Wholesale Energy Costs Research Articles

Economic Viability Assessment of Neighbourhood versus Residential Batteries: Insights from an Australian Case Study

Amidst the evolving paradigms of the contemporary energy landscape, marked by the imperative of sustainability and efficiency, the integration of energy storage has emerged as a transformative strategy that seeks to recalibrate the dynamics of electricity distribution and consumption. However, there remains a pressing need to determine the most economically viable approach for deploying energy storage solutions in residential low-voltage (LV) feeders, especially in rural areas. In this context, this paper presents the results of an economic evaluation of energy storage solutions for a residential LV feeder in a rural town in Australia. Specifically, the study compares the financial viability of a front-of-the-meter (FTM) battery installed on the feeder with that of a fleet of behind-the-meter (BTM) batteries. The FTM battery, with a size of 100 kW/200 kWh, is assumed to be operated by the retailer but owned by the community, with any profits assigned to the community. In this scenario, we studied a battery operating under standard network tariffs and three different trial tariffs that distribution network service providers currently offer in Australia. On the other hand, the fleet of BTM batteries (3 kW, 3.3 kWh) are individually owned by households with solar installations, and their cumulative capacity matches that of the FTM battery. The comparison is based on key economic parameters, including network charges, retail margins, frequency control ancillary service (FCAS) revenues, wholesale energy costs, technology costs associated with community batteries, and net profit or loss for the community, as well as considerations of utility grid arbitrage and solar photovoltaic (PV) self-consumption. The study also assumes different grant levels to assess the impact of subsidies on the economic feasibility for both battery configurations. The findings indicate that, while both require some form of subsidy for profitability, the BTM batteries outperform the FTM battery in terms of economic viability and so would require lower grant support. The FTM battery case finds a need for grants ranging from 75% to 95% to break even, while the BTM fleet requires approximately 50% in grants to achieve a similar outcome. In conclusion, this study highlights the importance of grant support in making energy storage solutions economically feasible. In particular, it highlights how the less mature segment of FTM batteries will need higher support initially if it is to compete with BTM. The outcomes of this study inform decision-making processes for implementing energy storage solutions in similar communities, fostering sustainable and cost-effective energy systems.

Relationship between wind power, electric vehicles and charger infrastructure in a two-settlement energy market

This study investigates the technological and economic relationships of integrating wind power, plug-in electric vehicles (PEVs) and mixtures of Level 1/Level 2 charger infrastructures in New York Independent System Operator’s (NYISO’s) two-settlement wholesale electric energy market. Using 7560 scenarios constructed from various PEV penetrations, Level 2 charging and wind dispatch policies, this study reports findings that substantiate and challenge aspects of the previously envisioned synergy between wind power, PEVs and charging infrastructure. An econometric model based on historical market data, including system-level costs of load ramps, was used to study resource integration and to avoid data fidelity issues that plague traditional fundamentals-based models. Results show: (1) the existence of time-series correlation between PEV charging and wind dispatch depends on curtailment policy, (2) PEV charging with wind over-forecast nearly triples the rate of reduction in curtailed wind energy compared to under-forecast, (3) using wholesale energy cost as metric, PEVs can be adversely coupled to curtailable wind, and decoupled with must-take wind, and (4) PEV penetration, Level 2 charging and wind power may be economic substitutes in the energy market.

Arbitraging Intraday Wholesale Energy Market Prices With Aggregations of Thermostatic Loads

We investigate the potential for aggregations of residential thermostatically controlled loads (TCLs), such as air conditioners, to arbitrage intraday wholesale electricity market prices via non-disruptive load control. We present two arbitrage approaches: 1) a benchmark that gives us an optimal policy but requires local computation or real-time communication and 2) an alternative based on a thermal energy storage model, which relies on less computation/communication infrastructure, but is suboptimal. We find that the alternative approach achieves around 60%–80% of the optimal wholesale energy cost savings. We use this approach to compute practical upper bounds for savings via arbitrage with air conditioners in California's intraday energy market. We investigate six sites over four years and find that the savings range from $2–$37 per TCL per year, and depend upon outdoor temperature statistics and price volatility.

