Tobias Haring

A framework for and assessment of demand response and energy storage in power systems

The shift in the electricity industry from regulated monopolies to competitive markets as well as the widespread introduction of fluctuating renewable energy sources bring new challenges to power systems. Some of these challenges can be mitigated by using demand response (DR) and energy storage to provide power system services. The aim of this paper is to provide a unified framework that allows us to assess different types of DR and energy storage resources and determine which resources are best suited to which services. We focus on four resources: batteries, plug-in electric vehicles, commercial buildings, and thermostatically controlled loads. We define generic power system services in order to assess the resources. The contribution of the paper is threefold: (i) the development of a framework for assessing DR and energy storage resources; (ii) a detailed analysis of the four resources in terms of ability for providing power system services, and (iii) a comparison of the resources, including an example case for Switzerland. We find that the ability of resources to provide power system services varies largely and also depends on the implementation scenario. Generally, there is large potential to use DR and energy storage for providing power system services, but there are also challenges to be addressed, for example, adequate compensation, privacy, guaranteeing costumer service, etc.

Allocating the Cost of Demand Response Compensation in Wholesale Energy Markets

Currently, demand response resources can sell load reductions in wholesale energy markets. However, paying for load reductions ultimately results in an unbalanced market, where the amount of resources sold (megawatts) is less than the amount of resources bought (megawatts and “negawatts”). To resolve this imbalance, the ISO must allocate the cost of compensating demand response to those buyers who benefit from reduced LMPs. Current cost allocation methods are quite broad and based on each energy buyers share of the total load. In an uncongested network, this results in a “fair” allocation of costs, i.e., an allocation proportional to the benefits that each party accrues. However, in a congested network, this is no longer the case, as price separation occurs between nodes. In this paper, we therefore propose a cost allocation method based on LMP sensitivity that accounts for the effect of congestion on the distribution of benefits between nodes with different LMPs. Since this sensitivity-based method only takes into account the cost allocation per node, we also propose a means of allocating costs between individual load serving entities (LSEs) at a single node. Due to this refinement, LSEs are rewarded according to their individual contribution to demand response. Finally, we define a fairness index to evaluate the performance of the proposed method as compared to a load-based allocation. We find that when load reductions are small (1%-3% total load), the fairness index of the proposed method is very close to zero, indicating almost identical benefit to cost ratios for all market participants. Although the fairness index increases with increasing load reductions, results show that even for larger load reductions, the fairness index is still lower for the proposed method than for the load-based allocation method.

Decentralized contract design for demand response

We introduce a novel contract design framework that enables demand side resources to participate in ancillary services markets in a cost efficient manner. Resources enter contracts with aggregators (which may be utilities) to provide capacity, which is directly controlled by the aggregator via a control signal. The contracting process allows consumers to make choices based upon their own cost/benefit analysis. Additionally, we assume the consumer agents cooperate, which potentially results in greater system benefit than with non-cooperative behavior. We design the contracts to be both incentive compatible and individually rational in the presence of imperfect information exchange between the consumers and the aggregator. Our model gives us insights into the effect of economic and engineering contract design parameters on the amount of reserve provision and the costs of demand response programs. We find more reserves are provided if agents can form separate coalitions for up and down reserves. Further, we find that short duration contracts (e.g., 1-4 hours) are preferable to day-ahead contracts. Additionally, we highlight the benefits of a day-ahead contract with several different pricing periods.

Comparing Centralized and Decentralized Contract Design Enabling Direct Load Control for Reserves

Demand response could provide reserves to power systems and market designs should enable cost-efficient exploitation of these resources. In direct load control programs, consumers provide demand response in exchange for incentive payments. The success of such contracts is a function of level of information sharing, consumer costs, and power system constraints/costs. In this paper, we compare three approaches to contract design, each of which assumes different levels of consumer privacy. Our aim is to explore tradeoffs between privacy, resource exploitation, and the reward earned by the load aggregator. The first approach assumes full and truthful information exchange between the consumer and the system operator. We then develop a novel centralized approach in which an aggregator applies mechanism design to offer contracts to consumers who reveal partial cost information. A novel decentralized approach is developed in which consumers act cooperatively to pool demand response reserves, enabling them to keep individual cost information private. Through simulation studies, we find that, in the centralized approach, resource exploitation/rewards are highly sensitive to the accuracy of the load aggregators consumer cost curves approximations. We also find that in the decentralized approach, rewards can be small, especially if information exchange is costly.

