Energy storage models require binary variables to correctly model reserves and to ensure that the storage cannot charge and discharge simultaneously. This paper proposes a tight linear program (LP), i.e., convex hull, for the storage, which guarantees that there is no better LP approximation to its mixed-integer program (MIP) counterpart. Although the resulting LP formulation cannot guarantee that charge and discharge are mutually exclusive at all times, it does not affect the feasibility of providing reserves. By embedding the proposed LP formulation into large optimization problems, it helps to provide solutions equal to or very near to the exact integer feasible behaviour of the storage; and when used in its integer form, it speeds up MIP problems. Furthermore, the tight LP formulation is extended to include storage investment decisions, thus providing a very strong LP relaxation, opposite to the LP relaxation resulting from the big-M constraints commonly used in storage investment models.
The liberalization of the retail market of electricity increased the tariff choice of end-use consumers. Retailers compete in the retail market for customers, obtaining private portfolios of end-use consumers to manage. Retailers buy electricity at wholesale markets to feed their customers’ demands. They can use spot, derivatives, and bilateral markets to acquire the energy they need. The increasing levels of variable renewable energy sources trading at spot markets, increase the price volatility of these markets. To hedge against the volatility of spot prices, retailers may negotiate standard physical or financial bilateral contracts at derivatives markets. Alternatively, they can also negotiate private bilateral contracts. This article addresses the optimization of the retailers purchasing options, to increase their risk-return ratio from electricity markets, and offer more competitive tariffs to consumers. Considering the risk attitude of retailers, they use a multi-step purchasing model composed of a multi-level risk-return optimization and a decision support system. The article presents an agent-based study considering a retailer with a portfolio of 312 real-world consumers. Risk-seeking and risk-neutral retailers obtained a return up to 38%, less than 7% of the optimal return. However, risk-neutral retailers are subject to four times higher risk in their returns than risk-seeking retailers. The results support the conclusion that wholesale markets of electricity are more favourable to risk-seeking retailers, considering their real returns.
Over the last few decades, the electricity sector has experienced several changes, resulting in different electricity markets (EMs) models and paradigms. In particular, liberalization has led to the establishment of a wholesale market for electricity generation and a retail market for electricity retailing. In competitive EMs, customers can do the following: freely choose their electricity suppliers; invest in variable renewable energy such as solar photovoltaic; become prosumers; or form local alliances such as Citizen Energy Communities (CECs). Trading of electricity can be done in spot and derivatives markets, or by bilateral contracts. This article focuses on CECs. Specifically, it presents how agent-based local consumers can form alliances as CECs, manage their resources, and trade on EMs. It also presents a review of how agent-based systems can model and support the formation and interaction of alliances in the electricity sector. The CEC can trade electricity directly with sellers through private bilateral agreements. During the negotiation of private bilateral contracts, the CEC receives the prices and volumes of their members and according to its negotiation strategy, tries to satisfy the electricity demands of all members and reduce their costs for electricity.
The liberalization of energy markets brought full competition to the electric power industry. In the wholesale sector, producers and retailers submit bids to day-ahead markets, where prices are uncertain, or alternatively, they sign bilateral contracts to hedge against pool price volatility. In the retail sector, retailers compete to sign bilateral contracts with end-use customers. Typically, such contracts are subject to a high-risk premium—that is, retailers request a high premium to consumers to cover their potential risk of trading energy in wholesale markets. Accordingly, consumers pay a price for energy typically higher than the wholesale market price. This article addresses the optimization of the portfolios of retailers, which are composed of end-use customers. To this end, it makes use of a risk-return optimization model based on the Markowitz theory. The article presents a simulation-based study conducted with the help of the MATREM system, involving 6 retailer agents, with different risk preferences, and 312 real-world consumers. The retailers select a pricing strategy and compute a tariff to offer to target consumers, optimize their portfolio of consumers using data from the Iberian market, sign bilateral contracts with consumers, and compute their target return during contract duration. The results support the conclusion that retail markets are more favourable to risk-seeking retailers, since substantial variations in return lead to small variations in risk. However, for a given target return, risk-averse retailers consider lower risk portfolios, meaning that they may obtain higher returns in both favourable and unfavourable situations.