Reducing power system costs with thermal energy storage

Thermal energy storage (TES) have been shown to be locally beneficial, helping building managers reduce their electricity bills. Due to increasing interest in TES, it is important for utilities and policy-makers alike to consider the economic implications of increasing TES penetration levels on to the power system. The aim of this paper is to show that TES can also bring significant benefits, and that these benefits are maximized when loads are properly controlled. This paper studies the effect of a heuristic optimal TES load allocation strategy on the New York Independent System Operator (NYISO) system’s load factor, peak-to-valley ratio, ramping, and operation costs. These results are also compared to different control methods in order to justify the need for such a model and also to justify the results. We first determine the total amount of cooling load that can be shifted in New York State through the use of TES technology by using data from various government agencies. Using a coefficient of performance (COP) model for the chiller to account for efficiency changes throughout the day, the flexible cooling demand for the system is estimated. A method to optimally allocate flexible cooling loads is then used with the goal of reducing the power system cost, while providing the necessary cooling load to keep buildings at comfortable temperature levels throughout the state. Power system cost is determined by using a wholesale energy cost model that was developed using NYISO market and load data for both the day-ahead and real-time wholesale markets. By flattening out the system load, increasing the electrical system’s load factor, and reducing system ramping, TES can reduce steady-state and ramping costs, thus reducing the overall power system’s operation costs.

Active Demand Response Using Shared Energy Storage for Household Energy Management

In a deregulated market, wholesale energy costs and distribution investment costs contribute significantly to consumers' electricity bills. However, in a low carbon electrical power system, the two cost pressure points may not be synchronous in time and space with each other. This paper develops a novel methodology for home area energy management as a key vehicle for demand response, using electricity storage devices. The aim is to enable energy storage at consumer premises to not only take advantage of lower wholesale energy prices, but also to support low voltage (LV) distribution networks for reducing network investment. New operation strategies for domestic energy storage to facilitate demand response (DR) are developed in the paper. They have the capability to maximize the overall savings in energy costs and investment costs. In the proposed approach, the operation of home-area energy storage devices is jointly conducted by end customers and network operators. The purpose is to fight for an optimal balance between DRs to energy price and to network congestion, and thus to maximize benefits for both consumers and network operators. An intensive study is carried out to investigate the impacts of different dispatch strategies on wholesale energy costs and network investment costs. Benefit quantification methods are introduced as well to evaluate the total benefits in terms of savings in energy costs and investment costs that can be brought along by the proposed operation approach. The demonstration is carried out on two practical distribution networks with varying utilization levels for one typical calendar day and a whole year.

Intelligent electric vehicle charging: Rethinking the valley-fill

This study proposes an intelligent PEV charging scheme that significantly reduces power system cost while maintaining reliability compared to the widely discussed valley-fill method of aggregated charging in the early morning. This study considers optimal PEV integration into the New York Independent System Operator's (NYISO) day-ahead and real-time wholesale energy markets for 21 days in June, July, and August of 2006, a record-setting summer for peak load. NYISO market and load data is used to develop a statistical Locational Marginal Price (LMP) and wholesale energy cost model. This model considers the high cost of ramping generators at peak-load and the traditional cost of steady-state operation, resulting in a framework with two competing cost objectives. Results show that intelligent charging assigns roughly 80% of PEV load to valley hours to take advantage of low steady-state cost, while placing the remaining 20% equally at shoulder and peak hours to reduce ramping cost. Compared to unregulated PEV charging, intelligent charging reduces system cost by 5–16%; a 4–9% improvement over the flat valley-fill approach. Moreover, a Charge Flexibility Constraint (CFC), independent of market modeling, is constructed from a vehicle-at-home profile and the mixture of Level 1 and Level 2 charging infrastructure. The CFC is found to severely restrict the ability to charge vehicles during the morning load valley. This study further shows that adding more Level 2 chargers without regulating PEV charging will significantly increase wholesale energy cost. Utilizing the proposed intelligent PEV charging method, there is a noticeable reduction in system cost if the penetration of Level 2 chargers is increased from 70/30 to 50/50 (Level 1/Level 2). However, the system benefit is drastically diminished for higher penetrations of Level 2 chargers.

