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Investments into renewable energy are increasing rapidly around the world. Energy system models are able to provide insights into optimal investment capacities and thus are widely used to aid the long-term investment decision-making under an electricity market environment. Existing energy system models, however, fail to consider bilateral electricity markets while in reality, these constitute a major part of all energy trades. In this paper, we propose an improved energy system model that endogenously considers mixed bilateral and pool markets. In this model, we also introduce three externality cost items that account for the social cost of technologies, carbon taxes/renewable energy subsidies, and the bilateral product differentiation in the bilateral market, respectively. We start with an equilibrium problem formulation for different market players and next, an equivalent optimization problem is presented. Then, a case study of the pan-European market to reach 95\% emission reduction in 2050 is conducted to demonstrate the model. Different scenarios are constructed to showcase two different usages of product differentiation in the bilateral market, i.e., willingness to pay and exogenous costs. Our main conclusion is that the inclusion of mixed bilateral and pool markets into our enriched energy system model significantly changed the optimal investment capacities, compared to benchmark results from the existing, conventional energy system model. This shows that the inclusion of the bilateral market is of key importance in future investment considerations. Our model is the first of its kind to include this important and realistic bilateral market in energy system models.

We propose a framework where generation and transmission capacities are planned concurrently in market environments with a focus on the prosumers. This paper is a continuation of Part I and presents numerical results from three archetypal case studies. Following the proposed framework, optimal planning decisions are shown in all the cases. Furthermore, in case study I, no-regret planning decisions considering the uncertainties in future electricity market designs are discussed. In case study II, we look at a situation where the social resistance of wind energy prevails and the prosumers choose to not invest in wind energy. This preference results in an increased system cost, and thus may harm other prosumers. The framework is used as a negotiation simulator to deal with this problem. Case study III presents numerical results for a mixed bilateral/pool market. The case studies utilize realistic data from the Dutch power system and the European power system to provide policy-relevant results that aid their decarbonization in various market environments.

Recently, the volatility associated with marginal prices has increased due to large scale integration of renewable generation. Price volatility is undesirable from a consumer perspective. To address this issue, we present a framework for hedging that uses duality theory for quantifying the amount of demand-side flexibility required for constraining marginal prices to the consumers maximum willingness to pay for electricity. Using our formulation, we investigate the ability of an Energy Storage System (ESS), as a demand-side flexibility source, to hedge against electricity price volatility across a multi-time period horizon while accounting for its inter-temporal constraints. Additionally, we analyze the economical benefit that operating the ESS under information forecasts brings to the consumers., Comment: Submitted to IEEE Power and Energy Society General Meeting 2019

Locational Marginal Price (LMP) is a dual variable associated with supply-demand matching and represents the cost of delivering power to a particular location if the load at that location increases. In recent times it become more volatile due to increased integration of renewables that are intermittent. The issue of price volatility is further heightened during periods of grid congestion. Motivated by these problems, we propose a market design where, by constraining dual variables, we determine the amount of demand-side flexibility required to limit the rise of LMP. Through our proposed approach a price requesting load can specify its maximum willingness to pay for electricity and through demand-side flexibility hedge against price volatility. For achieving this, an organizational structure for flexibility management is proposed that exhibits the coordination required between the Distribution System Operator (DSO), an aggregator and the price requesting load. To demonstrate the viability of our proposed formulation, we run an illustrative simulation under infinite and finite line capacities.