Incentive Compatible Imbalance Settlement

Imbalance settlement markets are managed by the system operators and provide a mechanism for settling the inevitable discrepancies between contractual agreements and physical delivery. In European power markets, settlements schemes are mainly based on heuristic penalties. These arrangements have disadvantages: First, they do not provide transparency about the cost of the reserve capacity that the system operator may have obtained ahead of time, nor about the cost of the balancing energy that is actually deployed. Second, they can be gamed if market participants use the imbalance settlement as an opportunity for market arbitrage, for example if market participants use balancing energy to avoid higher costs through regular trade on illiquid energy markets. Third, current practice hinders the market-based integration of renewable energy and the provision of financial incentives for demand response through rigid penalty rules. In this paper we try to remedy these disadvantages by proposing an imbalance settlement procedure with an incentive compatible cost allocation scheme for reserve capacity and deployed energy. Incentive compatible means that market participants voluntarily and truthfully state their valuation of ancillary services. We show that this approach guarantees revenue sufficiency for the system operator and provides financial incentives for balance responsible parties to keep imbalances close to zero.

Residential Demand Response program design: Engineering and economic perspectives

There exists disagreement on how Demand Response (DR) programs should be designed. This is likely because people from different fields view DR differently. For example, some see DR as a mechanism to improve the economic efficiency of electricity markets while others see it as a new control variable that can enhance power system reliability and security. In this paper, we review the many options for harnessing residential electric loads for DR and consider the engineering and economic implications associated with three specific cases: (1) real time pricing, (2) dispatch-based control via an aggregator participating in wholesale markets, and (3) direct participation in energy markets. We develop both the engineering and the economic arguments for/against each option, and analyze them together in order to understand which options are most suitable for which applications. We find that the appropriate choice of DR program design depends on the DR program objective. Economic goals may be achieved through well-designed pricing and/or bidding mechanisms. Reliability is best achieved through dispatched-based programs. We illustrate our findings with several conceptual examples.

Efficient allocation of balancing and ramping costs

Electricity market designs must evolve to incorporate efficiently the large-scale penetration of renewable energy sources and demand side participation. Current renewable energy support schemes and fixed tariff systems fail to address two major power system operation issues and therefore create additional system costs. First, unlike other commodity markets, the provision of reserve capacity is required for reliable operation. Second, power system operation is stressed by increasing flexibility requirements. One way to reduce these costs is to share the costs of ramping and reserve capacity between consumers, producers and the system operator. We present a market mechanism that reduces the cost of reserve capacity and the cost of ramping in a Pareto-efficient manner. Simulation studies demonstrate the cost reduction that this mechanism achieves as compared with a benchmark approach.

Redesign of the automatic generation control scheme in the Swiss power system

Demand side and energy storage participation can increase the liquidity of ancillary service markets and can have advantages such as faster response than conventional units when they paricipate in the automatic generation control (AGC). Unfortunately, demand and storage units have operational constraints comprising power, energy and on/off duty-cycles. One solution to overcome these limitations is to split the AGC signal into (a) a component which has low ramp rate requirements but does not ensure energy neutral behavior, and (b) a component with high ramp rate requirements but short duration in any direction. This paper presents two methodologies which are implementable in real-time operation and evaluates the requirements in the AGC signal of the Swiss power system. The applied methodologies comprise filtering techniques and an optimization setup. Time domain simulations show that the control performance is at least equal to the current performance level in all cases examined.

Modeling and economic evaluation of Power2Gas technology using energy hub concept

A major challenge in power system operation is the integration of renewable energy in-feed in large scale. Due to the fluctuating nature and seasonal dependency of these energy carriers, excess energy might be curtailed and shortfalls are covered by conventional generation units, since it is possible that sufficient storage capacities are not always available. In this paper we focus on the Power-to-Gas technology as an additional source for enhancing power system operability. Power-to-Gas converts electrical energy into hydrogen or methane, which can be stored or transported via the existing natural gas infrastructure. A major concern is whether this technology is economically valid. In order to address this issue, we propose a model based on the energy hub concept and apply it to historic data. In a simulation study we show, that currently a power-to-gas plant is not economically viable.

On wind farm operation with third-party storage

A major challenge in power system operation is the integration of renewable energy in-feed in large scale. Currently, the responsibility to cope with uncertainty in power injection is transferred to a central authority, i.e. the system operator, while renewable energy in-feed is supported via a tariff system. In this paper we propose market participation of wind farms in combination with a third-party energy storage. A novel concept of storage capacity reservation is presented, where the wind power producer hedges unfavorable wind power realizations with a third-party storage. In a day-ahead scheduling stage, profit maximizing bids for the day-ahead market are stated incorporating costs of storage reservation. During an intra-day stage, the storage device backs up the wind power producer by tracking its day-ahead market bids. In a simulation study we show that after the consideration of the costs of storage reservations and storage operation, the proposed model can lead to profitable operation of wind power plants while reducing the profit variability.