Household response to dynamic pricing of electricity: a survey of 15 experiments

Since the energy crisis of 2000–2001 in the western United States, much attention has been given to boosting demand response in electricity markets. One of the best ways to let that happen is to pass through wholesale energy costs to retail customers. This can be accomplished by letting retail prices vary dynamically, either entirely or partly. For the overwhelming majority of customers, that requires a change out of the metering infrastructure, which may cost as much as $40 billion for the US as a whole. While a good portion of this investment can be covered by savings in distribution system costs, about 40% may remain uncovered. This investment gap could be covered by reductions in power generation costs that could be brought about through demand response. Thus, state regulators in many states are investigating whether customers will respond to the higher prices by lowering demand and if so, by how much. To help inform this assessment, this paper surveys the evidence from the 15 most recent pilots, experiments and full-scale implementations of dynamic pricing of electricity. It finds conclusive evidence that households respond to higher prices by lowering usage. The magnitude of price response depends on several factors, such as the magnitude of the price increase, the presence of central air conditioning and the availability of enabling technologies such as two-way programmable communicating thermostats and always-on gateway systems that allow multiple end-uses to be controlled remotely. In addition, the design of the studies, the tools used to analyze the data and the geography of the assessment influence demand response. Across the range of experiments studied, time-of-use rates induce a drop in peak demand that ranges between 3 and 6% and critical-peak pricing (CPP) tariffs induce a drop in peak demand that ranges between 13 and 20%. When accompanied with enabling technologies, the latter set of tariffs lead to a reduction in peak demand in the 27–44% range.

Household Response to Dynamic Pricing of Electricity - A Survey of the Empirical Evidence

Since the energy crisis of 2000-2001 in the western United States, much attention has been given to boosting demand response in electricity markets. One of the best ways to let that happen is to pass through wholesale energy costs to retail customers. This can be accomplished by letting retail prices vary dynamically, either entirely or partly. For the overwhelming majority of customers, that requires a changeout of the metering infrastructure, which may cost as much as $40 billion for the US as a whole. While a good portion of this investment can be covered by savings in distribution system costs, about 40 percent may remain uncovered. This investment gap could be covered by reductions in power generation costs that could be brought about through demand response. Thus, state regulators in many states are investigating whether customers will respond to the higher prices by lowering demand and if so, by how much. To help inform this assessment, we survey the evidence from the 15 most recent pilots, experiments and full-scale implementations of dynamic pricing of electricity. We find conclusive evidence that households (residential customers) respond to higher prices by lowering usage. The magnitude of price response depends on several factors, such as the magnitude of the price increase, the presence of central air conditioning and the availability of enabling technologies such as two-way programmable communicating thermostats and always-on gateway systems that allow multiple end-uses to be controlled remotely. They also vary with the design of the studies, the tools used to analyze the data and the geography of the assessment. Across the range of experiments studied, time-of-use rates induce a drop in peak demand that ranges between three to six percent and critical-peak pricing tariffs induce a drop in peak demand that ranges between 13 to 20 percent. When accompanied with enabling technologies, the latter set of tariffs lead to a drop in peak demand in the 27 to 44 percent range.

Record high for nuclear power in 2002

This study proposes an intelligent PEV charging scheme that significantly reduces power system cost while maintaining reliability compared to the widely discussed valley-fill method of aggregated charging in the early morning. This study considers optimal PEV integration into the New York Independent System Operator's (NYISO) day-ahead and real-time wholesale energy markets for 21 days in June, July, and August of 2006, a record-setting summer for peak load. NYISO market and load data is used to develop a statistical Locational Marginal Price (LMP) and wholesale energy cost model. This model considers the high cost of ramping generators at peak-load and the traditional cost of steady-state operation, resulting in a framework with two competing cost objectives. Results show that intelligent charging assigns roughly 80% of PEV load to valley hours to take advantage of low steady-state cost, while placing the remaining 20% equally at shoulder and peak hours to reduce ramping cost. Compared to unregulated PEV charging, intelligent charging reduces system cost by 5–16%; a 4–9% improvement over the flat valley-fill approach. Moreover, a Charge Flexibility Constraint (CFC), independent of market modeling, is constructed from a vehicle-at-home profile and the mixture of Level 1 and Level 2 charging infrastructure. The CFC is found to severely restrict the ability to charge vehicles during the morning load valley. This study further shows that adding more Level 2 chargers without regulating PEV charging will significantly increase wholesale energy cost. Utilizing the proposed intelligent PEV charging method, there is a noticeable reduction in system cost if the penetration of Level 2 chargers is increased from 70/30 to 50/50 (Level 1/Level 2). However, the system benefit is drastically diminished for higher penetrations of Level 2 chargers.

Load management at a medium-size utility

Grand Rapids is a medium-size city in northern Minnesota, served by its own municipal utility. The rate structure of its wholesale energy supplier causes wholesale demand charges to be quite high and energy charges to be quite low. A load-management feasibility study showed that major reductions in demand charges could be achieved, and that dual-fuel residential heating could be introduced. Details of water heating and dual-fuel heating analyses, bid evaluation, and promotion techniques are given. The load-management system was installed early in 1988 and is effective in controlling wholesale energy costs for the municipal utility.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>