The development and large-scale dissemination of the new and variable renewable technologies took place from 1990 onwards in most developed countries, in a process led by Europe. To promote the renewable sector development financial incentives, both for investment and for the payment of renewable energy, were always present. These incentives usually consisted of guaranteed feed-in tariffs that ensured a return of the investments made in this new business—thus minimizing the financial risks and building a more attractive business for private companies in the renewables sector. That approach was the main basis that essentially supported the remarkable growth of the renewable sector in Europe in the past 30 years. Nowadays, the renewable energy sector is already mature in most aspects. The cost of generating electricity from wind or solar (photovoltaic) resources is competitive with conventional gas or coal-based technologies. However, some challenges still exist in the transition of the electrical power sector to a desirable carbon-free, near 100% renewable-based sector—and one of those main challenges is the negotiation of the electricity generated by these novel technologies, due to the time and spatial variability of the primary resources as well as their poor predictability and dispatchability of the power generated. This chapter addresses those challenges as well as the approaches available to overcome them within competitive electricity markets.
Global warming contributes to the worldwide goal of a sustainable carbon-neutral society. Currently, hydroelectric, wind and solar power plants are the most competitive renewable technologies. They are limited to the primary resource availability, but while hydroelectric power plants (HPPs) can have storage capacity but have several geographical limitations, wind and solar power plants have variable renewable energy (VRE) with stochastic profiles, requiring a substantially higher investment when equipped with battery energy storage systems. One of the most affordable solutions to compensate the stochastic behaviour of VRE is the active participation of consumers with demand response capability. Therefore, the role of citizen energy communities (CECs) can be important towards a carbon-neutral society. This work presents the economic and environmental advantages of CECs, by aggregating consumers, prosumers and VRE at the distribution level, considering microgrid trades, but also establishing bilateral agreements with large-scale VRE and HPPs, and participating in electricity markets. Results from the case-study prove the advantages of CECs and self-consumption. Currently, CECs have potential to be carbon-neutral in relation to electricity consumption and reduce consumers’ costs with its variable term until 77%. In the future, electrification may allow CECs to be fully carbon-neutral, if they increase their flexibility portfolio.
Driven by climate change concerns, Europe has taken significant initiatives toward the decarbonization of its energy system. The European Commission (EC) has set targets for 2030 to achieve at least 40% reduction in greenhouse gas emissions with respect to the 1990 baseline level and cover at least 32% of the total energy consumption in the European Union (EU) through renewable energy sources, predominantly wind and solar generation. However, these technologies are inherently characterized by high variability, limited predictability and controllability, and lack of inertia, significantly increasing the balancing requirements of the system with respect to historical levels. The flexibility burden is currently carried by flexible fossil-fueled conventional generators (mainly gas), which are required to produce significantly less energy (as low operating cost and CO<sub>2</sub>-free renewable and nuclear generation are prioritized in the merit order) and operate part loaded with frequent startup and shut-down cycles, with devastating effects on their cost efficiency.
This article aims to assess and understand the impact of large-scale integration of the solar photovoltaic (PV) technology in the Iberian electricity market. This impact was evaluated using the projections of the Portuguese solar deployment capacity established in the National Energy and Climate Plan (NECP) 2030 and a multi-agent electricity market simulator designated as MATREM (for Multi-Agent Trading in Electricity Market). Comparing with the values obtained for 2016, the results suggest that the installed capacities projected in the PNEC allow to reduce the average price on the day-ahead spot market by 8.10 €/MWh, reaching 45.52 €/MWh. Considering only the period when solar production is expected (i.e., excluding the night hours), the average price obtained for 2030 is 46.76 €/MWh. With the current installations costs values of solar PV and the values obtained in this work, the results suggest that it is reasonable for a solar power producer to select a market-based remuneration. Thus, in addition to the environmental benefits, the large-scale integration of solar PV technology can have a positive socio-economic impact.
The European Union defined ambitious targets for the production of energy from renewable energy sources. Most European markets trade now high levels of variable renewable energy (VRE). Renewable generation increases the variability and uncertainty of the net-load (i.e., demand minus VRE). To a large extent, this variability and uncertainty can be compensated by hydroelectric power plants. Typically, hydro power producers (HPPs) consider the periods of time with low market prices (and normally low demand and/or high VRE production) to pump, and the periods with high market prices (and normally high demand and/or low VRE production) to produce energy. This article presents a model for hydro power plants and a study to analyse the hydro-wind balance in a real-world setting, namely a simplified version of the Portuguese power system, involving a significant penetration of hydro and wind power (more than 50%). The study is conducted with the help of the multi-agent system MATREM. The results confirm (and rebut) the typical behavior of hydroelectric power plants (to produce energy, to pump water or to stay idle).