward contracts because they establish conditions for future energy supply, allowing grid maintainers to plan a cost-effective operation. Thus, end customers interact in local retail markets in advance to agree on service conditions that fulfill their needs. This paper presents a comprehensive analysis of the risks involved in those forward contracts with the aim of providing valuable information to participants. The TES environment modifies the typical risks of electricity contracts due to the information exchange in the negotiation and execution stages. Indeed, reliable data and realistic forecasting assumptions become a primary concern for each participant since they constitute the main threat of contract defaulting. Risk management strategies are presented in bow-tie and Ishikawa diagrams to elicit the decisions for market participants. Case study results demonstrate that forecasting errors impact the conditional value at risk of the contracts, in proportion to the demand uncertainty.
Time-varying electricity rates enable demand-side potentials, which provide an opportunity for distribution companies (DisCos) to hedge against the financial risk imposed by volatile spot market ...prices and uncertain customers' load. In particular, time-varying rates can be effective alternatives for at least a portion of costly forward contracts. This paper establishes a stochastic framework to determine optimal forward market purchases under time-varying rates. Various electricity rating strategies with different time intervals covering flat, time-of-use, and real-time pricing schemes are considered. The objective of the framework is to maximize DisCo's expected profit while the exposure risk is restricted to a predetermined level. The risk is modeled using the conditional value at risk approach. The elastic behavior of demand is taken into account via the price elasticity matrix model. The proposed framework is formulated as a mixed-integer linear programming problem which can be easily solved through commercially available solvers. The effectiveness of the developed methodology is examined through comprehensive case studies based on real data from Finland. A detailed comparison on the scheduling of forward contracts under different rating strategies is also provided.
A challenge in setting regulated rates for default retail electricity products is the presence of both price and quantity uncertainty faced by the default retail provider. To address this challenge, ...regulators have been increasingly employing competition via full-load (load-following) auctions to value the costs associated with this uncertainty. In a full-load auction, firms bid to supply a fixed percentage of the regulated utility’s hourly demand at a fixed price. In this paper, we develop a model of break-even pricing of electricity forward products. We use this model to evaluate the performance of full-load auctions in Alberta, where the largest regulated retail provider adopted such auctions in December 2018. We find that the winning full-load bids exceed break-even levels, but that the difference falls over time. This reduction coincides with an increase in the number of bidders active in the full-load auctions. Our paper highlights the importance of sufficient participation for the success of full-load auctions and the potential role for competitive markets in determining the value of risk faced by regulated retail providers.
•Regulated default products can serve a prominent role in markets with retail competition.•Alberta developed a full-load auction to determine the default product’s energy price.•We assess the performance of the default product’s full-load procurement auction.•We find evidence that the full-load price exceeded break-even levels.•The full-load price decreased towards its break-even level as the number of participating bidders increased.
Wind generation must trade in forward electricity markets based on imperfect forecasts of its output and real-time prices. When the real-time price differs for generators that are short and long, the ...optimal forward strategy must be based on the opportunity costs of charges and payments in real-time rather than a central estimate of wind output. We present analytical results for wind's optimal forward strategy. In the risk-neutral case, the optimal strategy is determined by the distribution of real-time available wind capacity, and the expected real-time prices conditioned on the forward price and wind out-turn; our approach is simpler and more computationally efficient than formulations requiring specification of full joint distributions or a large set of scenarios. Informative closed-form examples are derived for particular specifications of the wind-price dependence structure. In the usual case of uncertain forward prices, the optimal bidding strategy generally consists of a bid curve for wind power, rather than a fixed quantity bid. A discussion of the risk-averse problem is also provided. An analytical result is available for aversion to production volume risk; however, we doubt whether wind owners should be risk-averse with respect to the income from a single settlement period, given the large number of such periods in a year.
Conventional computing resource trading over mobile networks generally faces many challenges, e.g., excessive decision-making latency, undesired trading failures, and underutilization of dynamic ...resources, owing to the constraint of wireless networks. To improve resource utilization rate under dynamic network conditions, this paper introduces a novel computing resource provisioning mechanism empowered by overbooking, that allows the amount of booked resources to exceed the resource supply. Cloud-aided mobile edge networks are considered for the proposed framework, where an edge server can purchase more resources from a cloud server to offer computing services to multiple end-users with computation-intensive tasks. Specifically, the proposed mechanism relies on designing pre-signed forward trading contracts among edge and end-users, as well as between edge and cloud in advance to future practical trading; while encouraging an appropriate overbooking rate to improve resource utilization, via analyzing historical statistics associated with uncertainties such as dynamic resource supply/demand, and varying channel qualities. The contract design is formulated as a multi-objective optimization problem that aims to maximize the expected utilities of end-users, edge, and cloud, via evaluating potential risks; for which a two-phase multilateral negotiation scheme is proposed that facilitates the bargaining procedure among the three parties, to reach the final trading consensus (namely, contract terms). Experimental results demonstrate that the proposed mechanism achieves mutually beneficial utilities of three parties, while outperforming baseline methods on significant indicators such as task completion, trading failure, time efficiency, resource usage, etc., from various analytical angles.
•Proposing an equilibrium model for joint forward contracts and day-ahead markets.•Proposing a method for modeling the negotiations between producers and consumers.•Considering the strategic behavior ...of consumers in forward contract negotiations.•Considering the mutual impacts of forward contracts and day-ahead markets.•Proposing a risk management method based on the different concerns of market players.
Forward contracts are one of the prevalent and useful tools for managing the risks associated with the volatility of the electricity market prices. Forward contracts and day-ahead electricity market are executed simultaneously, and hence, they affect each other. This paper proposes a comprehensive supply function equilibrium model to consider the mutual interactions between forward contracts and the associated day-ahead electricity market in a power system. Negotiation between each producer and consumer in forward market is taken into account in the model. In order to consider the risk management behaviors of all market players in the model, a new risk management method is presented. The proposed risk management method takes into account the concerns of market players about the future prices of day-ahead market over the delivery period. The model proposed in this paper is applied to a test system with forward and day-ahead markets. The results are compared with the case that there is no forward contract in the power system. Impacts of growing the concerns of producers and consumers about the future, impacts of increasing demand uncertainty, impacts of improving bargaining power of consumers in contracting period and impact of contracting obligations for producers on the simulation results are discussed. The proposed risk management method is compared with CVaR method and its efficiency is evaluated. Finally, applicability of the proposed model to real size power systems is examined.
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