Johannes Gärttner

Modeling and Valuation of Residential Demand Flexibility for Renewable Energy Integration

The share of renewable generation (RG) in the energy mix has seen constant growth in recent years. RG is volatile and not (fully) controllable. Consequently, the alignment of stochastic demand with supply, which is fundamental for ensuring grid stability, becomes more difficult. The utilization of demand side flexibility as well as RG portfolio design are attractive opportunities to avoid excessive investments in conventional power plants and costs for balancing power. This paper provides a comprehensive centralized scheduling model to exploit demand flexibility from residential devices. We analyze the monetary value of households for demand response (DR) by determining the potential of various current and possible available future end consumer devices to reduce generation costs of a flexibility aggregator in a microgrid with a large share of RG. Furthermore, we identify key characteristics affecting the value of demand flexibility and derive recommendations for an aggregator’s RG portfolio structure. Our simulation results indicate that electric vehicles, stationary batteries, and storage heaters are the most promising devices for residential DR. Furthermore, we show that the potential of a device to directly utilize intermittent RG is largely influenced by the composition of the renewable energy source portfolio.

Trading on local energy markets: A comparison of market designs and bidding strategies

Increasing renewable energy sources and innovative information and communication systems open up new challenges and opportunities to integrate distributed generation into the energy supply system. Formerly centralized energy systems need to be adapted to take full advantage of the immense potential of decentralized energy generation and smart, interconnected energy end users. We introduce a local electricity market on which prosumers and consumers of a community are able to trade electricity directly amongst each other. This local electricity market supports the local integration of renewable energy generation. It facilitates a local balance of energy supply and demand and hence reduces the need for extensive electricity transmission. We introduce, evaluate and compare two local market designs, a direct peer-to-peer market and a closed order book market, as well as two agent behaviors, zero-intelligence agents and intelligently bidding agents. We derive four scenarios by combining each market design with each agent behavior, respectively. All market scenarios offer similar economic advantages for the market participants. However, the peer-to-peer market with intelligent agents appears to be the most advantageous as it results in the lowest average overall electricity price.

Load Shifting, Interrupting or Both? Customer Portfolio Composition in Demand Side Management

The share of renewable power sources in the electricity generation mix has seen enormous growth in recent years. Generation from fluctuating renewable energy sources (Wind, Solar) has to be considered stochastic and not (fully) controllable. To align demand with volatile supply, balancing and storage capacities have to be increased. To avoid high costs of storage investments, we suggest exploiting demand side flexibility instead. This can be operationalized through scheduling of electrical loads. Prior research typically assumes that both the set of customers, as well as the flexibility endowments of the scheduling problem, are exogenously given. However, the quality of the scheduling result highly depends on the composition of the customer portfolio. Therefore, it should be designed in an optimal fashion. This includes two decisions: which customers should be part of the portfolio and how much flexibility each customer should offer. Thus, future energy retailers face a complicated decision-making problem.We present a portfolio design optimization model which includes both selecting customers to be part of the portfolio and scheduling their flexibility. Furthermore, we present exemplary results from a scenario based on empirical load and generation data.

Portfolio and contract design for demand response resources

Abstract Electricity generation from renewable energy sources has seen significant growth in recent years. To improve grid integration of these volatile energy resources, demand side flexibility can be operationalized through intelligent scheduling of flexible electrical loads. Prior research has mainly focused on determining dispatch schedules for exogenously given portfolios of flexible electricity demand. We expand on this literature by considering both contracting and dispatch of flexible loads. To this end, we formulate a demand aggregator’s problem of designing and dispatching a portfolio of supply (volatile renewable and conventional generators) and demand (inflexible base, shiftable and curtailable load) assets as a stochastic program. To account for different contracting regimes, we consider three market scenarios: (1) a liquid flexibility market where the energy retailer is a price-taker, (2) an opaque market where non-strategic customers will accept any individually rational contract offer and (3) a bi-level model with strategic customers optimally self-selecting into available contracts. In the last case, we also explore the effect of price discrimination versus uniform pricing. We evaluate these models using empirical load and generation data. Contrary to conventional wisdom, we find that flexibility contracting is not monotone-increasing in renewable generation capacities. Our research also suggests that curtailable load is a closer substitute to supply flexibility than shiftable load. Finally, we find that contracting of curtailing flexibility will be harder to implement if the aggregator has limited market power.

The role of energy storage in local energy markets

To facilitate the integration of renewable electricity sources into the energy system, innovative market designs must be discussed. Local markets that are organized in a decentralized fashion can help to decrease the need for extensive investment in transmission capacity. To analyze such markets, this work presents an agent-based simulation study of a local peer-to-peer electricity market in a community. The market offers a decentralized marketplace for procuring electricity directly from local renewable generation. We evaluate the market efficiency in terms of the attained rate of self-consumption and the average electricity price depending on the number of potential trading partners in two scenarios: A local market without energy storage and a local market with a community energy storage. The results indicate that a community energy storage can substantially increase the markets efficiency.

Analysis of redispatch and transmission capacity pricing on a local electricity market setup

As the transition to more renewable energy sources progresses the regional generation clusters of wind and solar generation increase. Since the transmission capacity is limited we can observe an increasing need for redispatch measures in the German electricity grid to accommodate this development. In this paper we analyze the need and costs of redispatch measures and propose a local electricity market setup to create economic incentives for the expansion of generation capacity close to load centers. We introduce an analytical model to investigate small networks and a graph model simulation to deal with more sophisticated structures. We find that redispatch is especially relevant in networks with bottleneck transmission links and rather independent of the overall grid capacity. Furthermore, we argue that transmission capacity needs to be priced explicitly and that graph theory can help in investigating market mechanisms in electricity grids.

Using vehicle-to-grid concepts to balance redispatch needs: A case study in Germany

The transition to more sustainable energy generation challenges transmission system operators to include intermittent renewable generation as well as electric vehicles into the power system. Especially in uniform-price power markets, this results in the need for unpopular grid expansions to overcome grid congestion. We analyze the ability of the expanded German transmission grid to cope with the increasing penetration of electric vehicles. We find that uncoordinated charging is likely to overload the transmission system and therefore propose a decentralized local market mechanism to include electric vehicles into the congestion management mechanism. We calculate redispatch needs and the associated possible remuneration of electric vehicle owners. We conclude that EVs can effectively reduce the need for redispatch and receive an according compensation.

Electricity and telecommunication markets: A discussion of market designs

The German electricity market is undergoing the largest transformation since its liberalization. With increasing shares of renewable generation and decreasing spot exchange prices utilities are searching for new business models. Lessons can be learned from the telecommunication industry which has been liberalized at similar times but has been more competitive and customer centric since. In this paper we review the development of both industries along the four dimensions of competition, tariff design, auction design and the quality of service. We then develop an electricity market design based on experiences from the development of the telecommunication industry.